---
-- OS we are using: Ubuntu 19.04
-- Prerequisites:
-- H/W:
-- 256 MB RAM, 512 MB recommended
-- 10 GB Hard Disk
-- S/W:
-- Java8:
-- sudo apt-get update
-- sudo apt-get install openjdk-8-jre
-- Docker CE:
-- Add the GPG key:
-- curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
-- Add repository:
-- sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable edge test"
-- Note that the stable version of docker ce for Ubuntu 19.04 doesn't exist as of this writing
-- Hence, we had to use edge/test version
-- Ensure installing docker from the repository added above, and not from the ubuntu default repo:
-- apt-cache policy docker-ce
-- Install Docker:
-- sudo apt-get install docker -y
-- verify installation: docker version
-- Install Jenkins:
-- Download Jenkins: wget http://mirrors.jenkins.io/war-stable/latest/jenkins.war
-- Compile with Java and assign a web port: java -jar jenkins.war --httpPort=8080
-- Jenkins should be running now on port 8080
-- To access Jenkins, use the IP and port on the browser or curl it
-- It can be accessed via http://localhost:8080 or http://<ipaddress>:8080
-- Following the instructions on the screen to complete the installation
-- In my case the Administrator password was found in /home/networkandcode/.jenkins/secrets/initialAdminPassword
-- That had to be entered to proceed with the installation
-- I have chosen to Install Jenkins with suggested Plugins (recommended by the community)
-- Examples of Plugins are Git, Gradle, LDAP
-- Set up admin credentials, name and email
-- you can change the URL if required
-- The setup is now complete
-- It shows the complete Jenkins dashboard, and new jobs could now be created
-...
ConfigMaps are dictionaries or maps holding a set of key value pairs. ConfigMaps are also Kubernetes objects. For example if there is a Pod and there are lots of configuration in it, we can keep the Pod configuration/manifest simple by keeping all the configuration related information separately as a ConfigMap, and we would then relate the Pod with the ConfigMap so that the Pod takes it's configuration from the ConfigMap.
-
-
-
ConfigMaps can also be thought of like 'Secrets' which are again Kubernetes objects holding key value pairs, however the difference is that Secrets contain encrypted data and are more secure, where as ConfigMaps contain unencrypted data and are often used to store data that is no sensitive
There should be two endpoints for the Jenkins service as there are two Pods
-
-networkandcode@k8s-master:~ kubectl get ep svc29-jenkins-ha
-NAME ENDPOINTS AGE
-svc29-jenkins-ha 10.32.1.7:8080,10.32.2.4:8080 51s
-
-
Check the Service's IP and Ports
-
-networkandcode@k8s-master:~ kubectl get svc svc29-jenkins-ha
-NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
-svc29-jenkins-ha LoadBalancer 10.0.4.207 80:31807/TCP 2m46s
-
-
The Jenkins Application may not be accessible unless the traffic is allowed through the firewall filter, depending on the NodePort value, a firewall rule may be defined as follows
-
-31807 is the NodePort in this case as per the output above, and it can be used to access the Jenkins application via the Node's external IP in the format http://NodeIP:NodePort. These steps are not shown here. The GUI has to be accessed and the credentials be set. We shall use the same credentials for both the Jenkins instances (as there are two Pods).
-
-The initial key for the Jenkins instances could be found as follows
-<
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
A Kubernetes system is said to be distributed because the software might not be installed in just one machine, it could be installed in a collective group of machines serving the whole purpose of a single Kubernetes system. A Kubernetes cluster is a group of nodes(VMs / Physical servers) on which the different components of the overall Kubernetes software are installed. However using VMs as nodes is quite common and popular these days. There are two types of nodes - Masters and Workers(Workers are just called as nodes often). There could be one or more Master in the Cluster, when there are more than one master, we call it a High Available (HA) Cluster. The master nodes are collectively referred to as the control plane, as the master nodes control the worker nodes. Note that it's also possible to install all the master and worker software components onto a single node, which is often referred to as an all in one (AIO) installation, however it's primarily used in learning environments and not recommended for production systems.
-
The main software components that are installed on the master are - kube-apiserver, etcd, kube-scheduler, kube-controller-manager, cloud-controller-manager. And those on the worker nodes are kubelet, kube-proxy, container runtime.
-
kube-apiserver is a REST API server, It is the central software component through which other components of the Master communicate, and it is also used for interconnecting the Kubernetes software components of the Masters and Workers. Any client application or program such as kubectl or some custom code written in any programming language such as python or some familiar programs such as postman should send an HTTP REST API call to the kube-apiserver to retrieve details of the Kubernetes cluster or to modify it's operation. Note that REST refers to a standard and HTTP is a popular RESTful protocol as it conforms to the compliances of REST.
-
etcd is a key-value based data store that is proven to be consistent, when we have more than one master with etcd installed on each, we call the group of etcd components as a high available etcd cluster as etcd by itself is a distributed system and it is leveraged for use with Kubernetes. The etcd components in each master interact with each other. etcd is a separate open source software that can also be used with any other software, not just Kubernetes, it is not a native Kubernetes software component and hence we don't see the word kube on it's name. Key value pairs are like dictionaries or maps used with programming languages. Note that key-value pairs are nothing but a collection of keys to which are like variables and each key holding a value, and the value could be a number, string(text), list(array), or even another dictionary(map) and so on. Since etcd stores all the Kubernetes cluster configuration items, it is necessary to have a backup place in plan for the data stored in the etcd cluster. Since etcd by itself is a separate piece of software, all the etcd components in each of the master would interact with each other directly. Note that In a HA cluster, if there are etcd components in more than one master, these don't have to interact with each other through the kube-apiserver like other components, they would interact directly as they are separate from the native Kubernetes processes, however when etcd wants to talk with other native Kubernetes components, it goes through the kube-apiserver.
-
kube-scheduler is responsible for scheduling or spawning pods on nodes. Pods are the fundamental objects in Kubernetes. Pods would wrap one or more containers inside them as well other associated objects such as volumes that the containers can share. However it's most common to see Pods with single containers. When a Pod is being created, the kube-scheduler is responsible for scheduling it in one of the nodes according to the policies in any as mentioned in the Pod configuration or manifest.
-
kube-controller-manager is a process that is responsible for running Controller processes such as Node Controller, Replication Controller, Endpoints Controller, Service Account & Token Controllers. Node Controller notifies and responds to node down events. Replication Controller helps maintaining the correct number of replicas(Pods) for the Replica Controller Objects. Endpoints Controller handles service endpoints. A service would have endpoints which refer to the associated Pods and their respective ports. Service Account & Token Controllers deal with service accounts, tokens for new namespaces to allow api access etc.
-
cloud-controller-manager is a process that is responsible for running processes that interact with the underlying cloud provider, for example, the Google Kubernetes Engine. These processes include Node Controller, Route Controller, Service Controller, and Volume Controller. Each interacting with specific attributes on the Cloud Provider, for example the Route Controller process is responsible for setting up Network Routes in the underlying cloud.
-
kubelet is the key process in each worker node that ensures that Pods created by Kubernetes are running healthy on the node. Note that kubelet doesn't manager containers that are not created by Kubernetes such as one that's created directly using Docker pull.
-
kube-proxy is a network daemon that helps the functioning of Kubernetes Service objects. It is responsible for orchestrating service VIP(virtual IP) management on the worker node where it's installed. Services are Kubernetes objects and each Service is assigned a Virtual IP.
-
A container runtime process such as Docker, Container-D, frakti, rkt(often as rocket) required on each of the worker nodes so that containers be created. Kubelet interacts with the container runtime to ensure containers specified in the Pod spec are created properly. Kubernetes by itself doesn't create containers, it depends on the container run time, hence this container run time is also an external software and not a native Kubernetes process.
-
In addition to these components, so many add-ons could be enabled in the Kubernetes cluster by creating additional Pods / Services in the kube-system namespace for those respective add-ons. Examples are cluster DNS (this one is essential), Web UI / Dashboard (for a graphical analysis to the cluster and it's objects), container resource monitoring, cluster level logging and so on.
Secrets are objects to store certain sensitive information such as credentials.
-
To view the list of secrets
-
networkandcode@cloudshell:~ (kubernetes-cka-224606)$ kubectl get secrets
-NAME TYPE DATA AGE
-default-token-s5qzc kubernetes.io/service-account-token 3 5d
-
Let's say we want to store a username and password in a new secret object, we have to first get the base64 encoded value for our credentials
-
Let the username be 'secretusername' and password be 'secretpassword', to find the base64 equivalents of these
etcd is a key value kinda database that stores all the Cluster related data, etcd implementation can itself be on separate clusters, or be setup on the nodes that are running as Kubernetes masters. On a High availabilty design, etcd clusters should be odd be in number, i.e. etcd should be installed on odd number of nodes 3, 5, and so on. However we are dealing here with a single ectd node, and etcd is futher or the master node of the k8s-cluster, so there isn't a separate etcd node.
-
-
-
I am using a 4 node cluster - 1 Master and 3 Nodes, on Google cloud, let's start them
The listen-client-urls and advertise-client-rules refer to the same node, however it has two IPs, 127.0.0.1 refers to the localhost itself, as the APIserver and etcd are on the same master node, the APIserver can communicate with etcd using 127.0.0.1, but this IP is not valid outside the host, so if ectd has to be reached from other node in the cluster, that should happen through the private IP, in this case 10.128.0.4, Note that ectd client to server communication happens on TCP port 2379, where as etcd server to server communication happens on TCP port 2389, In our case as there is only one etcd server, no communication happens on 2380
-
-
-
In a Kubernetes cluster, the kube-api-server is the centrail point of contact for all other components, so the etcd server should also communicate with the kube-apiserver, however the speciality here is that the kube-apiserver acts as a client(rather than a server) to talk with etcd server. So, the kube-apiserver is acting like an etcd client. Let's check the apiserver Pod in the cluster, the apiserver should run on the master too
-
-
-
networkandcode@k8s-master:~$ kubectl get all -n kube-system | grep api
-pod/kube-apiserver-k8s-master 1/1 Running 15 47d
-
-networkandcode@k8s-master:~$ kubectl get po kube-apiserver-k8s-master -n kube-system -o wide
-NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
-kube-apiserver-k8s-master 1/1 Running 15 47d 10.128.0.4 k8s-master <none> <none>
-
-
-
-
If we check more info about the apiserver Pod, we should find it has options specify etcd related information
In this cluster, we have a deployment in the default namespace with 10 Pod replicas, please make a note of this as we would illustrate how these deployments would come again once etcd is restored
-
-
-
networkandcode@k8s-master:~/tech/kubernetes/cka$ kubectl get deploy
-NAME READY UP-TO-DATE AVAILABLE AGE
-deploy7 10/10 10 10 9s
-
-
-
As ectd is storing all the cluster data, it's essential to backup it's data periodically, let's do the backup using etcdctl, we need to first install it if it's not there. While taking a backup we can specify pki(public key infrastructure) information such as ca certificate, server certificate and server key, these would match with what's there on the etcd Pod configuration checked earlier
TCP is a window based protocol, i.e. it implements a window based flow control mechanism where the current window size restricts the amount of unacknowledged data that can be transferred between a TCP sender and receiver. Originally this maximum window size awnd(advertised windows) was advertised by the receiver.
-
1980s - new congestion control mechanisms introduced to prevent congestion in the internet caused by TCP senders overrunning resources of the network.
-
1988 - Tahoe TCP released, included 3 congestion control algorithms: slow start, congestion avoidance and fast retransmit. Two new variables cwnd(congestion window) and ssthresh(slow start threshold) introduced.
-
1990 - Reno TCO released, included the fast recovery algorithm
-
-
TCP sender's window size w = min (cwnd, awnd)
-awnd prevents the sender from overrunning the resources of the receiver. cwnd prevents the sender from sending more data than that the network can handle. cwnd can be set according to the packet loss condition which can be detected either via a time-out mechanism or via duplicate ACKs.
-Each packet has a timer (RTO Retransmission timeout) associated with it, and when that timer expires the packet is retransmitted. RTO should be similar to that of an RTT(Round trip time) which is usually calculated using algorithms such as Karn.
-
-
-
-
- {%- include header.html -%}
-
- {%- include analytics.html -%}
-
-
-
-
diff --git a/_posts/2021-06-30-online-shop-with-nextjs-and-harperdb.md b/_posts/2021-06-30-online-shop-with-nextjs-and-harperdb.md
deleted file mode 100644
index 23b1346..0000000
--- a/_posts/2021-06-30-online-shop-with-nextjs-and-harperdb.md
+++ /dev/null
@@ -1,162 +0,0 @@
----
-canonical_url: https://networkandcode.hashnode.dev/online-shop-with-nextjs-and-harperdb
-categories: harperdb, material-ui, nextjs, stripe
-date: 2021-06-30
-tags: harperdb, material-ui, nextjs, stripe
-title: Online shop with NextJS and HarperDB
----
-
-*This post appeared on [hashnode.dev](https://networkandcode.hashnode.dev/online-shop-with-nextjs-and-harperdb)*
-
-Hey All, this post is for someone who wants to build or run an online shop with minimal instructions. The code is available at https://github.com/networkandcode/shop and a sample deployment is available at https://shop-two-chi.vercel.app/
-
-This should help deploying a small site with hundreds of items, if not thousands. So far, I have managed to add features to this site such as authentication, categories, sub categories, items, checkout etc. A todo list is being tracked [here](https://github.com/networkandcode/shop/blob/main/TODO.md).
-
-# Environment Variables
-I am beginning with env vars cause thats what is mainly needed for the deployment part and then will take you through some of the setup and walkthrough. The following environment variables need to be added, either to .env.local or at platforms such as Vercel before deploying. The names of the environment variables are self explanatory.
-
-```
-# Stripe keys
-NEXT_PUBLIC_STRIPE_PUBLISHABLE_KEY
-STRIPE_SECRET_KEY
-STRIPE_SUCCESS_URL
-STRIPE_CANCEL_URL
-
-# Company details
-NEXT_PUBLIC_COMPANY_NAME="Shop"
-NEXT_PUBLIC_HTML_TITLE="Buy Food Items, Apparel, and Accessories at best price."
-NEXT_PUBLIC_MY_DOMAIN="example.com"
-NEXT_PUBLIC_SUB_TITLE_1="Affordable rates and best quality assured."
-NEXT_PUBLIC_SUB_TITLE_2="COD is available at select locations."
-#NEXT_PUBLIC_YOUTUBE_URL="https://youtube.com/c/"
-#NEXT_PUBLIC_WHATSAPP_NUMBER=
-
-# Admin email
-NEXT_PUBLIC_ADMIN = "admin@example.com"
-
-# HarperDB
-HDB_PASSWORD
-HDB_USERNAME
-NEXT_PUBLIC_HDB_PASSWORD
-NEXT_PUBLIC_HDB_SCHEMA
-NEXT_PUBLIC_HDB_URL
-NEXT_PUBLIC_HDB_USERNAME
-
-# Color
-NEXT_PUBLIC_THEME_COLOR
-NEXT_PUBLIC_THEME_COLOR_SEC
-```
-
-With no other customization in the code, if you manage to update just the variables above, you should have a decent site. However, you need to setup the services appropariately before gaining there credentials :).
-
-# HarperDB Setup
-I have used HarperDB studio for setting up the following
-
-## Tables
-- attributes: To store all fixed attributes for an item, something that a buyer can not change, but just view.
-- cart_items
-- categories : all the categories and sub categories.
-- favorites
-- items
-- variable_attributes (attributes that can be changed by the buyer)
-
-## Roles
-- super_user role, this is present by default, it has admin access to all tables
-- read_only role, to read data from all tables except cart_items and favorites
-
-## Users
-Two users, one with super_user role(refers to env varaible HDB_USERNAME) and one with read_only role(refers to NEXT_PUBLIC_HDB_USERNAME).
-
-The read only user is used for accessing items and categories publicly from the client(browser), and the super user with privileged access is used for operations such as modifying items, updating cart, via the server. Note that variables that start with NEXT_PUBLIC are accessible from the client itself.
-
-## Attributes
-The attributes and variable_attributes records are modified directly via the HarperDB studio at the moment, and not through code. Sample records and screenshots are below.
-
-```
-{
- name: 'Pattern',
- values: [
- 'Checks',
- 'Stripes',
- 'Plain',
- 'Printed'
- ]
-}
-```
-
-
-
-```
-{
- name: 'Size',
- values: [
- 'xs',
- 's',
- 'm',
- 'l',
- 'xl',
- 'xxl',
- 'xxxl'
- ]
-}
-```
-
-
-# Admin walkthrough
-
-## Sign in
-
-Click the PowerSettings icon at the top right
-
-and then login with your admin email and password
-
-
-
-Cick on the supervisor icon to add items or categories
-
-
-## Add items
-
-Here you can enter the name, description and price of the item. You have to select the category or subcategory from the drop-down list. And finally upload a relevant image for the item.
-
-## Add categories
-
-Enter the name of the category to be created, select a parent category only if you are creating a sub category. And select the fixed(buyers can't change) and variable(buyers can change) attributes if required. And finally upload a relevant image for the category. Please do not include '/' in the category name.
-
-# Buyer walk through
-Signin just like admin, and select a category from the homepage, for example Accessories, it has 1 item as shown in parantheses.
-
-
-
-Click on the Item pic
-
-
- This opens up a dialog, set the quantity and any other attributes if applicable and update the cart.
-
-
-
-Once the cart is updated, the dialog can be closed. The checkout icon at the appbar should show the total cart amount.
-
-Clicking on that would take you to the checkout page
-
-
-
-Click on proceed to pay, and then the proceed to payment gateway button
-
-
-The email will be populated automatically, fill rest of the details and pay, If you have used stripe's test api key, you can enter the card number as 4242 4242 4242 4242. Click pay and you are done.
-
-
-
-Well, thats the overview of the website I have developed for the #HarperDBHackathon, hope it has some stuff in it, and there could definitely be bugs, and lots of room for improvement. Suggestions are welcome, and thank you @[Hashnode](@hashnode) and HarperDB for the opportunity.
-
-Here is some final notes on what I liked about HarperDB:
-- Tabular and JSON way of representing records (in the studio).
-- Support for both SQL and NoSQL queries.
-- Good reference to multiple libraries(I have chosen fetch and axios), on the docs site.
-- Roles are neat, no confusion, no complexity, anyone can easily understand what they mean.
-
-*Credits: Firebase(for authentication and storage), HarperDB, @hashnode, Material-UI, NextJS, ReactJS, Stripe, Unsplash, Vercel, and lots of other great online resources*
-
---end-of-post--
-
diff --git a/_posts/2022-01-16-run-svelte-app-on-aws-cloud9.md b/_posts/2022-01-16-run-svelte-app-on-aws-cloud9.md
deleted file mode 100644
index 27e3a3a..0000000
--- a/_posts/2022-01-16-run-svelte-app-on-aws-cloud9.md
+++ /dev/null
@@ -1,201 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/run-svelte-app-on-aws-cloud9-4j5b
-categories: aws, cloud, solidjs, svelte
-date: 2022-01-16
-tags: aws, cloud, solidjs, svelte
-title: Run Svelte/Solid app on AWS Cloud9
----
-
-*This post first appeared on [dev.to](https://dev.to/aws-builders/run-svelte-app-on-aws-cloud9-4j5b)
-
-
-Hey all :wave:, let's say you do not have a system with sufficient memory / CPU, to write code on IDE and then subsequently test / run it, or if you want to test code on a Linux instance such as Ubuntu/Amazon Linux2, or may be you just keep things related to development isolated and you don't want to mess around with your machine, you could then leverage the online IDE offered by [AWS Cloud9](https://aws.amazon.com/cloud9/) to overcome all such restrictions and also use it's preview functionality, to test the app right there. Your work is also saved, and the associated instance gets terminated if it's idle based on the cost savings duration set.
-
-You could also access other AWS services right from AWS Cloud9 too. I've been liking :green_heart:Cloud9 so far, and in this post I would just show how to setup and run the Svelte boilerplate, and then preview it on Cloud9. Svelte as most are aware is quite popular these days, seems a bit easy/fun to learn too.
-
-Let's get started, by launching AWS cloud9. Search for Cloud9 on the AWS console, which should look like:
-
-
-And then create a new environment
-
-
-Give it some name
-
-
-I left all the other settings to be default, you may modify as required. The default settings in my case should launch an evironment with the following details:
-- Name: cloud9-svelte
-- Description: No description provided
-- Environment type: EC2
-- Instance type: t2.micro
-- Platform: Amazon Linux 2 (recommended)
-- Cost-saving settings: After 30 minutes (default)
-- IAM role: AWSServiceRoleForAWSCloud9 (generated)
-
-Note that Cloud9 only offers 3 platforms for now, to choose from.
-
-
-The environment get's created in a while, once the create button is clicked.
-
-
-There should be a bash terminal on which I am now going to run certain commands.
-
-
-You can just drag the tiny bash window to the top and close other tabs that are not required.
-
-Let's use degit as menitoned in the [Svelte](https://svelte.dev/blog/the-easiest-way-to-get-started) quick start guide, to bootstrap the svelte project.
-```
-nc:~/environment $ npx degit sveltejs/template my-svelte-project
-Need to install the following packages:
- degit
-Ok to proceed? (y) y
-> cloned sveltejs/template#HEAD to my-svelte-project
-npm notice
-npm notice New minor version of npm available! 8.1.2 -> 8.3.1
-npm notice Changelog: https://github.com/npm/cli/releases/tag/v8.3.1
-npm notice Run npm install -g npm@8.3.1 to update!
-npm notice
-```
-We can acknowledge the npm notice and update npm, if required.
-```
-nc:~/environment $ npm install -g npm@8.3.1
-
-removed 8 packages, changed 38 packages, and audited 215 packages in 3s
-
-10 packages are looking for funding
- run `npm fund` for details
-
-3 moderate severity vulnerabilities
-
-To address all issues, run:
- npm audit fix
-
-Run `npm audit` for details.
-```
-
-Change to the project directory and then install the node modules.
-```
-nc:~/environment/my-svelte-project $ npm i
-
-added 97 packages, and audited 98 packages in 6s
-
-7 packages are looking for funding
- run `npm fund` for details
-
-found 0 vulnerabilities
-```
-Excellent, npm found no vulnerabilities.
-
-Well, that's it run the Svelte app.
-```
-nc:~/environment/my-svelte-project $ npm run dev
-
- > svelte-app@1.0.0 dev
-> rollup -c -w
-
-rollup v2.64.0
-bundles src/main.js → public/build/bundle.js...
-LiveReload enabled
-created public/build/bundle.js in 487ms
-
-[2022-01-16 09:39:48] waiting for changes...
-
-> svelte-app@1.0.0 start
-> sirv public --no-clear "--dev"
-
-
- Your application is ready~! 🚀
-
- - Local: http://localhost:8080
- - Network: Add `--host` to expose
-
-────────────────── LOGS ──────────────────
-
-```
-Make a note that it's running on port 8080, based on the output above.
-
-Let's see if the app is working by using the curl command. press ALT T to open a new bash terminal. On the new terminal, execute the following command.
-```
-nc:~/environment $ curl localhost:8080
-
-
-
-
-
-
- Svelte app
-
-
-
-
-
-
-
-
-
-
-
-```
-
-So, we verified the app is working through the CLI:black_circle:. We can now try it on the browser. Hit Preview > Preview Running Application on the top bar. Boom:boom:, you should see the Svelte app on the preview browser tab. 
-
-This is so far, local preview, what if you want to view it from the Internet:globe_with_meridians:, or let's say your friends want to view your app over the Internet while you are developing it. Let's exactly see that now, let's get the instance's public IP.
-```
-nc:~/environment $ curl https://checkip.amazonaws.com
-
-```
-
-We have to now modify the security group, for which we can visit the EC2 instances page on AWS console, and select our instance id.
-
-And then click on the Security group name in the Security tab. You can edit the inbound rules here.
-
-
-A rule can be added to allow port 8080, from your local machine.
-
-
-Optionally, you can also add other source IPs, its always better to restrict traffic to minimal and known sources instead of applying rule for a broader range or subnet.
-
-Save rules and you are done.
-
-
-Let's stop the npm process by hitting Ctl C. And then run it again by prepending HOST=0.0.0.0. [Here](https://stackoverflow.com/questions/63255453/running-svelte-dev-on-server) is why.
-```
-nc:~/environment/my-svelte-project $ HOST=0.0.0.0 npm run dev
-
-> svelte-app@1.0.0 dev
-> rollup -c -w
-
-rollup v2.64.0
-bundles src/main.js → public/build/bundle.js...
-LiveReload enabled
-created public/build/bundle.js in 476ms
-
-[2022-01-16 10:22:50] waiting for changes...
-
-> svelte-app@1.0.0 start
-> sirv public --no-clear "--dev"
-
-
- Your application is ready~! 🚀
-
- - Local: http://0.0.0.0:8080
- - Network: http://172.31.4.12:8080
-
-────────────────── LOGS ──────────────────
-
-```
-
-If you now try to visit the Cloud9 instance's public IP on the browser, from your local machine, over port 8080, it should work.
-
-
-
-That's for the post, so you can make use of the online IDE offered by AWS Cloud9 and develop apps on the go. Thanks for reading !!!
-
-Update:
-You can run [solid.js](https://docs.solidjs.com/guides/getting-started-with-solid/installing-solid) apps the same way. You can try the following commands:
-```
-npx degit solidjs/templates/ts my-app
-cd my-app
-npm i
-npm run dev -- --host --port 8080
-```
-
\ No newline at end of file
diff --git a/_posts/2022-03-19-nextjs-deployment-via-aws-codecommit-amplify.md b/_posts/2022-03-19-nextjs-deployment-via-aws-codecommit-amplify.md
deleted file mode 100644
index d17ba83..0000000
--- a/_posts/2022-03-19-nextjs-deployment-via-aws-codecommit-amplify.md
+++ /dev/null
@@ -1,143 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/nextjs-deployment-via-aws-codecommit-amplify-6oj
-categories: amplify, aws, cicd, nextjs
-date: 2022-03-19
-tags: amplify, aws, cicd, nextjs
-title: NextJS deployment via AWS CodeCommit / Amplify
----
-
-*This post first appeared on [dev.to](https://dev.to/aws-builders/nextjs-deployment-via-aws-codecommit-amplify-6oj/edit)*
-
-
-Hey All :wave:, Let's see how to add the NextJS starter code in an AWS CodeCommit repo and deploy it with AWS Amplify. I am using the [Cloud9](https://dev.to/aws-builders/run-svelte-app-on-aws-cloud9-4j5b) IDE :cloud: for this exercise. You may follow these steps on any Linux/Unix based machine though.
-
-I am using [aws cli v2](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html). You may upgrade the version if required. Also ensure you have setup the CLI with the required authentication config.
-
-```
-$ aws --version
-aws-cli/2.4.27 Python/3.8.8 Linux/4.14.262-200.489.amzn2.x86_64 exe/x86_64.amzn.2 prompt/off
-```
-
-The user id I'm using has administrator permissions :fire:, so I shouldn't have any issues while creating the repo. If not an admin, the IAM user should be setup with [CodeCommit policies] (https://docs.aws.amazon.com/codecommit/latest/userguide/security-iam-awsmanpol.html).
-
-Let's go ahead and create the repo.
-```
-$ aws codecommit create-repository --repository-name next-js-boilerplate --repository-description "Boilerplate code for NextJS" --tag "code=JavaScript,framework=NextJS"
-{
- "repositoryMetadata": {
- "accountId": "",
- "repositoryId": "",
- "repositoryName": "next-js-boilerplate",
- "repositoryDescription": "Boilerplate code for NextJS",
- "lastModifiedDate": "2022-03-19T08:17:28.327000+00:00",
- "creationDate": "2022-03-19T08:17:28.327000+00:00",
- "cloneUrlHttp": "https://git-codecommit.us-east-2.amazonaws.com/v1/repos/next-js-boilerplate",
- "cloneUrlSsh": "ssh://git-codecommit.us-east-2.amazonaws.com/v1/repos/next-js-boilerplate",
- "Arn": "arn:aws:codecommit:us-east-2::next-js-boilerplate"
- }
-}
-```
-
-The repo :file_folder: is created and should appear in the list of repositories.
-```
-$ aws codecommit list-repositories --output text
-REPOSITORIES next-js-boilerplate
-```
-Can be checked on the AWS console too, on the browser.
-
-
-We are going to connect to the repo via SSH for which we have to upload the SSH public key to the AWS user account. But before that you have to ensure the SSH key is already generated. You may refer to this [link](https://docs.aws.amazon.com/codecommit/latest/userguide/setting-up-ssh-unixes.html) if you want to know how to generate the SSH key pair. The public key in my system is at the standard location i.e. ~/.ssh/id_rsa.pub.
-
-Let's upload this key :key: and retrieve the public key id.
-```
-$ SSHPublicKeyId=$(aws iam upload-ssh-public-key --user-name nc --ssh-public-key-body file://~/.ssh/id_rsa.pub --output text --query SSHPublicKey.SSHPublicKeyId)
-```
-
-Setup SSH config, and modify its permission so that only the owner(current user) of the file can access it(Read + Write).
-```
-$ cat > ~/.ssh/config <..." to include in what will be committed)
- .eslintrc.json
- .gitignore
- README.md
- next.config.js
- package-lock.json
- package.json
- pages/
- public/
- styles/
-
-$ git add .
-$ git commit -m 'adding nextjs boiler plate code'
-
-$ git push
-```
-
-We can verify this on the AWS console.
-
-
-
-:cool: we can now deploy this code via AWS Amplify, I am going to use the GUI for this.
-
-Search for Amplify, create a new app, and then choose CodeCommit.
-
-
-The next step is as follows, to select the correct repo and branch.
-
-
-Jus continue to the final step with no changes, and deploy.
-
-
-In a few minutes :stopwatch:, the app should be deployed. We should see the 4 stages(provision, build, deploy and verify) to be successful. There should also be a testing stage, which we haven't used here, as no tests are written.
-
-
-You should now be able to view :arrow_forward: the application by clicking on the https link provided above.
-
-
-Thus, we have gone through some parts of CodeCommit and Amplify. CLI was used with CodeCommit, just to see the power of AWS CLI and I think many cloud operations are possible with it. Note that we can customize Amplify deployments with environment variables, build command modifications etc.
-
-That's it for now, :slightly_smiling_face: thanks for reading...
\ No newline at end of file
diff --git a/_posts/2022-04-10-serverless-backend-setup-for-a-todo-list-in-aws.md b/_posts/2022-04-10-serverless-backend-setup-for-a-todo-list-in-aws.md
deleted file mode 100644
index cd265dc..0000000
--- a/_posts/2022-04-10-serverless-backend-setup-for-a-todo-list-in-aws.md
+++ /dev/null
@@ -1,286 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/serverless-backend-setup-for-a-todo-list-in-aws-189l
-categories: api, aws, lambda, serverless
-date: 2022-04-10
-tags: api, aws, lambda, serverless
-title: Serverless backend setup for a todo list in AWS
----
-
-*This post first appeared on [dev.to](https://dev.to/aws-builders/serverless-backend-setup-for-a-todo-list-in-aws-189l)
-
-Hello :wave:, in this post :pencil: we are going to build a simple backend for a todo application using [AWS services](https://docs.aws.amazon.com/apigateway/latest/developerguide/http-api-dynamo-db.html) :cloud: such as AWS API Gateway, AWS Lambda and AWS DynamoDB.
-
-Starting with DynamoDB, we are gonna setup a table with **task** as the hash / partition key:key:. This table is a simple one with four fields task, description, date and done(binary). We don't have to specify all the fields while creating the table though except the hash key, the fields could be created dynamically while we add data to the table.
-
-
-Leave rest of the settings to the default and create the table.
-
-Next, lets go to IAM and create a policy :page_with_curl: which would allow CRUD operations on our DynamoDB table todo. I have set CrudOhioDynamoTodoTable as the policy name as Ohio(us-east-2) is the region where the table was created. You may visit this [site](https://awspolicygen.s3.amazonaws.com/policygen.html) to generate policies:vertical_traffic_light:. The policy json is as follows.
-```
-{
- "Version": "2012-10-17",
- "Statement": [
- {
- "Action": [
- "dynamodb:DeleteItem",
- "dynamodb:GetItem",
- "dynamodb:PutItem",
- "dynamodb:Scan",
- "dynamodb:UpdateItem"
- ],
- "Effect": "Allow",
- "Resource": "arn:aws:dynamodb:us-east-2::table/todo"
- }
- ]
-}
-```
-
-
-We have to now create a role and attach this policy.
-
-
-Select the use case as Lambda and on the next page select the policy we have created.
-
-
-Choose a name for the Role, for ex. LambdaToCrudOhioDynamoTodoTable, and finally create the role.
-
-
-*Progress so far: Lambda service role > Crud Policy > DynamoDB*
-
-So the IAM part is done, we are good to create the Lambda function now and attach the role to it. Just set a function name (ex. todo) and set the execution role to the role we created. Rest of the settings can be default.
-
-
-
-Replace the code in index.js with the following and deploy the function.
-```
-const AWS = require("aws-sdk");
-
-const dynamo = new AWS.DynamoDB.DocumentClient();
-
-exports.handler = async (event, context) => {
- let body;
- let statusCode = 200;
- const headers = {
- "Content-Type": "application/json"
- };
-
- try {
- switch (event.routeKey) {
- case "DELETE /tasks/{task}":
- await dynamo
- .delete({
- TableName: "todo",
- Key: {
- task: event.pathParameters.task
- }
- })
- .promise();
- body = `Deleted task ${event.pathParameters.task}`;
- break;
-
- case "GET /tasks/{task}":
- body = await dynamo
- .get({
- TableName: "todo",
- Key: {
- task: event.pathParameters.task
- }
- })
- .promise();
- break;
-
- case "GET /tasks":
- body = await dynamo.scan({ TableName: "todo" }).promise();
- break;
-
- case "PUT /tasks":
- let requestJSON = JSON.parse(event.body);
- await dynamo
- .put({
- TableName: "todo",
- Item: {
- task: requestJSON.task,
- description: requestJSON.description,
- date: requestJSON.date,
- done: requestJSON.done ? true : false
- }
- })
- .promise();
- body = `New task added: ${requestJSON.task}`;
- break;
-
- default:
- throw new Error(`Unsupported route: "${event.routeKey}"`);
- }
- } catch (err) {
- statusCode = 400;
- body = err.message;
- } finally {
- body = JSON.stringify(body);
- }
-
- return {
- statusCode,
- body,
- headers
- };
-};
-```
-
-Ok so our Lambda function is ready.
-Lambda Function > Lambda Role > Crud Policy > Dynamo DB
-
-What's next, something should invoke the Lambda, which is our API. Let's create a single API gateway with relevant API methods.
-
-Go to API gateway on the console, and create an HTTP API with lambda integration.
-
-
-And next the routes.
-
-
-The gateway can be created with other prompts set to default values.
-
-
-Make a note of the execution URL, as that would be used to make API calls.
-
-I am going to better set it as an environment variable, so that I don't have to keep typing the longer URL for the rest of the post.
-```
-$ executionURL=https://j6yotbi8ta.execute-api.us-east-2.amazonaws.com
-```
-
-Hmm ok, so I think our backend is kinda setup now with this.
-API gateway > Lambda Function > Lambda Role > CRUD policy > DynamoDB
-
-Let's try making some calls and see if it actually works.
-```
-$ curl -X PUT ${executionURL}/tasks -H "Content-Type: application/json" -d '{
-"task": "BuyBooks",
-"description": "Buy Java and System Design books from Amazon",
-"date": "10-Apr-2022"
-}'
-"New task added: BuyBooks"
-
- $ curl -X PUT ${executionURL}/tasks -H "Content-Type: application/json" -d '{
-"task": "ShutEC2Instances",
-"description": "Shut down the unused EC2 instances to avoid billing",
-"date": "10-Apr-2022"
-}'
-"New task added: ShutEC2Instances"
-```
-We were able to successfully add couple new tasks with the PUT method.
-
-Let's retrieve all items from the DB table.
-```
-$ curl --silent ${executionURL}/tasks | jq
-{
- "Items": [
- {
- "date": "10-Apr-2022",
- "task": "ShutEC2Instances",
- "description": "Shut down the unused EC2 instances to avoid billing",
- "done": false
- },
- {
- "date": "10-Apr-2022",
- "task": "BuyBooks",
- "description": "Buy Java and System Design books from Amazon",
- "done": false
- }
- ],
- "Count": 2,
- "ScannedCount": 2
-}
-```
-
-And now, retrieve items based on the primary key which in our case is task.
-```
-$ curl --silent ${executionURL}/tasks/BuyBooks | jq
-{
- "Item": {
- "date": "10-Apr-2022",
- "task": "BuyBooks",
- "description": "Buy Java and System Design books from Amazon",
- "done": false
- }
-}
-
-$ curl --silent ${executionURL}/tasks/ShutEC2Instances | jq
-{
- "Item": {
- "date": "10-Apr-2022",
- "task": "ShutEC2Instances",
- "description": "Shut down the unused EC2 instances to avoid billing",
- "done": false
- }
-}
-```
-Lets make couple changes to the tasks. For the first one Java is replaced with JavaScript, and the second one I'm setting done as true.
-```
-$ curl -X PUT https://j6yotbi8ta.execute-api.us-east-2.amazonaws.com/tasks -H "Content-Type: application/json" -d '{
-"task": "BuyBooks",
-"description": "Buy JavaScript and System Design books from Amazon",
-"date": "10-Apr-2022"
-}'
-"New task added: BuyBooks"
-
-$ curl -X PUT https://j6yotbi8ta.execute-api.us-east-2.amazonaws.com/tasks -H "Content-Type: application/json" -d '{
-"task": "ShutEC2Instances",
-"description": "Shut down the unused EC2 instances to avoid billing",
-"date": "10-Apr-2022", "done": "true"
-}'
-"New task added: ShutEC2Instances"
-```
-The put method either creates a new item, or replaces an existing item, which I think is fine in our case as our table is kinda small. Let's view the contents one more time.
-```
-$ curl --silent https://j6yotbi8ta.execute-api.us-east-2.amazonaws.com/tasks | jq
-{
- "Items": [
- {
- "date": "10-Apr-2022",
- "task": "ShutEC2Instances",
- "description": "Shut down the unused EC2 instances to avoid billing",
- "done": true
- },
- {
- "date": "10-Apr-2022",
- "task": "BuyBooks",
- "description": "Buy JavaScript and System Design books from Amazon",
- "done": false
- }
- ],
- "Count": 2,
- "ScannedCount": 2
-}
-```
-The value for "done" is boolean though we have set it as string while executing the curl command, this is due to the following code in Lambda function.
-```
-done: requestJSON.done ? true : false
-```
-
-Finally, the delete method.
-```
-$ curl -X DELETE ${executionURL}/tasks/ShutEC2Instances "Deleted task ShutEC2Instances"
-
-$ curl -X DELETE ${executionURL}/tasks/BuyBooks
-"Deleted task BuyBooks"
-```
-So we have been sending unauthenticated calls from CURL. For some security, we can add IAM authorizer to all the routes.
-
-
-With this, we shouldn't be able to make calls like before, we should now be authenticated and authorized.
-```
-$ curl ${executionUrl}/tasks | jq
-curl: (3) URL using bad/illegal format or missing URL
-```
-
-Let's use [postman](https://aws.amazon.com/premiumsupport/knowledge-center/iam-authentication-api-gateway/) as its easy to send requests from it with AWS signature.
-
-
-The IAM user whose credentials are entered should have permissions to send API calls to the API gateway. In my case the user id has admin permissions and hence it works good.
-
-
-Well that's it for this post.. :thumbsup: So we saw how to setup the backend for a mini todo application with API gateway, Lambda and IAM. And we tested it with a few API calls via CURL(with out authentication) and Postman(with IAM authentication).
-
-But what's pending, we could have some sort of a web frontend that could send API calls to the API gateway using client libraries such as fetch, axios etc. just like CURL / Postman did it for us from the CLI / Desktop, thus resulting in a proper web application...
-
-Thanks for reading !!! Don't forget to delete the resources you have created, if they are no longer in use :)
\ No newline at end of file
diff --git a/_posts/2022-05-12-cricket-scoring-app-using-appwrite-nextjs.md b/_posts/2022-05-12-cricket-scoring-app-using-appwrite-nextjs.md
deleted file mode 100644
index a67f3c1..0000000
--- a/_posts/2022-05-12-cricket-scoring-app-using-appwrite-nextjs.md
+++ /dev/null
@@ -1,46 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/cricket-scoring-app-using-appwrite-nextjs-3730
-categories: appwritehack, cricker, nextjs, webdev
-date: 2022-05-12
-tags: appwritehack, cricker, nextjs, webdev
-title: Cricket scoring app using Appwrite & NextJS
----
-
-*This post first appeared on [dev.to](https://dev.to/networkandcode/cricket-scoring-app-using-appwrite-nextjs-3730)
-
-[Instructions]: # (To submit to the Appwrite Hackathon on DEV, please fill out all sections.)
-
-
-### Overview of My Submission
-Hi, this is an attempt to learn appwrite by trying out a single user cricket scoring app. We play cricket hence the idea, thought it would be nice to have an app that we can use for ourselves to add scoring and see how we played :).
-
-I have used NextJS with some minimal tailwind based styling, have spent more time on the functonality of the App as the state changes, due to various scoring conditions, were a bit confusing and time consuming.
-
-Here is the link to the [github repository] (https://github.com/networkandcode/cricscore/tree/appwrite-hackathon)
-
-### Submission Category:
-Wacky Wildcards
-
-
-
-
-### Additional Resources / Info
-Here are some screenshots
-
-
-
-
-
-
-
-
-
-
-
-
-
-Note: The image at the bottom is a random one from [Unsplash](https://source.unsplash.com/featured/?wickets)
-
-FYI, the application is not quite complete, there is some more state improvements.
-
-Thank you!!!
\ No newline at end of file
diff --git a/_posts/2022-05-19-cricket-scoring-app-with-appwrite-and-nextjs-contd.md b/_posts/2022-05-19-cricket-scoring-app-with-appwrite-and-nextjs-contd.md
deleted file mode 100644
index c476474..0000000
--- a/_posts/2022-05-19-cricket-scoring-app-with-appwrite-and-nextjs-contd.md
+++ /dev/null
@@ -1,389 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/cricket-scoring-app-with-appwrite-and-nextjscontd-2k64
-categories: appwrite, nextjs, react, tailwindcss
-date: 2022-05-19
-tags: appwrite, nextjs, react, tailwindcss
-title: Cricket scoring app with Appwrite and NextJS(contd.)
----
-
-*This post first appeared on [dev.to](https://dev.to/networkandcode/cricket-scoring-app-with-appwrite-and-nextjscontd-2k64/edit)*
-
-Hey all :wave:, this is in continuation to the [previous post](https://dev.to/networkandcode/cricket-scoring-app-using-appwrite-nextjs-3730), that covered changes done on the [appwrite-hackathon](https://github.com/networkandcode/cricscore/tree/appwrite-hackathon) branch, which was mainly kept and submitted for the hackathon.
-
-This post is not part of the [hackathon](https://dev.to/t/appwritehack), as it's over. I thought I would share a few more changes I have done recently, which should be visible on the [main](https://github.com/networkandcode/cricscore/tree/main) branch, and a preview is available via [vercel](https://cricscore.vercel.app/) hosting. Note that the web app may not work properly just in case the backend Appwrite server is not on, as I have used EC2 on [AWS Cloud9](https://dev.to/aws-builders/run-svelte-app-on-aws-cloud9-4j5b) for setting it up and there are chances it can be shut when idle.
-
-Ok, so here are a few screenshots from Appwrite that shows some backend, DB configuration etc.
-
-Make sure the platform configuration allows requests from the client URL, in my case it's as follows.
-Thank you @meldiron for the quick help on this platform stuff.
-
-I have setup appwrite with a custom domain, by adding an IPv4 A record for a subdomain pointing to the EC2 instance's elastic IP. The DNS configuration can be done where you bought the domain from, with out any namespace changes. Since I am using Appwrite over a domain, I have to do two extra things at Appwrite side, first the env variable _APP_DOMAIN_TARGET should be set to what ever domain over which you are intending to use Appwrite and then, you need to go the custom domains section and add the same URL.
-
-
-And once the .env file is setup properly Appwrite can be reinstalled/installed with `docker-compose up`, so you would need to first download both docker-compose.yaml and .env from the recent URL provided by [Appwrite](https://appwrite.io/docs/installation#manual), and also should have installed [docker-compose](https://docs.docker.com/compose/install/).
-
-```
-$ cat .env | grep -i DOMAIN_TARGET
-_APP_DOMAIN_TARGET=
-```
-
-The docker compose file should create a bunch of containers :fire:.
-```
-$ docker container ls | grep appwrite | awk '{print $2}' | uniq
-appwrite/appwrite:0.13.0
-traefik:2.5
-appwrite/appwrite:0.13.0
-redis:6.0-alpine3.12
-mariadb:10.7
-appwrite/telegraf:1.2.0
-appwrite/influxdb:1.0.0
-```
-As seen above, appwrite also uses mariadb behind the scenes. Though I have used 0.13 here, [0.14](https://hub.docker.com/layers/appwrite/appwrite/appwrite/0.14/images/sha256-357db37e2db12816a8bb79c816b3fbdd86e6df1ae9358c265ba5a59599ab975d?context=explore) is already out:new:. I would plan for an upgrade though, just seeing how I can do a seamless upgrade.
-
-What else, some screenshots from Appwrite that shows the DB fields.
-
-The collections are as follows.
-
-
-
-And all the collections are setup with document level permissions.
-
-
-The atrributes and indexes for each collection are as follows.
-
-Players:
-```
- "attributes": [
- {
- "key": "username",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "format": "email",
- "default": null
- },
- {
- "key": "players",
- "type": "string",
- "status": "available",
- "required": true,
- "array": true,
- "size": 255,
- "default": null
- }
- ]
-```
-
-Matches:
-```
-"attributes": [
- {
- "key": "matchName",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "matchNoOfPlayers",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "matchNoOfOvers",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "matchPlace",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "matchStatus",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "teamAName",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "teamAPlayers",
- "type": "string",
- "status": "available",
- "required": true,
- "array": true,
- "size": 255,
- "default": null
- },
- {
- "key": "teamBName",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "teamBPlayers",
- "type": "string",
- "status": "available",
- "required": true,
- "array": true,
- "size": 255,
- "default": null
- },
- {
- "key": "tossWinner",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "tossWinnerChoice",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "userID",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "winner",
- "type": "string",
- "status": "available",
- "required": false,
- "array": false,
- "size": 255,
- "default": null
- }
- ]
-```
-
-Overs:
-```
-"attributes": [
- {
- "key": "balls",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "bowler",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "matchID",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "innings",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "over",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "runs",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "wickets",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- }
- ],
- "indexes": [
- {
- "key": "matchID",
- "type": "key",
- "status": "available",
- "attributes": [
- "matchID"
- ],
- "orders": [
- "ASC"
- ]
- }
- ]
-```
-
-BattingScoreCard:
-```
-"attributes": [
- {
- "key": "balls",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "batsman",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "batsmanNo",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "innings",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "matchID",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "position",
- "type": "string",
- "status": "available",
- "required": true,
- "array": false,
- "size": 255,
- "default": null
- },
- {
- "key": "runs",
- "type": "integer",
- "status": "available",
- "required": true,
- "array": false,
- "min": -9223372036854776000,
- "max": 9223372036854776000,
- "default": null
- },
- {
- "key": "out",
- "type": "boolean",
- "status": "available",
- "required": false,
- "array": false,
- "default": false
- }
- ],
- "indexes": [
- {
- "key": "matchID",
- "type": "key",
- "status": "available",
- "attributes": [
- "matchID"
- ],
- "orders": [
- "ASC"
- ]
- }
- ]
-```
-
-The database could be even tweaked better, with precise min max values, note that the attributes have to be defined first, unlike firestore or [HarperDB](https://networkandcode.hashnode.dev/online-shop-with-nextjs-and-harperdb), where they could be created on the fly. But this approach is ok, I think we have more control, and is secure.
-
-Ok give it a [try](https://cricscore.vercel.app/), and let me know if it's ok or needs improvements to the logic or UI, and feel free to modify the [code](https://github.com/networkandcode/cricscore) and make it better.
-
-
-Thank you !!! :slightly_smiling_face:
\ No newline at end of file
diff --git a/_posts/2022-05-31-host-alexa-skill-on-aws-with-serverless.md b/_posts/2022-05-31-host-alexa-skill-on-aws-with-serverless.md
deleted file mode 100644
index 795a56a..0000000
--- a/_posts/2022-05-31-host-alexa-skill-on-aws-with-serverless.md
+++ /dev/null
@@ -1,304 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/setup-an-alexa-skill-with-serverless-1gck
-categories: alexa, aws, node, serverless
-date: 2022-05-31
-tags: alexa, aws, node, serverless
-title: Host Alexa skill on AWS with Serverless
----
-
-*This post first appeared on [dev.to](https://dev.to/aws-builders/setup-an-alexa-skill-with-serverless-1gck)*
-
-Hey all :wave: we are gonna see how to setup an Alexa skill for a trivia related to space events, using the [Serverless](https://serverless.com) framework. It's assumed you are ok with some Alexa fundamentals and certain concepts of AWS such as IAM, Lambda etc. Let's get started.
-
-You may go through this nice [tutorial](https://developer.amazon.com/en-US/docs/alexa/workshops/build-an-engaging-skill/get-started/index.html) if you want to get started with Alexa by building an Alexa hosted skill. What we have done here in this blog is an AWS hosted skill.
-
-## Alexa
-Login to the Alexa skill kit [console](https://developer.amazon.com/alexa/console/ask) with your developer account.
-
-You can then create a skill and give it some invocation name.
-
-
-### Intents
-I've addedd 2 built-in intents and 2 custom intents, than what gets added by default.
-
-
-The GetAnswerIntent has the following utterances.
-```
-it's {date}
-I guess it's on {date}
-I think the date is {date}
-{date}
-I'm guessing it's {date}
-```
-You may add more or modify as you wish. The only slot here is `date` and it is of built-in type AMAZON.DATE.
-
-Likewise the AskQuestionIntent has the following utterances.
-```
-could you ask me the question please
-can you go back to the question
-can you ask me the question
-question please
-go back to the question
-next question
-Ask question
-```
-Ensure to save and build the model once all the intents are added.
-
-## IAM
-Log in to [AWS](https://console.aws.amazon.com) as a root user, and create a user group
-
-
-The user group should be attached by the AWS managed permission policy [AWSCloud9User](https://console.aws.amazon.com/iam/home#/policies/arn:aws:iam::aws:policy/AWSCloud9User) that allows creating Cloud9 environments. This is not required though, if you are not using Cloud9.
-
-I've then created another custom [policy](https://us-east-1.console.aws.amazon.com/iamv2/home#/policies) with the following [JSON](https://www.serverless.com/framework/docs/guides/providers#using-a-custom-iam-role-and-policy), with the name `ServerlessPolicy` that gives enough permissions for the serverless SDK to deploy using cloud formation stack, and access to other relevant services as listed.
-```
-{
- "Version": "2012-10-17",
- "Statement": [
- {
- "Effect": "Allow",
- "Action": [
- "apigateway:DELETE",
- "apigateway:GET",
- "apigateway:PATCH",
- "apigateway:POST",
- "apigateway:PUT",
- "cloudformation:CreateChangeSet",
- "cloudformation:CreateStack",
- "cloudformation:DeleteChangeSet",
- "cloudformation:DeleteStack",
- "cloudformation:DescribeChangeSet",
- "cloudformation:DescribeStackEvents",
- "cloudformation:DescribeStackResource",
- "cloudformation:DescribeStacks",
- "cloudformation:ExecuteChangeSet",
- "cloudformation:ListStackResources",
- "cloudformation:UpdateStack",
- "cloudformation:ValidateTemplate",
- "events:DescribeRule",
- "events:PutRule",
- "events:PutTargets",
- "events:RemoveTargets",
- "iam:CreateRole",
- "iam:DeleteRole",
- "iam:DeleteRolePolicy",
- "iam:GetRole",
- "iam:PassRole",
- "iam:PutRolePolicy",
- "iam:UpdateAssumeRolePolicy",
- "lambda:AddPermission",
- "lambda:CreateFunction",
- "lambda:DeleteFunction",
- "lambda:GetAccountSettings",
- "lambda:GetAlias",
- "lambda:GetEventSourceMapping",
- "lambda:GetFunction",
- "lambda:GetFunctionConfiguration",
- "lambda:GetLayerVersion",
- "lambda:GetLayerVersionPolicy",
- "lambda:GetPolicy",
- "lambda:InvokeFunction",
- "lambda:ListAliases",
- "lambda:ListEventSourceMappings",
- "lambda:ListFunctions",
- "lambda:ListLayerVersions",
- "lambda:ListLayers",
- "lambda:ListTags",
- "lambda:ListVersionsByFunction",
- "lambda:PublishVersion",
- "lambda:RemovePermission",
- "lambda:UpdateFunctionCode",
- "lambda:UpdateFunctionConfiguration",
- "logs:CreateLogGroup",
- "logs:DeleteLogGroup",
- "logs:DeleteSubscriptionFilter",
- "logs:DescribeLogGroups",
- "logs:FilterLogEvents",
- "logs:GetLogEvents",
- "logs:PutSubscriptionFilter",
- "s3:CreateBucket",
- "s3:DeleteBucket",
- "s3:DeleteBucketPolicy",
- "s3:DeleteBucketWebsite",
- "s3:DeleteObject",
- "s3:DeleteObjectVersion",
- "s3:GetBucketLocation",
- "s3:GetObject*",
- "s3:ListBucket",
- "s3:PutBucketPolicy",
- "s3:PutEncryptionConfiguration",
- "s3:PutObject",
- "sts:GetCallerIdentity"
- ],
- "Resource": "*"
- }
- ]
-}
-```
-
-So the group is attached to both policies.
-
-
-Once the group is created, add a new user to the group.
-
-
-And don't forget to copy the credentials
-
-## Instance
-You may now login to AWS as the new user. Next we need a machine from which we can clone the serverless code and deploy it, for this purpose I would be launching a [cloud 9](https://dev.to/aws-builders/run-svelte-app-on-aws-cloud9-4j5b) instance, so that I can also use it as an online editor. You can use any Linux machine though.
-
-I'd be creating a Cloud9 environment in the Mumbai region, ap-south-1.
-
-I've choosen t3.small as the instance type, we may go with t2.micro if we want a free tier eligible instance.
-
-Once it's created you shoud see the console.
-
-
-## AWS CLI
-AWS CLI comes pre-installed in Cloud9 and it would also have the credentials file
-```
-serverless-user-1:~/environment $ ls ~/.aws/
-credentials
-```
-We can setup the config though.
-```
-serverless-user-1:~/environment $ cat ~/.aws/config
-[default]
-region=ap-south-1
-```
-
-## Clone
-Let's clone the alexa skill repo [space-events-trivia](https://github.com/networkandcode/space-events-trivia) from github.
-```
-serverless-user-1:~/environment $ git clone https://github.com/networkandcode/space-events-trivia.git
-```
-The code we cloned is a set of nodejs functions and is compatible with the serverless sdk.
-```
-serverless-user-1:~/environment $ cd space-events-trivia/
-serverless-user-1:~/environment/space-events-trivia (main) $ ls
-AplRender.js GetAnswerIntentHandler.js interceptors.js README.md StartTriviaHandler.js
-CancelAndStopIntentHandler.js HelpIntentHandler.js LaunchRequestHandler.js RepeatIntentHandler.js triviaFunctions.js
-documents index.js package.json serverless.yml
-ErrorHandler.js IntentReflectorHandler.js package-lock.json SessionEndedRequestHandler.js
-```
-
-The file [documents/questions.json](https://github.com/networkandcode/space-events-trivia/blob/main/documents/questions.json) contains the list of questions for the trivia, you may modify it as required.
-
-## Packages
-The package.json file should tell us the packages we would be using in our code.
-
-
-Let's install those.
-```
-serverless-user-1:~/environment/space-events-trivia (main) $ npm i
-npm WARN deprecated querystring@0.2.0: The querystring API is considered Legacy. new code should use the URLSearchParams API instead.
-npm WARN deprecated uuid@3.3.2: Please upgrade to version 7 or higher. Older versions may use Math.random() in certain circumstances, which is known to be problematic. See https://v8.dev/blog/math-random for details.
-
-added 18 packages, and audited 19 packages in 2s
-
-1 package is looking for funding
- run `npm fund` for details
-
-found 0 vulnerabilities
-```
-
-## Serverless
-We can install the serverless SDK and later deploy the code using it to AWS lambda. We are actually talking about two things here, one the serverless framework/SDK, and two the serverless technology offering from AWS which is Lambda. Instead of writing the functions directly on Lambda we are going to use the serverless SDK with it's constructs to acheieve the purpose in a controlled way.
-```
-serverless-user-1:~/environment $ npm i serverless -g
-```
-It should now be installed.
-```
-serverless-user-1:~/environment $ serverless -v
-Framework Core: 3.18.2
-Plugin: 6.2.2
-SDK: 4.3.2
-```
-There is a serverless.yml file in our repo, that has our serverless [configuration](https://www.serverless.com/framework/docs/providers/aws/guide/serverless.yml), you may modify it according to your setup.
-```
-serverless-user-1:~/environment/space-events-trivia (main) $ cat serverless.yml
-app: space-events-trivia
-service: space-events-trivia
-
-frameworkVersion: '3'
-
-provider:
- environment:
- DYNAMODB_REGION: ${aws:region}
- DYNAMODB_TABLE: ${self:service}-users-${sls:stage}
- iam:
- role:
- statements:
- - Effect: 'Allow'
- Action:
- - 'dynamodb:CreateTable'
- - 'dynamodb:PutItem'
- - 'dynamodb:Get*'
- - 'dynamodb:Scan*'
- - 'dynamodb:UpdateItem'
- - 'dynamodb:DeleteItem'
- Resource: arn:aws:dynamodb:${aws:region}:${aws:accountId}:table/${self:service}-users-${sls:stage}
- name: aws
- region: ap-south-1
- runtime: nodejs16.x
- stage: dev
-
-functions:
- handler:
- handler: index.handler
- events:
- - alexaSkill: amzn1.ask.skill.${param:alexaSkillId}
-```
-The org is missing in the configuration, we can specify that while deploying. We have also given permissions for the lambda function on DynamoDB incuding the create table permission, so that the lambda function can create the table if it doesn't exist.
-
-## Deploy
-Let's deploy the function, for which first login to serverless.
-```
-$ serverless login
-? Which would you like to log into? Serverless Framework Dashboard
-Logging into the Serverless Dashboard via the browser
-If your browser does not open automatically, please open this URL:
-https://app.serverless.com?client=cli&transactionId=
-```
-Once logged in via the browser, you should see this screen.
-
-
-That's it, time to deploy.
-```
-$ serverless deploy --org --param="alexaSkillId="
-```
-You have to mention your org and alexaSkillId before running the command above. The org name is something you created in serverless while signing up the account, and you can get the skill ID from the alexa developer console, so that it gets mapped with `alexaSkill: ${param:alexaSkillId}` in [serverless.yml](https://github.com/networkandcode/space-events-trivia/blob/main/serverless.yml)
-
-
-The function should get successfully deployed by now. The serverless dashboard should show a successful status with green color.
-
-
-## Endpoints
-You can get the lambda endpoint straight from the Serverless CLI.
-```
-$ serverless info --param="alexaSkillId=" --verbose
-service: space-events-trivia
-stage: dev
-region: ap-south-1
-stack: space-events-trivia-dev
-functions:
- handler: space-events-trivia-dev-handler
-
-Stack Outputs:
- HandlerLambdaFunctionQualifiedArn:
- EnterpriseLogAccessIamRole:
- ServerlessDeploymentBucketName:
-
-Want to ditch CloudWatch? Try our new console: run "serverless --console"
-```
-You can copy the lambda ARN from the output above except the suffix which is a number, and set it as an endpoint in the Skill settings in Alexa developer console. It should have the format `arn:aws:lambda:::function:`. I've just added it for the default region.
-
-
-The skill could now be tested from the test window.
-
-
-You can also test :test_tube: the skill from an Alexa device that's using the same account as your developer account.
-
-Alright then, that's it for now, thanks for reading !!!
-
-Image credit: [unsplash](https://source.unsplash.com/featured/?galaxy)
\ No newline at end of file
diff --git a/_posts/2022-06-11-install-appwrite-on-linode.md b/_posts/2022-06-11-install-appwrite-on-linode.md
deleted file mode 100644
index 586ff3a..0000000
--- a/_posts/2022-06-11-install-appwrite-on-linode.md
+++ /dev/null
@@ -1,180 +0,0 @@
----
-canonical_url: https://networkandcode.hashnode.dev/install-appwrite-on-linode
-categories: appwrite, docker, linode, linux
-date: 2022-06-11
-tags: appwrite, docker, linode, linux
-title: Install Appwrite on Linode
----
-
-*This post first appeared on [hashnode.dev](https://networkandcode.hashnode.dev/install-appwrite-on-linode)*
-
-## Introduction
-[Appwrite](https://appwrite.io/) is a backend server that can be leveraged for integrating services such as authentication, storage, database etc. to our frontend application. It can be launched with docker, as it's a set of docker containers offering specific services. Here, we are going to install it on top of an Ubuntu machine on [Linode](https://www.linode.com/).
-
-## SSH keys
-This step is not required if you would be accessing the cloud instance via password. However SSH keys are a secure way to access instances than passwords.
-
-You can follow this on any Unix / Linux based machine, it works on [Git Bash](https://git-scm.com/download/win) too on Windows.
-
-Generate SSH keys on your local machine, from which you would be accessing the Linode instance.
-```
-$ ssh-keygen
-```
-You can copy the public key, which is by default at the following location.
-```
-$ cat ~/.ssh/id_rsa.pub
-```
-
-## Instance
-Appwrite needs atleast 1 CPU and 2 GB RAM as mentioned on their [docs](https://appwrite.io/docs/installation#systemRequirements). So, I have created a Linode instance with the following spec.
-
-![Create linode](https://cdn.hashnode.com/res/hashnode/image/upload/v1654915190109/lAaB7W6WH.png align="left")
-```
-OS: Ubuntu 22.04 LTS
-Hostname: appwrite
-2 CPU Cores, 80 GB Storage, 4 GB RAM
-
-Plan:
-Linode 4 GB
-
-Region:
-Mumbai, IN
-```
-You can setup password for the root user and optionally add the SSH keys(more secure) copied from the previous step, as per your convenience.
-
-## Change hostname
-The default hostname is localhost, so we can better change it to appwrite.
-```
-root@localhost:~# hostname appwrite
-```
-The new hostname would be effective from the next login.
-
-## Install docker engine
-We can now install the [docker engine](https://docs.docker.com/engine/install/ubuntu/)
-```
-apt-get update -y
-
-apt-get install \
- ca-certificates \
- curl \
- gnupg \
- lsb-release -y
-
-mkdir -p /etc/apt/keyrings
-
-curl -fsSL https://download.docker.com/linux/ubuntu/gpg | gpg --dearmor -o /etc/apt/keyrings/docker.gpg
-
-echo \
- "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
- $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
-
-apt-get update -y
-
-apt-get install docker-ce docker-ce-cli containerd.io docker-compose-plugin -y
-```
-
-We shoud now have docker and docker compose
-```
-root@appwrite:~# docker -v
-Docker version 20.10.17, build 100c701
-
-root@appwrite:~# docker compose version
-Docker Compose version v2.6.0
-```
-
-## Add user
-When we created the instance it would only have the root user. Login to the instance via the LISH console or any SSH client as root, and add a new user.
-```
-root@localhost:~# adduser appwrite
-Adding user `appwrite' ...
-Adding new group `appwrite' (1000) ...
-Adding new user `appwrite' (1000) with group `appwrite' ...
-Creating home directory `/home/appwrite' ...
-Copying files from `/etc/skel' ...
-New password:
-Retype new password:
-passwd: password updated successfully
-Changing the user information for appwrite
-Enter the new value, or press ENTER for the default
- Full Name []:
- Room Number []:
- Work Phone []:
- Home Phone []:
- Other []:
-Is the information correct? [Y/n] Y
-```
-
-The appwrite user should have been created under the appwrite group.
-```
-root@appwrite:~# id appwrite
-uid=1000(appwrite) gid=1000(appwrite) groups=1000(appwrite)
-```
-
-## Add to group
-The docker group would have read write permissions on the docker.sock file.
-```
-$ ls /var/run/docker.sock -l
-srw-rw---- 1 root docker 0 Jun 11 03:06 /var/run/docker.sock
-```
-Hence, add the appwrite user to the docker group, so that we can run docker commands as the appwrite user.
-```
-root@appwrite:~# usermod -aG docker appwrite
-root@appwrite:~# id appwrite
-uid=1000(appwrite) gid=1000(appwrite) groups=1000(appwrite),999(docker)
-```
-
-## Clone
-Login as the appwrite user with the password for the first time, and then optionally you can copy the SSH public key from your local machine to the location `.ssh/authorized_keys` for futher logging in via SSH keys.
-
-Clone the [appwrite](https://github.com/appwrite/appwrite.git) repo
-```
-appwrite@appwrite:~$ git clone https://github.com/appwrite/appwrite.git
-```
-
-## Up
-Change directory and run docker compose.
-```
-cd appwrite
-docker compose up
-```
-This is not the quick start installation mode, we are doing a full installation, so that we can update Appwrite environment configuration when required. There would be a build status at the top of the screen like below.
-```
-[+] Building 355.8s (85/609)
-```
-Note that this would take a while, and we have to wait until all the images are built.
-
-## Containers
-You can open a different SSH session and see if the containers are running.
-```
-appwrite@appwrite:~$ docker container ls | awk '{print $2}'
-ID
-appwrite_appwrite-worker-functions
-traefik:2.7
-appwrite_appwrite-executor
-appwrite_appwrite-worker-database
-appwrite_appwrite
-appwrite_appwrite-maintenance
-appwrite_appwrite-worker-mails
-appwrite_appwrite-worker-deletes
-appwrite_appwrite-worker-audits
-appwrite_appwrite-worker-builds
-appwrite_appwrite-worker-certificates
-appwrite_appwrite-realtime
-appwrite_appwrite-worker-webhooks
-appwrite_appwrite-schedule
-appwrite/requestcatcher:1.0.0
-redis:6.2-alpine
-adminer
-mariadb:10.7
-appwrite/telegraf:1.4.0
-appwrite/influxdb:1.5.0
-appwrite/mailcatcher:1.0.0
-```
-So Appwrite is following a [microservices](https://dev.to/appwrite/30daysofappwrite-appwrite-s-building-blocks-1936) architectural pattern where multiple microservices are running separately as containers to collectlively form the Appwrite stack/service.
-
-## Appwrite
-We can now try to login to the Appwrite UI on the browser with the same IP we used to SSH into the instance. It should provide the signup page where we can create the account.
-![Appwrite signup](https://cdn.hashnode.com/res/hashnode/image/upload/v1654920901564/m3rgsuhD8.png align="left")
-
-So we have finally installed and launched Appwrite successfully on Linode. Thank you for reading :)
-
diff --git a/_posts/2022-06-13-install-harperdb-on-linode.md b/_posts/2022-06-13-install-harperdb-on-linode.md
deleted file mode 100644
index 68170ae..0000000
--- a/_posts/2022-06-13-install-harperdb-on-linode.md
+++ /dev/null
@@ -1,106 +0,0 @@
----
-canonical_url: https://networkandcode.hashnode.dev/install-harperdb-on-linode
-categories: docker, harperdb, linode, linux
-date: 2022-06-13
-tags: docker, harperdb, linode, linux
-title: Install HarperDB on Linode
----
-
-*This post first appeared on [hashnode.dev](https://networkandcode.hashnode.dev/install-harperdb-on-linode)*
-
-Hi... let's see how to install HarperDB with Docker on a Linux machine running on Linode. HarperDB is a NoSQL DB that also supports SQL style queries. It can be installed in various ways and we shall be installing it the Docker way, in this post.
-
-## Instance
-I launched an instance on Linode with the following spec.
-
-```
-Name: harperdb
-
-
-Summary:
-1 CPU Core, 50 GB Storage, 2 GB RAM
-
-Plan:
-Linode 2 GB
-
-Region:
-Mumbai, IN
-```
-
-Please refer to this [post](https://networkandcode.hashnode.dev/install-appwrite-on-linode) for instructions on SSH keys and installation of Docker.
-
-## Hostname
-Then I logged in to the instance on it's public IP via SSH, and changed the hostname.
-```
-root@localhost:~# hostname harperdb
-```
-
-## Add user
-I have added a user harperdb.
-```
-root@harperdb:~# adduser harperdb
-Adding user `harperdb' ...
-Adding new group `harperdb' (1000) ...
-Adding new user `harperdb' (1000) with group `harperdb' ...
-Creating home directory `/home/harperdb' ...
-Copying files from `/etc/skel' ...
-New password:
-Retype new password:
-passwd: password updated successfully
-Changing the user information for harperdb
-Enter the new value, or press ENTER for the default
- Full Name []:
- Room Number []:
- Work Phone []:
- Home Phone []:
- Other []:
-Is the information correct? [Y/n] Y
-```
-
-This would also generate a group with the same name.
-```
-root@harperdb:~# id harperdb
-uid=1000(harperdb) gid=1000(harperdb) groups=1000(harperdb)
-```
-
-## Add to group
-Let's now add this to the docker group.
-```
-root@harperdb:~# usermod -aG docker harperdb
-```
-
-## Run
-Login as the harperdb user and now run the docker command to install HarperDB. Different command line arguments are provided [here](https://hub.docker.com/r/harperdb/harperdb).
-```
-harperdb@harperdb:~$ docker run -d -e HDB_ADMIN_USERNAME=HDB_ADMIN -e HDB_ADMIN_PASSWORD=password -p 9925:9925 harperdb/harperdb
-```
-The container should be running.
-```
-harperdb@harperdb:~$ docker container ls
-CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
-eb3364e372ed harperdb/harperdb "tini -- harperdb" 8 minutes ago Up 8 minutes 0.0.0.0:9925->9925/tcp, :::9925->9925/tcp modest_raman
-```
-
-## API
-Let's try a rest [API](https://api.harperdb.io/) call via CURL and see if it works.
-```
-harperdb@harperdb:~$ curl -u HDB_ADMIN -X POST 'http://localhost:9925' --header 'Content-Type: application/json' --data-raw '{
- "operation": "create_schema",
- "schema": "dev"
-}'
-Enter host password for user 'HDB_ADMIN':
-{"message":"schema 'dev' successfully created"}
-```
-
-## Remote
-Let's try to delete this schema, this time from a remote machine, where we need to replace localhost with the public IP of the HarperDB instance.
-```
-$ curl -u HDB_ADMIN -X POST 'http://:9925' --header 'Content-Type: application/json' --data-raw '{
- "operation": "drop_schema",
- "schema": "dev"
-}'
-Enter host password for user 'HDB_ADMIN':
-{"message":"successfully deleted schema 'dev'"}
-```
-
-In a similar manner we could send these rest API calls to HarperDB from client or server SDKs such as fetch, axios etc. instead of CURL and integrate it with our application. Thank you for reading :)
\ No newline at end of file
diff --git a/_posts/2022-06-26-school-admin-app-with-nextjs-on-linode.md b/_posts/2022-06-26-school-admin-app-with-nextjs-on-linode.md
deleted file mode 100644
index 7686dcd..0000000
--- a/_posts/2022-06-26-school-admin-app-with-nextjs-on-linode.md
+++ /dev/null
@@ -1,247 +0,0 @@
----
-date: 2022-06-26
-canonical_url: https://networkandcode.hashnode.dev/school-admin-app-with-nextjs-on-linode
-categories: linode, nextjs, tailwindcss, typescript
-tags: linode, nextjs, tailwindcss, typescript
-title: School admin app with NextJS on Linode
----
-
-*This post first appeared on [hashnode.dev](https://networkandcode.hashnode.dev/school-admin-app-with-nextjs-on-linode)*
-
-## Introduction
-Hi 👋, in this post we shall see how to deploy a school management web app with some fundamental functionalities, on Linode, and then see some screenshots from the running app. You may click [here](https://github.com/networkandcode/sms) to check the GitHub repo.
-
-## Instance
-Let's launch an instance on Linode. Go to this [link](https://cloud.linode.com/linodes/create) and create an instance with the following spec.
-```
-Ubuntu
-2 CPU Cores, 80 GB Storage 4 GB RAM
-
-Plan: Linode 4 GB
-Region: Mumbai, IN
-```
-
-## Hostname
-SSH into the instance as root user with either password or SSH key as relevant, and change the hostname which should be effective from next login.
-```
-root@localhost:~# hostname sms
-```
-
-## Node
-Let's install [nodejs](https://github.com/nodejs/help/wiki/Installation) on our system.
-```
-root@sms:~# wget https://nodejs.org/dist/v18.4.0/node-v18.4.0-linux-x64.tar.xz
-root@sms# tar -xvJf node-v18.4.0-linux-x64.tar.xz -C /usr/local/lib/nodejs
-root@sms# rm node-v18.4.0-linux-x64.tar.xz
-```
-
-## Add a user
-Add a new user, so that we can do rest of the operations as that user
-```
-# adduser sms
-Adding user `sms' ...
-Adding new group `sms' (1000) ...
-Adding new user `sms' (1000) with group `sms' ...
-Creating home directory `/home/sms' ...
-Copying files from `/etc/skel' ...
-New password:
-Retype new password:
-passwd: password updated successfully
-Changing the user information for sms
-Enter the new value, or press ENTER for the default
- Full Name []:
- Room Number []:
- Work Phone []:
- Home Phone []:
- Other []:
-Is the information correct? [Y/n] Y
-```
-Once the user is added, you may exit the shell and relogin as new user.
-
-## Sudo
-We can add the new user to the sudo group, to run commands that may require sudo privileges.
-```
-root@sms:~# usermod -aG sudo sms
-```
-We can validate using the id command.
-```
-root@sms:~# id sms
-uid=1000(sms) gid=1000(sms) groups=1000(sms),27(sudo)
-```
-So the user sms belongs to two groups sms and sudo.
-
-## Path
-Update path to access node and npm.
-```
-sms@sms:~$ export PATH=/usr/local/lib/nodejs/node-v18.4.0-linux-x64/bin:$PATH
-sms@sms:~ . ~/.profile
-```
-
-Validate.
-```
-sms@sms:~$ node -v
-v18.4.0
-sms@sms:~$ npm -v
-8.12.1
-```
-
-## Clone
-Clone the code from github.
-```
-sms@sms:~$ git clone https://github.com/networkandcode/sms.git
-```
-
-## Backend
-I have used [Appwrite](https://networkandcode.hashnode.dev/install-appwrite-on-linode) for authentication, and [HarperDB](https://networkandcode.hashnode.dev/install-harperdb-on-linode) as database. You may click on the respective hyperlinks for instructions to set up those on Linode.
-
-## Appwrite
-Update the platform settings on Appwrite, to allow requests from the client, you can either use the IP or domain. In this case I can use the public IP of the instance we have launched in this post.
-![Platform settings](https://cdn.hashnode.com/res/hashnode/image/upload/v1656177416027/ov-xFqXoq.png align="left")
-
-## Variables
-Change directory and set the environment variables.
-```
-sms@sms:~$ cd sms
-sms@sms:~/sms$ cat .env
-APPWRITE_API_KEY=
-HARPERDB_URL=
-HARPERDB_USERNAME=
-HARPERDB_PASSWORD=
-NEXT_PUBLIC_APPWRITE_SUPER_ADMINS=
-NEXT_PUBLIC_APPWRITE_EMAIL_VERIFICATION_URL=
-NEXT_PUBLIC_APPWRITE_ENDPOINT=
-NEXT_PUBLIC_APPWRITE_NEW_MEMBER_URL=
-NEXT_PUBLIC_APPWRITE_PROJECT_ID=
-```
-Please replace with actual values.
-
-## Install
-We can install all the modules defined in package.json using npm.
-```
-sms@sms:~/sms$ npm i
-npm WARN deprecated querystring@0.2.0: The querystring API is considered Legacy. new code should use the URLSearchParams API instead.
-
-added 300 packages, and audited 301 packages in 7s
-
-79 packages are looking for funding
- run `npm fund` for details
-
-found 0 vulnerabilities
-npm notice
-npm notice New minor version of npm available! 8.12.1 -> 8.13.1
-npm notice Changelog: https://github.com/npm/cli/releases/tag/v8.13.1
-npm notice Run npm install -g npm@8.13.1 to update!
-npm notice
-```
-
-So there are no vulnerabilties as per the output above. We can also try npm audit.
-```
-sms@sms:~/sms$ npm audit
-found 0 vulnerabilities
-```
-
-## Dev
-First, let's run it in development mode.
-```
-sms@sms:~/sms$ npm run dev
-
-> sms@0.1.0 dev
-> next dev
-
-ready - started server on 0.0.0.0:3000, url: http://localhost:3000
-info - Loaded env from /home/sms/sms/.env
-wait - compiling...
-event - compiled client and server successfully in 2.9s (212 modules)
-Attention: Next.js now collects completely anonymous telemetry regarding usage.
-This information is used to shape Next.js' roadmap and prioritize features.
-You can learn more, including how to opt-out if you'd not like to participate in this anonymous program, by visiting the following URL:
-https://nextjs.org/telemetry
-```
-
-The website should now be available on port 3000, we can check it on the browser with the public IP of the instance.
-
-Once logged in, you should see a screen like below.
-![Home screen](https://cdn.hashnode.com/res/hashnode/image/upload/v1656225817326/rre27Heks.png align="left")
-
-For the first time, when logged in as super admin, the generate tables link at the bottom can be clicked, to generate tables in HarperDB.
-
-Press Ctrl ^ C to stop the running application.
-
-## Build
-Now we can make a build and run it.
-
-```
-sms@sms:~/sms$ npm run build
-sms@sms:~/sms$ npm run start
-
-> sms@0.1.0 start
-> next start
-
-ready - started server on 0.0.0.0:3000, url: http://localhost:3000
-info - Loaded env from /home/sms/sms/.env
-```
-The app can be accessed again on the same URL on port 3000.
-
-## Screenshots
-Here are some screenshots from the app.
-
-### Authentication
-![Signup](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222329569/f7r2rGfkg.png align="left")
-
-![Login](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222363925/CVKxwEf2o.png align="left")
-
-### Screens visible for Admins
-![Classes](https://cdn.hashnode.com/res/hashnode/image/upload/v1656221269852/KjxH2ZWiK.png align="left")
-
-![Class](https://cdn.hashnode.com/res/hashnode/image/upload/v1656221214177/acZeAGZvp.png align="left")
-
-![Class students](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222821792/fBe7mD_QS.png align="left")
-
-![Class attendance](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222923838/2A92fTPwf.png align="left")
-
-![Class timetable](https://cdn.hashnode.com/res/hashnode/image/upload/v1656221701407/Pz5O_6Bl4.png align="left")
-
-![Exam score](https://cdn.hashnode.com/res/hashnode/image/upload/v1656223094365/HMKW2ztH-.png align="left")
-
-![Teams](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222096881/Qri87V2Cd.png align="left")
-
-![Team members](https://cdn.hashnode.com/res/hashnode/image/upload/v1656223895315/XxBUZebA6.png align="left")
-
-### Screens visible for parents
-![Home screen for parent](https://cdn.hashnode.com/res/hashnode/image/upload/v1656222584587/IYMKnehkS.png align="left")
-
-![Profile](https://cdn.hashnode.com/res/hashnode/image/upload/v1656224814592/EKzA3-t85.png align="left")
-
-![Children](https://cdn.hashnode.com/res/hashnode/image/upload/v1656224995274/3wgtIie1N.png align="left")
-
-Clicking on the timetable would redirect to the screen shown in the admin section earlier.
-
-## Security
-We are now using 3 instances on Linode.
-
-![instances](https://cdn.hashnode.com/res/hashnode/image/upload/v1656226856640/fV8PPQsqk.png align="left")
-
-We have been using port 3000 for the NextJS app, 80 for Appwrite and 9925 for HarperDB. So let's create firewalls on Linode and restrict access.
-![Create firewall](https://cdn.hashnode.com/res/hashnode/image/upload/v1656226828582/qzNYbAltw.png align="left")
-
-I would be creating 3 firewall rules.
-
-For Appwrite
-![Appwrite firewall rule](https://cdn.hashnode.com/res/hashnode/image/upload/v1656228109564/h5V55qMZO.png align="left")
-
-For HarperDB
-![HarperDB firewall rule](https://cdn.hashnode.com/res/hashnode/image/upload/v1656228055129/OAPCcUfrT.png align="left")
-
-For the NextJS app
-![sms firewall rule](https://cdn.hashnode.com/res/hashnode/image/upload/v1656228005578/vFs8V-IXY.png align="left")
-
-I have mentioned the source as all though, which could be changed to allow only specific IPs.
-
-## Endnote
-The app has some fundamental uses and the logic can be expanded further to include various features such as holiday management, file sharing, etc..
-
-The app can also be deployed as a container on a VM or on linode’s kubernetes engine.
-
-Thanks for reading !!!
-
-Image credit: [unsplash](https://unsplash.com)
\ No newline at end of file
diff --git a/_posts/2022-06-30-trying-my-hands-on-neo4j-with-some-iot-data.md b/_posts/2022-06-30-trying-my-hands-on-neo4j-with-some-iot-data.md
deleted file mode 100644
index 5cf04e1..0000000
--- a/_posts/2022-06-30-trying-my-hands-on-neo4j-with-some-iot-data.md
+++ /dev/null
@@ -1,232 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/trying-my-hands-on-neo4j-with-some-iot-data-28g7
-categories: cypher, graphdb, iot, neo4j
-date: 2022-06-30
-tags: cypher, graphdb, iot, neo4j
-title: Trying my hands on Neo4j with some IoT data
----
-
-*This post first appeared on [dev.to](https://dev.to/networkandcode/trying-my-hands-on-neo4j-with-some-iot-data-28g7)*
-
-## Introduction
-
-Hello :wave:, time for some GraphDB...
-
-Neo4j is a Graph DB written in Java, the j in 4j at the end stands for Java :). I like the variety of self placed [courses](https://graphacademy.neo4j.com/courses/) and the certifications offered by them, all for free, wow.
-
-[Cypher](https://neo4j.com/docs/cypher-manual/current/) is the declarative query language we would be using to interact with the Neo4j database. We can run Cypher queries directly on the Neo4j [browser](https://neo4j.com/docs/browser-manual/current/) and can use one of the [drivers](https://neo4j.com/developer/language-guides/) to make calls to the database from our application.
-
-In this post we shall focus on running certain Cypher queries from the browser, and see some key GraphDB concepts along the way. Let's get started...
-
-## Sandbox
-Head over to this [link](https://neo4j.com/sandbox/), signup/signin, and create a sandbox > create a project, choose Blank Project.
-
-We have choosen blank project cause we can also load our own data instead of working with some pre-built data.
-
-Click on the Open button to open the project with the Neo4j browser.
-
-## Delete all
-I have already added some data to the blank project before, so I'm going to delete all the nodes and their relationships first, you may not need this yet, however you may come back to this step later on when needed.
-```
-MATCH (n) DETACH DELETE n
-
-Deleted 42 nodes, deleted 1 relationship, completed after 9 ms.
-```
-In the command above, the parentheses pair represents a node, and n is a variable that represents a node, so we are matching all nodes (as there are no conditions) and subsequently deleting those including their relationships using [DETACH DELETE](https://neo4j.com/docs/cypher-manual/current/clauses/delete/).
-
-## Node
-A node is a discrete entity, for our IoT use case, it could be an Edge device, power source etc. Refer to this github [repo](https://github.com/muntasirjoarder/NeoThings) for a sample IoT data modeling.
-
-In Cypher a Node is enclosed in parantheses, for ex. `(e)` refers to a node represented by a variable e.
-
-### Labels
-And then comes label(s) which are denoted by colon `:`, that we could use to tag a node, for instance if it's an edge device we could label it `:EdgeDevice`. So now our node becomes `(e:EdgeDevice)`. Note that labels are usually written in PascalCase.
-
-We could add multiple labels to a node, so let's also label our edge device as a thing, making our node look like `(e:EdgeDevice:Thing)`,
-
-### Properties
-Properties are key value pairs defining the actual object. Let's say we want to give some names to our edge devices, like Edge Device 1, 2 etc. and another property to identify the floor in which they are installed, like GF, 1F, 2F etc. The properties for our first device would then be like:
-```
-{
- name: 'Edge Device 1',
- floor: 'GF'
-}
-```
-
-### Create nodes
-Our node should finally look like `(e:EdgeDevice:Thing { name: 'Edge Device 1', floor: 'GF' } )`. Note that the variable name is only optional and is required only if we reuse the variable in our query. Let's create the node on the browser.
-```
-CREATE (e:EdgeDevice:Thing { name: 'Edge Device 1', floor: 'GF' } ) RETURN e
-```
-You should now see a graph output like 
-
-And the respective table should be:
-```
-{
- "identity": 41,
- "labels": [
- "EdgeDevice",
- "Thing"
- ],
- "properties": {
-"name": "Edge Device 1",
-"floor": "GF"
- }
-}
-```
-Note that the identity was auto generated.
-
-### Constraints
-What if we create another node with the same properties.
-```
-CREATE (e:EdgeDevice:Thing { name: 'Edge Device 1', floor: 'GF' } ) RETURN e
-```
-
-It would get created, and we would now have two similar nodes.
-```
-MATCH (e:EdgeDevice:Thing { name: 'Edge Device 1'} ) RETURN COUNT(e)
-
-2
-```
-
-let's say we want the name of the device to be unique, in such case, we could create a [constraint](https://neo4j.com/docs/cypher-manual/current/constraints/examples/) to set the name as unique.
-
-But before doing so, we should get rid of the duplicates, as otherwise it would throw an error. Let's first get the IDs of the nodes.
-```
-MATCH (e:EdgeDevice:Thing) RETURN(ID(e))
-
-0
-41
-```
-So there are two nodes with IDs 0 and 41, we can delete one, let's go with 41. Note the numbers may vary in your case.
-```
-MATCH (e) WHERE ID(e) = 41 DELETE e
-
-Deleted 1 node, completed after 8 ms.
-```
-
-Let's now create the constraint.
-```
-CREATE CONSTRAINT unqiue_edge_device_name FOR (e:EdgeDevice) REQUIRE e.name IS UNIQUE
-
-Added 1 constraint, completed after 70 ms.
-```
-
-Now, if we try to create another device with the same name, it should fail.
-```
-CREATE (e:EdgeDevice:Thing { name: 'Edge Device 1', floor: 'GF' } ) RETURN e
-
-Neo.ClientError.Schema.ConstraintValidationFailed
-Node(0) already exists with label `EdgeDevice` and property `name` = 'Edge Device 1'
-```
-The above [error](https://neo4j.com/docs/status-codes/current/) denotes ClientError as the error classification, Schema as the error category and ConstraintValidationFailed as the error title.
-
-### Import nodes
-So far, we have added only one edge device, we could add other devices as required in a similar manner. However it's common to import many such nodes from a CSV as it would be faster, than executing CREATE statements individually.
-
-I am just going to add some data in Google sheets as follows.
- There are 74 devices in the table, from device 2 to 75.
-
-I then published it with the following settings.. Let's now create nodes.
-```
-LOAD CSV WITH HEADERS FROM AS row
-CREATE (:EdgeDevice:Thing { name: row.name, floor: row.floor })
-
-Added 148 labels, created 74 nodes, set 148 properties, completed after 586 ms.
-```
-Awesome, so we have successfully created the edge device nodes.
-
-### Manufacturer nodes
-Let's do a similar exercise to add nodes for the manufacturers. We would add only one property which is name.
-
-Note that I got the companies list from [here](https://builtin.com/internet-things/iot-internet-of-things-companies)
-
-Let's create those. But this time let's go with a loop as we would only add 10 companies.
-```
-WITH ['Cooler Screens',
- 'Farmer’s Fridge',
- 'Simplisafe',
- 'Inspire',
- 'Enovo',
- 'Tive',
- 'Xage Security',
- 'Samsara',
- 'Arm',
- 'Clearblade'] AS manufacturers
-FOREACH ( manufacturer IN manufacturers | CREATE (m:Manufacturer{ name: manufacturer}) )
-
-Added 10 labels, created 10 nodes, set 10 properties, completed after 8 ms.
-```
-
-Let's also add a constraint for the name.
-```
-CREATE CONSTRAINT unqiue_manufacturer_name FOR (m:Manufacturer) REQUIRE m.name IS UNIQUE
-```
-
-## Sensor types
-Let's add few other nodes for the sensor type. I obtained the info form this [link](https://behrtech.com/blog/top-10-iot-sensor-types/)
-```
-WITH [
- 'Temperature',
- 'Humidity',
- 'Pressure',
- 'Proximity',
- 'Level',
- 'Accelerometers',
- 'Gyroscope',
- 'Gas',
- 'Infrared',
- 'Optical'
-] AS sensorTypes
-FOREACH ( sensorType IN sensorTypes | CREATE (:SensorType{ name: sensorType }) )
-
-Added 10 labels, created 10 nodes, set 10 properties, completed after 7 ms.
-```
-
-## Relatioships
-So far we have been adding nodes, for now these nodes are isolated data entities with out any relationships to other nodes.
-
-Let's now add a relationship between the nodes Edge Device 1 and Cooler Screens.
-
-Relationships are represented by arrows and square brackets. They are unidirectional `-[]->` or `<-[]-`. They also have a label like node, but it's only one label for a relationship unlike a node, and the relationship label is also called a relationship type.
-
-Like a node, we can also add properties to a relationship. So if we use `r` as the variable and `IS_MANUFACTURED_BY` as the label it should now become `-[r:IS_MANUFACTURED_BY]->`. Just like nodes, using a variable is optional here too, and is useful when there is a need to reuse it.
-
-Ok, so now let's put the source and target nodes in the relation, so the final Cypher would be `(:Edge_Device:Thing { name: 'Edge Device 1' } ) -[]-> (:Manufacturer { name: 'Cooler Screens'})`
-
-We have formed the cypher, we just need to put CREATE before it to create the relation.
-```
-Match ( e:EdgeDevice:Thing {name: 'Edge Device 1'}), (m:Manufacturer { name: 'Cooler Screens' } )
-CREATE (e) -[r:IS_MANUFACTURED_BY]-> (m)
-RETURN e, r, m
-```
-
-Let's use MATCH to get the graph.
-```
-MATCH (e:Edge_Device:Thing { name: 'Edge Device 1' } ) -[r:IS_MANUFACTURED_BY]-> (m:Manufacturer { name: 'Cooler Screens'}) RETURN e, r, m
-```
-
-The graph should look like 
-
-Note that we can drag the graph objects for desired visibility.
-
-### Sensor
-To say Edge device device 1 supports Temperature sensor.
-```
-Match ( e:EdgeDevice:Thing {name: 'Edge Device 1'}), (s:SensorType { name: 'Temperature' })
-CREATE (e) -[r:HAS_SENSOR_TYPE]-> (s)
-RETURN e, r, s
-```
-
-The returned graph should be
-
-
-Let's now see the final graph of Edge device 1 with both relationships.
-```
-MATCH (e:EdgeDevice:Thing) -[r]-> (n) RETURN e, r, n
-```
-
-
-Thus, we have put some minimal data relevant to IoT and explored some fundamental concepts/functionalities of GraphDB, Cypher, and the Neo4j browser. Thank you for reading !!!
-
-
diff --git a/_posts/2022-07-11-setup-iot-core-on-google-cloud-with-terraform.md b/_posts/2022-07-11-setup-iot-core-on-google-cloud-with-terraform.md
deleted file mode 100644
index 91e1f3c..0000000
--- a/_posts/2022-07-11-setup-iot-core-on-google-cloud-with-terraform.md
+++ /dev/null
@@ -1,351 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/setup-iot-core-on-google-cloud-with-terraform-4h6a
-categories: cloud, googlecloud, iot, terraform
-cover_image: https://source.unsplash.com/featured/?iot
-tags: cloud, googlecloud, iot, terraform
-title: Setup IoT core on Google cloud with Terraform
----
-
-*This post first appeared on [dev.to](https://dev.to/networkandcode/setup-iot-core-on-google-cloud-with-terraform-4h6a)*
-
-Hello :wave:, we shall see how to provision a minimal IoT infrastructure on Google cloud with Terraform.
-
-I shall be doing this straight on the Google cloud shell...
-
-## Project
-Set your gcloud config...
-
-Get you projects list and set one of the projects as the current project.
-```
-$ gcloud projects list
-
-$ gcloud config set project
-```
-
-## Directories
-Let's create two directories for the terraform resources, one for the service account and another for rest of the resources.
-```
-$ mkdir ~/sa
-$ mkdir ~/iot
-```
-and one more hidden directory for storing the keys/certificates.
-```
-$ mkdir ~/.auth
-```
-
-## TF Provider
-We would set the Terraform provider configuration here.
-
-Get the list of zones in the specific region. Note that cloud IoT is currently supported in these regions: asia-east1, europe-west1, us-central1.
-```
-$ gcloud compute zones list --filter="region~asia-east1" | grep -i name
-NAME: asia-east1-b
-NAME: asia-east1-a
-NAME: asia-east1-c
-```
-
-I would be using zone c.
-
-Set the provider details in terraform with the available information.
-```
-$ cat ~/sa/main.tf
-provider "google" {
- project = ""
- region = "asia-east1"
- zone = "asia-east1-c"
-}
-
-$ cp ~/sa/main.tf ~/iot/main.tf
-```
-
-## Service account
-We are going to create a service account from our user account, which could be further used for creating other resources using terraform.
-```
-$ ls ~/sa
-main.tf outputs.tf sa.tf
-
-$ cat ~/sa/sa.tf
-# https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/google_service_account
-
-resource "google_service_account" "iot_sa" {
- account_id = "iot-sa"
- display_name = "IoT Service Account"
-}
-
-# note this requires the terraform to be run regularly
-resource "time_rotating" "iot_sa_key_rotation" {
- rotation_days = 30
-}
-
-resource "google_service_account_key" "iot_sa_key" {
- service_account_id = google_service_account.iot_sa.name
-
- keepers = {
- rotation_time = time_rotating.iot_sa_key_rotation.rotation_rfc3339
- }
-}
-
-resource "google_project_iam_member" "iot_editor" {
- project = var.project_id
- role = "roles/cloudiot.editor"
- member = "serviceAccount:${google_service_account.iot_sa.email}"
-
- condition {
- title = "expires_after_2022_07_31"
- description = "Expiring at midnight of 2022-07-31"
- expression = "request.time < timestamp(\"2022-08-01T00:00:00Z\")"
- }
-}
-
-resource "google_project_iam_member" "pub_sub_editor" {
- project = var.project_id
- role = "roles/pubsub.editor"
- member = "serviceAccount:${google_service_account.iot_sa.email}"
-
- condition {
- title = "expires_after_2022_07_31"
- description = "Expiring at midnight of 2022-07-31"
- expression = "request.time < timestamp(\"2022-08-01T00:00:00Z\")"
- }
-}
-
-$ cat ~/sa/variables.tf
-variable "project_id" {
- type = string
- default = ""
-}
-
-$ cat ~/sa/outputs.tf
-output "iot_sa_private_key" {
- description = "Private key of the IoT service account"
- value = google_service_account_key.iot_sa_key.private_key
- sensitive = true
-}
-```
-
-So we are creating a service account with editor roles on IoT core & Pub/Sub, a key for the service account with rotation, and then we would output the private key to save it locally for future use.
-
-## API
-We have to enable the Cloud IoT [API](https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/google_project_service), you can get the fqdn of it using `$ gcloud services list --available --filter="name~.*iot.*"`. Let's add the terraform configuration which can enable it.
-```
-$ cat ~/sa/variables.tf
-variable "project_id" {
- type = string
- default = ""
-}
-
-$ cat ~/sa/apis.tf
-resource "google_project_service" "cloudiot" {
- project = var.project_id
- service = "cloudiot.googleapis.com"
-
- timeouts {
- create = "30m"
- update = "40m"
- }
-
- disable_dependent_services = true
-}
-```
-
-## Apply
-We can now create the service account, it's associated resources, and enable the Cloud IoT API.
-```
-$ cd ~/sa
-$ terraform init
-
-# optional, to know what will be changed
-$ terraform plan
-
-$ terraform apply --auto-approve
-```
-
-## Validate
-Validate the service account creation, via the console.
-
-
-And the roles attached to it.
-
-
-## Key
-The private key of the service account could be retrieved from the terraform output.
-```
-$ terraform output -raw iot_sa_private_key | base64 -d > ~/.auth/iot_sa_private_key.json
-```
-We have saved the base64 decoded private key in a hidden auth directory at home.
-
-## Credentials
-We could now start using the service principal's private key as a credential for rest of our Terraform activities, for which we have to set an environment variable.
-```
-$ export GOOGLE_APPLICATION_CREDENTIALS=~/.auth/iot_sa_private_key.json
-```
-
-Note: to remove the credential anytime, jus run `unset GOOGLE_APPLICATION_CREDENTIALS`
-
-## Certificate
-The connection between the IoT devices and Google IoT core would be secure over TLS, hence a [certificate](https://cloud.google.com/iot/docs/create-device-registry#create_your_credentials) should be generated for our virtual device.
-```
-$ openssl req -x509 -newkey rsa:2048 -keyout ~/.auth/rsa_private.pem -nodes -out ~/.auth/rsa_cert.pem -subj "/CN=unused"
-
-$ ls ~/.auth/ | grep pem
-rsa_cert.pem
-rsa_private.pem
-```
-The private key is in rsa_private.pem and the public certificate is in rsa_cert.pem.
-
-We would keep the private key locally and refer to it while generating a client connection from our device(we are not dealing with the client side of things in this post though), where as the public certificate would be attached to the remote side, in this case, the IoT core.
-
-## Registry
-Add the [terrafaorm](https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudiot_registry) configuration for the device registry, pub/sub topics it would use.
-```
-$ cd ~/iot
-
-$ cat registry.tf
-# https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudiot_registry
-
-resource "google_cloudiot_registry" "iot-registry" {
- name = "iot-registry"
-
- event_notification_configs {
- pubsub_topic_name = google_pubsub_topic.additional-telemetry.id
- subfolder_matches = "test/path"
- }
-
- event_notification_configs {
- pubsub_topic_name = google_pubsub_topic.default-telemetry.id
- subfolder_matches = ""
- }
-
- state_notification_config = {
- pubsub_topic_name = google_pubsub_topic.default-devicestatus.id
- }
-
- mqtt_config = {
- mqtt_enabled_state = "MQTT_ENABLED"
- }
-
- http_config = {
- http_enabled_state = "HTTP_ENABLED"
- }
-
- log_level = "INFO"
-}
-```
-We would be using 3 topics, all messages published by the client to the path /devices/DEVICE_ID/events would go to the default telemetry topic, and all messages for /devices/DEVICE_ID/state would go to the default device state topic. We have one additional topic with sub folder path "test/path" which means the messages published to /devices/DEVICE_ID/events/test/path would land there.
-
-## Pub/Sub
-A separate file for creating the pub/sub topics which will be linked to the registry.
-```
-resource "google_pubsub_topic" "default-devicestatus" {
- name = "default-devicestatus"
-}
-
-resource "google_pubsub_topic" "default-telemetry" {
- name = "default-telemetry"
-}
-
-resource "google_pubsub_topic" "additional-telemetry" {
- name = "additional-telemetry"
-}
-```
-## Devices
-We would be creating two devices, a basic one which should bind with the gateway, and an advanced device that could be standalone with out a gateway.
-
-The authentication for the basic device will be handled by the gateway and hence, we don't have to set any credentials for the basic device.
-```
-$ cat basic-device.tf
-# https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudiot_device
-
-resource "google_cloudiot_device" "basic-device" {
- name = "basic-device"
- registry = google_cloudiot_registry.iot-registry.id
-}
-
-$ cat advanced-device.tf
-# https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudiot_device
-
-resource "google_cloudiot_device" "advanced-device" {
- name = "advanced-device"
- registry = google_cloudiot_registry.iot-registry.id
-
- credentials {
- public_key {
- format = "RSA_X509_PEM"
- key = file("~/.auth/rsa_cert.pem")
- }
- }
-}
-```
-
-## Gateway
-And now the gateway.
-```
-# https://registry.terraform.io/providers/hashicorp/google/latest/docs/resources/cloudiot_device
-
-resource "google_cloudiot_device" "iot-gateway" {
- name = "iot-gateway"
- registry = google_cloudiot_registry.iot-registry.id
-
- credentials {
- public_key {
- format = "RSA_X509_PEM"
- key = file("~/.auth/rsa_cert.pem")
- }
- }
-
- gateway_config {
- gateway_type = "GATEWAY"
- gateway_auth_method = "ASSOCIATION_ONLY"
- }
-}
-```
-I have setup ASSOCIATION_ONLY as the auth method, which means the device I will bind to this gateway would rely on this gateway for authentication and woudln't authenticate with its own credential.
-
-## Apply
-The resources can be created.
-```
-$ terraform init
-
-# optional, to see what will change
-$ terraform plan
-
-$ terraform apply
-```
-
-## Bind
-The basic device should be bounded with the gateway, so that the gateway generate JWTs on behalf of the device.
-```
-$ gcloud iot devices gateways bind --gateway iot-gateway --gateway-region asia-east1 --gateway-registry iot-registry --device basic-device --device-region asia-east1
-```
-I used gcloud for binding the device with the gateway as I was not able to quite find it in the terraform registry.
-
-## Validate
-Finally, check the resources on the console.
-
-*Registry*
-
-
-*Devices*
-
-
-*Gateway*
-
-
-*Device binding*
-
-
-Seems all good :)
-
-## Graph
-Let's look at the graph that terraform can generate. We can view it on the cloud shell editor itself.
-
-```
-$ terraform graph | dot -Tsvg > graph.svg
-
-$ ls *.svg
-graph.svg
-```
-
-
-
-With this the post is complete, thanks for reading !!!
diff --git a/_posts/2022-07-17-aws-iot-pub-sub-over-mqtt.md b/_posts/2022-07-17-aws-iot-pub-sub-over-mqtt.md
deleted file mode 100644
index 959741b..0000000
--- a/_posts/2022-07-17-aws-iot-pub-sub-over-mqtt.md
+++ /dev/null
@@ -1,295 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/aws-iot-pubsub-over-mqtt-1oig
-categories: aws, ios, python, mqtt
-cover_image: https://source.unsplash.com/featured/?device
-date: 2022-07-17
-tags: aws, ios, python, mqtt
-title: AWS IoT pub/sub over MQTT
----
-
-*This post first appeared on [dev.to](https://dev.to/aws-builders/aws-iot-pubsub-over-mqtt-1oig)*
-
-## Introduction
-Hello, in this post we would create an IoT thing on AWS, use it's credentials, to create two virtual clients on a Linux VM with python and test publishing from one client and subscribing from the other.
-
-## VM
-Use your Linux machine or a VM as a virtual IoT device. We would be doing all of the CLI / coding tasks in the post, on this VM.
-
-## AWS
-Install and setup the [AWS CLI](https://aws.amazon.com/cli/). Here is the region I have set as default.
-```
-$ cat ~/.aws/config
-[default]
-region = ap-south-1
-```
-
-## Endpoint
-Goto `ASW IoT > Settings` on the cloud console, and get the Device data endpoint which is unique to the AWS account/region. Or get it from the AWS CLI.
-```
-$ IOT_DEV_EP=$(aws iot describe-endpoint --region ap-south-1 --output text --query endpointAddress)
-
-$ echo $IOT_DEV_EP
-.iot.ap-south-1.amazonaws.com
-```
-
-Check connectivity to this endpoint from the Linux VM, which is your virtual IoT device.
-```
-$ ping -c 1 $IOT_DEV_EP
----TRUNCATED---
-1 packets transmitted, 1 received, 0% packet loss, time 0ms
-rtt min/avg/max/mdev = 196.145/196.145/196.145/0.000 ms
-```
-
-I have tested with 1 packet `-c 1`. You may send more than one though.
-
-You can also check connectivity to the secure port for MQTT i.e. 8883 on the endpoint. Telnet should be present/installed on the machine though, for ex. `sudo yum install telnet -y`.
-```
-$ telnet $IOT_DEVICE_EP 8883
-Trying ...
-Connected to -ats.iot.ap-south-1.amazonaws.com.
-Escape character is '^]'.
-```
-
-## Thing
-Goto `AWS IoT > Manage > Things > Create Things`
-on the cloud console and create a new thing with the name *temp-sensor*, set unnamed shadow(classic) and choose
-*Auto-generate a new certificate (recommended)*.
-
-In the policies section, create and select a new policy with the name *temp-sensor* and the following JSON.
-```
-{
- "Version": "2012-10-17",
- "Statement": [
- {
- "Effect": "Allow",
- "Action": [
- "iot:Connect",
- "iot:Publish",
- "iot:Receive",
- "iot:RetainPublish",
- "iot:Subscribe"
- ],
- "Resource": "*"
- }
- ]
-}
-```
-Download all the certificates/keys and name those as needed, I have named them as follows.
-```
-$ ls *.pem
-ca-cert.pem pub-cert.pem pub-key.pem pvt-key.pem
-```
-
-Note: If you are using a different host system like Windows with a browser, you can download these files, copy the content and then paste into the respective file on a Linux VM.
-
-## SDK
-We would be using the AWS IoT SDK for Python.
-```
-# Clone the repository
-git clone https://github.com/aws/aws-iot-device-sdk-python-v2.git
-
-# Install using Pip
-python3 -m pip install ./aws-iot-device-sdk-python-v2
-
-# Remove the clone, if it isn't required anymore
-$ rm -rf aws-iot-device-sdk-python-v2
-```
-
-## Connect
-We have to first import the mqtt_connection_builder package from the awsiot sdk.
-```
-from awsiot import mqtt_connection_builder
-```
-We need the endpoint, the cerificate/key paths and a client_id to initiate a connection. We can generate a client_id using the uuid package.
-```
-from uuid import uuid4
-client_id = 'client-' + str(uuid4())
-```
-
-We can then pass the files as arguments using the argparse package.
-```
-##### parse arguments
-import argparse
-
-parser = argparse.ArgumentParser(description="Send and receive messages through and MQTT connection.")
-
-parser.add_argument('--ep', help="IoT device endpoint .iot..amazonaws.com", required=True, type=str)
-parser.add_argument('--pubcert', help="IoT device public certificate file path", required=True, type=str)
-parser.add_argument('--pvtkey', help="IoT device private key file path", required=True, type=str)
-parser.add_argument('--cacert', help="IoT device CA cert file path", required=True, type=str)
-parser.add_argument('--topic', help="Topic name", required=True, type=str)
-
-args = parser.parse_args()
-```
-You can also skip the parse arguments step and add the parameters directly.
-
-We have the necessary parameters to initiate the connection.
-```
-mqtt_connection = mqtt_connection_builder.mtls_from_path(
- endpoint=args.ep,
- cert_filepath=args.pubcert,
- pri_key_filepath=args.pvtkey,
- ca_filepath=args.cacert,
- client_id=client_id
-)
-
-connect_future = mqtt_connection.connect()
-
-# result() waits until a result is available
-connect_future.result()
-print(f'{client_id} is connected!')
-```
-
-Put the code we saw in the connect section so far in a file called connect.py and run the following.
-```
- $ python connect.py --ep $IOT_DEV_EP --pubcert pub-cert.pem --pvtkey pvt-key.pem --cacert ca-cert.pem --topic temperature
-client-3924e5d4-97d3-43e6-b214-169d008b2d02 is connected!
-```
-Great, the connection is successful.
-
-## Publish
-Before publishing, let's import certain variables from the previous connect code we wrote.
-```
-# import vars from connect.py
-from connect import args, client_id, mqtt_connection
-```
-
-We shall publish a message from our client that contains the client-id, temperature and current time. We already have the client_id with us.
-
-We can use the datetime library for getting the timestamp.
-```
-# set timestamp
-from datetime import datetime
-now = datetime.now()
-```
-
-And we can generate a random number for the temperature.
-```
-# set temperature
-import random
-temp = random.randrange(10, 40)
-```
-
-So our message now looks like:
-```
-# form the message
-message = f'id: {client_id}, temp: {temp}, time: {now}'
-```
-
-Time to publish it with the publish method.
-```
-# publish the message
-from awscrt import mqtt
-import json
-mqtt_connection.publish(
- topic=args.topic,
- payload= json.dumps(message),
- qos=mqtt.QoS.AT_LEAST_ONCE
-)
-print('Message published')
-```
-
-Note that awscrt is the AWS common runtime library we are using to set the [QoS](http://docs.oasis-open.org/mqtt/mqtt/v3.1.1/os/mqtt-v3.1.1-os.html#_Toc385349263).
-
-Put this code in a separate file with name *publisher.py* and run it.
-```
- $ python publisher.py --ep $IOT_DEV_EP --pubcert pub-cert.pem --pvtkey pvt-key.pem --cacert ca-cert.pem --topic temperature
-client-cb3f69b6-b53b-42a4-973f-63abe39f2c4f is connected!
-Message published
-```
-
-So far we published only one message, I would be modifying the code so that it continuously sends one message per second until interrupted with Ctrl C.
-```
-$ cat publisher.py
-# import vars from connect.py
-from connect import args, client_id, mqtt_connection
-
-from awscrt import mqtt
-from datetime import datetime
-import json, random, time
-
-while True:
- # set timestamp
- now = datetime.now()
-
- # set temperature
- temp = random.randrange(10, 40)
-
- # form the message
- message = f'id: {client_id}, temp: {temp}, time: {now}'
-
- # publish the message
- mqtt_connection.publish(
- topic=args.topic,
- payload= json.dumps(message),
- qos=mqtt.QoS.AT_LEAST_ONCE
- )
- print(f'Message published: {message}')
- time.sleep(1)
-```
-
-Run the code again.
-```
- $ python publisher.py --ep $IOT_DEV_EP --pubcert pub-cert.pem --pvtkey pvt-key.pem --cacert ca-cert.pem --topic temperature
-client-1102832d-a0c0-481c-b1f4-5b363f9c0890 is connected!
-Message published: id: client-1102832d-a0c0-481c-b1f4-5b363f9c0890, temp: 14, time: 2022-07-17 09:20:44.652955
-Message published: id: client-1102832d-a0c0-481c-b1f4-5b363f9c0890, temp: 29, time: 2022-07-17 09:20:45.654102
-Message published: id: client-1102832d-a0c0-481c-b1f4-5b363f9c0890, temp: 35, time: 2022-07-17 09:20:46.655002
-```
-
-Publishing looks good, let's go to the subscriber.
-
-## Subscriber
-Firts, import certain vars from the connect module, similar to what we did in publisher.
-```
-# import vars from connect.py
-from connect import args, mqtt_connection
-```
-
-Define a callback function that triggers when a message is received on the topic.
-```
-# call back to trigger when a message is received
-def on_message_received(topic, payload, dup, qos, retain, **kwargs):
- print("Received message from topic '{}': {}".format(topic, payload))
-```
-
-Subscribe to the topic.
-```
-##### subscribe to topic
-from awscrt import mqtt
-subscribe_future, packet_id = mqtt_connection.subscribe(
- topic=args.topic,
- qos=mqtt.QoS.AT_LEAST_ONCE,
- callback=on_message_received
-)
-
-# result() waits until a result is available
-subscribe_result = subscribe_future.result()
-print(f'Subscribed to {args.topic}')
-```
-
-We need to the keep the program open, so that we can read the messages, as defined in the callback function. For this, we can use the threading module.
-```
-import threading
-threading.Event().wait()
-```
-
-Keep this code in a file named subscriber.py.
-
-Time to run the subscriber code while the publisher code is also running.
-
-
-## Test on console
-You can also test if the publish/subscribe operations are working correctly via the handy MQQT test client on AWS cloud. So if you are publishig from the code, you can test it at the subscriber window.
-
-
-And likewise if you are subscribing on the code, you can publish a test message from the MQTT test client.
-
-```
-$ python3 subscriber.py --ep $IOT_DEV_EP --pubcert pub-cert.pem --pvtkey pvt-key.pem --cacert ca-cert.pem --topic temperature
-client-a17093b1-108e-4f3c-a65c-ea38900f2153 is connected!
-Subscribed to temperature
-Received message from topic 'temperature': b'{\n "message": "Hello from AWS IoT console"\n}'
-```
-
-With this the post is complete ;), thank you for reading !!!. For other code examples provided by the AWS team, please checkout this [github link](https://github.com/aws/aws-iot-device-sdk-python-v2/tree/main/samples)
\ No newline at end of file
diff --git a/_posts/2022-08-29-aws-cloudtrail-log-file-validation.md b/_posts/2022-08-29-aws-cloudtrail-log-file-validation.md
deleted file mode 100644
index 9d1c8ed..0000000
--- a/_posts/2022-08-29-aws-cloudtrail-log-file-validation.md
+++ /dev/null
@@ -1,145 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/aws-cloudtrail-log-file-validation-1ehl
-categories: aws, cloudtrail, logging, s3
-date: 2022-08-29
-tags: aws, cloudtrail, logging, s3
-title: AWS CloudTrail log file validation
----
-
-This post first appeared on [dev.to](https://dev.to/aws-builders/aws-cloudtrail-log-file-validation-1ehl)
-
-## Introduction
-CloudTrail lets us log all API calls in our AWS cloud. In this post, we shall see how to create a CloudTrail, see where the logs are stored
-in S3, delete log, digest files and perform log file validation.
-
-## Create a CloudTrail
-Search for CloudTrail on the AWS console and create a trail.
-
-
-## S3 bucket
-A bucket should be automatically created and associated with the CloudTrail. A folder with the name CloudTrail should appear on the bucket
-where all the cloud trail logs should get saved.
-
-
-## Generate logs
-Now let's do an activity and see if it gets logged. Create a lambda function with name helloWorld and all other settings as default. You can
-do any other activity on AWS cloud as well, instead of creating a function.
-
-
-We should see some files on S3 for this activity.
-
-
-## Delete log file
-I am deleting one of the log files.
-
-
-Log files are not suppose to be modified/deleted, as they can hold important auditing information, so now we need to find if our log files
-are modified or deleted(as in this case).
-
-We try to validate now from the [AWS CLI](https://aws.amazon.com/cli/), it should say the digest file doesn't exit.
-```
-$ aws cloudtrail validate-logs --trail-arn arn:aws:cloudtrail:ap-south-1::trail/management-events --start-time 2022-08-29
-Validating log files for trail arn:aws:cloudtrail:ap-south-1::trail/management-events between 2022-08-29T00:00:00Z and
-2022-08-29T06:26:38Z
-
-Results requested for 2022-08-29T00:00:00Z to 2022-08-29T06:26:38Z
-No digests found
-```
-
-This is because we have not enabled log file validation for the cloud trail.
-
-## Enable Log file validation
-We can enable log file validation, by editing the cloud trail.
-
-
-
-## Digest
-As the log file validation is enabled, we should see a new folder CloudTrail-Digest in S3.
-
-
-And digest files should get added each hour.
-
-
-
-## Validate
-As we enabled Log file validation, we can now check the integirty of the logs.
-```
-$ aws cloudtrail validate-logs --trail-arn arn:aws:cloudtrail:ap-south-1::trail/management-events --start-time 2022-08-29
-Validating log files for trail arn:aws:cloudtrail:ap-south-1::trail/management-events between 2022-08-29T00:00:00Z and
-2022-08-29T07:00:20Z
-
-Results requested for 2022-08-29T00:00:00Z to 2022-08-29T07:00:20Z
-Results found for 2022-08-29T05:55:08Z to 2022-08-29T06:55:08Z:
-
-1/1 digest files valid
-```
-Though we deleted a log file earlier, it shows the digest is valid, because we did not enable log file validation then.
-
-After an hour, we should see two digest files.
-
-
-The log file validation seems good for now.
-```
-$ aws cloudtrail validate-logs --trail-arn arn:aws:cloudtrail:ap-south-1::trail/management-events --start-time 2022-08-29
-Validating log files for trail arn:aws:cloudtrail:ap-south-1::trail/management-events between 2022-08-29T00:00:00Z and
-2022-08-29T08:17:57Z
-
-Results requested for 2022-08-29T00:00:00Z to 2022-08-29T08:17:57Z
-Results found for 2022-08-29T05:55:08Z to 2022-08-29T07:55:08Z:
-
-2/2 digest files valid
-10/10 log files valid
-```
-
-## Delete log file with validation check
-We can try deleting log file that was created after enabling log file validation.
-
-
-As expected the log file validations fails for one file. However the digests are still valid.
-```
-$ aws cloudtrail validate-logs --trail-arn arn:aws:cloudtrail:ap-south-1::trail/management-events --start-time 2022-08-29
-Validating log files for trail arn:aws:cloudtrail:ap-south-1::trail/management-events between 2022-08-29T00:00:00Z and
-2022-08-29T08:22:42Z
-
-Log file
-s3://aws-cloudtrail-logs--4a8dcb98/AWSLogs//CloudTrail/ap-south-1/2022/08/29/_CloudTrail_ap-south-1_20220829T0755Z_7rDSVFC6Icgi9Z8V.json.gz
-INVALID: not found
-
-Results requested for 2022-08-29T00:00:00Z to 2022-08-29T08:22:42Z
-Results found for 2022-08-29T05:55:08Z to 2022-08-29T07:55:08Z:
-
-2/2 digest files valid
-9/10 log files valid, 1/10 log files INVALID
-```
-It also clearly says the validation failed because it can't find a file that we deleted.
-
-## Delete digest
-This time we can try deleting a digest file.
-
-
-Hence digest validation should also fail.
-```
-$ aws cloudtrail validate-logs --trail-arn arn:aws:cloudtrail:ap-south-1::trail/management-events --start-time 2022-08-29
-Validating log files for trail arn:aws:cloudtrail:ap-south-1::trail/management-events between 2022-08-29T00:00:00Z and
-2022-08-29T10:09:35Z
-
-Digest file
-s3://aws-cloudtrail-logs--4a8dcb98/AWSLogs//CloudTrail-Digest/ap-south-1/2022/08/29/_CloudTrail-Digest_ap-south-1_management-events_ap-south-1_20220829T085508Z.json.gz
-INVALID: not found
-
-Log file
-s3://aws-cloudtrail-logs--4a8dcb98/AWSLogs//CloudTrail/ap-south-1/2022/08/29/_CloudTrail_ap-south-1_20220829T0755Z_7rDSVFC6Icgi9Z8V.json.gz
-INVALID: not found
-
-Results requested for 2022-08-29T00:00:00Z to 2022-08-29T10:09:35Z
-Results found for 2022-08-29T05:55:08Z to 2022-08-29T09:55:08Z:
-
-3/4 digest files valid, 1/4 digest files INVALID
-20/21 log files valid, 1/21 log files INVALID
-```
-
-Note that we can enable versioning on S3 buckets to restore files.
-
-## Summary
-So we saw how the log file validation feature in CloudTrail helps us find if there were any manual modifications to the log files or digest
-files. Thank you for reading !!!
diff --git a/_posts/2022-10-08-gcp-anthos-cluster-on-aws.md b/_posts/2022-10-08-gcp-anthos-cluster-on-aws.md
deleted file mode 100644
index c546602..0000000
--- a/_posts/2022-10-08-gcp-anthos-cluster-on-aws.md
+++ /dev/null
@@ -1,433 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/gcp-anthos-cluster-on-aws-19p8
-categories: anthos, aws, gcp, kubernetes
-date: 2022-10-08
-tags: anthos, aws, gcp, kubernetes
-title: GCP Anthos Cluster on AWS
----
-
-This post first appeared on [dev.to](https://dev.to/aws-builders/gcp-anthos-cluster-on-aws-19p8)
-
-
-Anthos is a software offering from Google, using which we can build kubernetes clusters on nodes both on and off cloud. In this post, we
-would launch an EC2 instance in AWS and build a single node kubernetes cluster on it with Anthos.
-
-Let's get started.
-
-## AWS cloud shell
-Login to the AWS console, and access the cloud shell from the top bar. You should see a prompt like below.
-```
-[cloudshell-user@ip-10-0-89-211 ~]$
-```
-
-## EC2
-Create an EC2 instance with other relevant components with these commands. Please refer to this
-[post](https://dev.to/aws-builders/aws-ec2-launch-instances-the-hard-way-with-cli-2ga3) for explanation on what each of these commands does.
-```
-$ mkdir ~/.aws
-
-$ cat ~/.aws/config < anthosKeyPair.pem
-$ mkdir .ssh
-$ mv anthosKeyPair.pem ~/.ssh/
-
-$ aws ec2 run-instances --image-id ami-0bba4b75264ecbfbd --count 1 --instance-type t2.large --key-name anthosKeyPair --security-group-ids
-$ANTHOS_SG_ID --subnet-id $ANTHOS_SUBNET_ID --associate-public-ip-address --block-device-mappings
-'DeviceName=/dev/sda1,Ebs={VolumeSize=200}'
-```
-
-The instance is now created. We can give it a name.
-```
-$ ANTHOS_INSTANCE_ID=$(aws ec2 describe-instances | jq -r '.Reservations[] | .Instances[] | select(.SubnetId==env.ANTHOS_SUBNET_ID) |
-.InstanceId')
-
-$ aws ec2 create-tags --resources $ANTHOS_INSTANCE_ID --tags Key=Name,Value=anthos-node
-```
-
-## SSH
-In order to SSH from the cloud shell to the Anthos instance, we first need to obtain the public IP of the cloudshell and add a rule in the
-security group to allow SSH access from that.
-```
-$ export MY_PUBLIC_IP=$(curl ifconfig.me --silent)
-$ aws ec2 authorize-security-group-ingress --group-id $ANTHOS_SG_ID --protocol tcp --port 22 --cidr $MY_PUBLIC_IP/32
-```
-
-Copy the SSH key pair to the instance as it's needed in the Anthos cluster config.
-```
-$ export ANTHOS_INSTANCE_IP=$(aws ec2 describe-instances --filter Name=tag:Name,Values=anthos-node --query
-"Reservations[*].Instances[*].PublicIpAddress" --output text)
-
-$ scp -i ~/.ssh/anthosKeyPair.pem ~/.ssh/anthosKeyPair.pem ubuntu@$ANTHOS_INSTANCE_IP:~/.ssh/anthosKeyPair.pem
-```
-
-SSH into the instance.
-```
-$ ssh -i ~/.ssh/anthosKeyPair.pem ubuntu@$ANTHOS_INSTANCE_IP
-```
-
-## Install gcloud
-Install the gcloud cli on the Anthos instance.
-```
-sudo apt-get install apt-transport-https ca-certificates gnupg -y
-
-echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | sudo tee -a
-/etc/apt/sources.list.d/google-cloud-sdk.list
-
-curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key --keyring /usr/share/keyrings/cloud.google.gpg add -
-
-sudo apt-get update -y && sudo apt-get install google-cloud-cli -y
-```
-
-## Login to gcloud
-This step is optional. Login to the gcloud cli with your account if you are going to create a service account yourself from the CLI.
-```
-gcloud auth login
-```
-
-## Authenticaion
-Create a [service account](https://cloud.google.com/iam/docs/creating-managing-service-accounts) in GCP and give it the following roles.
-```
-roles/gkehub.connect
-roles/gkehub.admin
-roles/logging.logWriter
-roles/monitoring.metricWriter
-roles/monitoring.dashboardEditor
-roles/stackdriver.resourceMetadata.writer
-roles/opsconfigmonitoring.resourceMetadata.writer
-```
-
-If you are using the gcloud CLI, you can create a service account and bind the roles with the following command.
-```
-gcloud iam service-accounts create
-
-gcloud projects add-iam-policy-binding "$PROJECT_ID" \
- --member= \
- --role= \
- --no-user-output-enabled
-```
-
-Create a key for the service account and copy it's credentials.
-```
-gcloud iam service-accounts keys create \
- --iam-account=${service-account-name}@${PROJECT_ID}.iam.gserviceaccount.com
-```
-
-Setup the credentials in the instance, activate the service account and set the project id.
-```
-$ mkdir .gcloud
-$ export PROJECT_ID=
-
-$ cat > .gcloud/keyfile.json << EOF
-{
- "type": "service_account",
- "project_id": $PROJECT_ID,
- "private_key_id": "",
- "private_key": ,
- "client_email": ,
- "client_id": ,
- "auth_uri": "https://accounts.google.com/o/oauth2/auth",
- "token_uri": "https://oauth2.googleapis.com/token",
- "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
- "client_x509_cert_url":
-}
-EOF
-
-$ gcloud auth activate-service-account --key-file .gcloud/keyfile.json
-
-$ export GOOGLE_APPLICATION_CREDENTIALS='/home/ubuntu/.gcloud/keyfile.json'
-
-$ gloud config set project $PROJECT_ID
-```
-
-## APIs
-Enable the services.
-```
-gcloud services enable \
- anthos.googleapis.com \
- anthosaudit.googleapis.com \
- anthosgke.googleapis.com \
- cloudresourcemanager.googleapis.com \
- container.googleapis.com \
- gkeconnect.googleapis.com \
- gkehub.googleapis.com \
- serviceusage.googleapis.com \
- stackdriver.googleapis.com \
- monitoring.googleapis.com \
- logging.googleapis.com \
- opsconfigmonitoring.googleapis.com
-```
-
-## Other tools
-Install kubectl, bmctl and docker.
-```
-curl -LO "https://storage.googleapis.com/kubernetes-release/release/$(curl -s
-https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl"
-
-chmod +x kubectl
-sudo mv kubectl /usr/local/sbin/
-
-gsutil cp gs://anthos-baremetal-release/bmctl/1.13.0/linux-amd64/bmctl .
-chmod a+x bmctl
-sudo mv bmctl /usr/local/sbin/
-
-curl -O https://download.docker.com/linux/static/stable/x86_64/docker-20.10.9.tgz
-tar xzvf docker-20.10.9.tgz
-sudo cp docker/* /usr/bin/
-rm -rf docker*
-sudo groupadd docker
-sudo usermod -aG docker $USER
-sudo dockerd&
-newgrp docker
-```
-
-## VxLAN
-Set up vxlan with the IP 10.200.2/24.
-```
-sudo ip link add vxlan0 type vxlan id 42 dev eth0 dstport 0
-sudo ip addr add 10.200.0.2/24 dev vxlan0
-sudo ip link set up dev vxlan0
-```
-
-## Cluster config
-Create the Anthos cluster config with bmctl.
-```
-export CLUSTER_ID=anthos-aws
-bmctl create config -c $CLUSTER_ID
-```
-
-Change the config.
-```
-$ cat > bmctl-workspace/${CLUSTER_ID}/${CLUSTER_ID}.yaml << EOF
----
-gcrKeyPath: /home/ubuntu/.gcloud/keyfile.json
-sshPrivateKeyPath: /home/ubuntu/.ssh/anthosKeyPair.pem
-gkeConnectAgentServiceAccountKeyPath: /home/ubuntu/.gcloud/keyfile.json
-gkeConnectRegisterServiceAccountKeyPath: /home/ubuntu/.gcloud/keyfile.json
-cloudOperationsServiceAccountKeyPath: /home/ubuntu/.gcloud/keyfile.json
----
-apiVersion: v1
-kind: Namespace
-metadata:
- name: cluster-${CLUSTER_ID}
----
-apiVersion: baremetal.cluster.gke.io/v1
-kind: Cluster
-metadata:
- name: ${CLUSTER_ID}
- namespace: cluster-${CLUSTER_ID}
-spec:
- profile: edge
- type: standalone
- anthosBareMetalVersion: 1.13.0
- gkeConnect:
- projectID: $PROJECT_ID
- controlPlane:
- nodePoolSpec:
- clusterName: ${CLUSTER_ID}
- nodes:
- - address: 10.200.0.2
- clusterNetwork:
- pods:
- cidrBlocks:
- - 192.168.0.0/16
- services:
- cidrBlocks:
- - 172.26.232.0/24
- loadBalancer:
- mode: bundled
- ports:
- controlPlaneLBPort: 443
- vips:
- controlPlaneVIP: 10.200.0.49
- ingressVIP: 10.200.0.50
- addressPools:
- - name: pool1
- addresses:
- - 10.200.0.50-10.200.0.70
- clusterOperations:
- location: asia-south1
- projectID: $PROJECT_ID
- storage:
- lvpNodeMounts:
- path: /mnt/localpv-disk
- storageClassName: node-disk
- lvpShare:
- numPVUnderSharedPath: 5
- path: /mnt/localpv-share
- storageClassName: local-shared
- nodeConfig:
- podDensity:
- maxPodsPerNode: 64
- nodeAccess:
- loginUser: ubuntu
-EOF
-```
-
-## Cluster creation
-Create the cluster.
-```
-$ bmctl create cluster -c ${CLUSTER_ID}
-```
-
-The above command should take some time and once it's successful, the kubernetes cluster should be ready.
-```
-$ export KUBECONFIG=bmctl-workspace/${CLUSTER_ID}/${CLUSTER_ID}-kubeconfig
-
-$ kubectl get nodes
-NAME STATUS ROLES AGE VERSION
-ip-10-0-0-9 Ready control-plane,master 153m v1.24.2-gke.1900
-```
-The cluster should appear on the Anthos clusters plage on GCP.
-
-## Run workloads
-Test with a sample nginx deployment.
-```
-$ cat > deploy.yaml << EOF
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: nginx
-spec:
- template:
- metadata:
- labels:
- app: nginx
- spec:
- containers:
- - name: nginx
- image: nginx
- selector:
- matchLabels:
- app: nginx
-EOF
-
-$ kubectl create -f deploy.yaml
-
-$ kubectl get deploy
-NAME READY UP-TO-DATE AVAILABLE AGE
-nginx 1/1 1 1 65s
-
-$ kubectl get pod
-NAME READY STATUS RESTARTS AGE
-nginx-8f458dc5b-jvrbb 1/1 Running 0 68s
-```
-
-Expose this deployment with a service.
-```
-$ cat > svc.yaml < 8080/TCP 106s
-
-$ kubectl get ep nginx
-NAME ENDPOINTS AGE
-nginx 192.168.0.48:80 2m3s
-```
-
-Try to curl the service IP and see if it works.
-```
-$ curl 172.26.232.21:8080
-
-
-
-Welcome to nginx!
-
-
-
-
Welcome to nginx!
-
If you see this page, the nginx web server is successfully installed and
-working. Further configuration is required.
-
-
For online documentation and support please refer to
-nginx.org.
-Commercial support is available at
-nginx.com.
-
-
Thank you for using nginx.
-
-
-```
-
-## Reset the cluster
-Finally reset the cluster when you no longer need it.
-```
-bmctl reset cluster -c ${CLUSTER_ID}
-```
-
-Thus, we have launched a single node kubernetes cluster with Anthos on AWS, and tested it by running an nginx service.
-
-Thanks for reading!!!
diff --git a/_posts/2022-11-20-subscribe-to-aws-iot-on-influxdb.md b/_posts/2022-11-20-subscribe-to-aws-iot-on-influxdb.md
deleted file mode 100644
index 0827056..0000000
--- a/_posts/2022-11-20-subscribe-to-aws-iot-on-influxdb.md
+++ /dev/null
@@ -1,102 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/send-messages-from-aws-iot-to-influxdb-via-native-mqtt-subscription-3366
-categories: aws, influxdb, iot, mqtt
-cover_image:
-https://images.unsplash.com/photo-1545259741-2ea3ebf61fa3?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=1770&q=80
-date: 2022-11-20
-tags: aws, influxdb, iot, mqtt
-title: Subscribe to AWS IoT topic on InfluxDB
----
-
-This post first appeared on [dev.to](https://dev.to/aws-builders/harperdb-on-eks-1bcb)
-
-Hey :wave:, here is my first post after the community builder renewal :satisfied:. In this post, we would send some MQTT messages in line
-protocol format to AWS IoT, which would then get ingested to InfluxDB via a native MQTT subscription.
-
-InfluxDB usually relies on systems such as Telegraf or some client programs to send metrics to it, however here with the native
-subscription, we don't need the intermediate system.
-
-As a prerequisite, follow this [post](https://dev.to/aws-builders/aws-iot-pubsub-over-mqtt-1oig) to understand how to publish messages from
-a Python based MQTT client to the MQTT endpoint in AWS.
-
-We would be making change to the publisher code, as InfluxDB looks for messages in a different format called as the line protocol.
-
-Refer to this
-[link](https://docs.influxdata.com/influxdb/cloud/reference/syntax/line-protocol/#:~:text=InfluxDB%20uses%20line%20protocol%20to,timestamp%20of%20a%20data%20point.&text=Lines%20separated%20by%20the%20newline,a%20single%20point%20in%20InfluxDB.)
-for more information on the lineprotocol.
-
-A sample message in our case would be like *temp_sensor,id=client-d36a601f-0b0e-4ba2-9d54-45feec236deb,room=lobby temp=30
-1668930716251915510*
-
-Where temp_sensor is the measurement name, the tags are id and room, the field is temp. Note the timestamp above is in unix timestamp format
-in nanoseconds. Note that the tags & timestamp are optional in line protocol, and you can have more than one filed. The timestamp will
-default to the current time if not provided.
-
-Our publisher code would look like below.
-```
-nc:~/environment/iot $ cat publish-line-protocol.py
-# import vars from connect.py
-from connect import args, client_id, mqtt_connection
-
-from awscrt import mqtt
-import json, random, time
-
-while True:
- rooms = [ 'bed-room', 'hall', 'kitchen', 'living-room', 'lobby' ]
- room = random.choice(rooms)
-
- # set random temperature between 24 and 32 (this is celsius range)
- temp = random.randrange(24, 32)
-
- # set timestamp in nanoseconds
- now = time.time_ns()
-
- # form the message
- message = f'temp_sensor,id={client_id},room={room} temp={temp} {now}'
-
- # publish the message
- mqtt_connection.publish(
- topic=args.topic,
- payload= message,
- qos=mqtt.QoS.AT_LEAST_ONCE
- )
- print(f'Message published: {message}')
- time.sleep(1)
-```
-
-Let's run the code.
-```
-nc:~/environment/iot $ python publish-line-protocol.py --ep $IOT_DEV_EP --pubcert pub-cert.pem --pvtkey pvt-key.pem --cacert ca-cert.pem
---topic temperature
-client-7219bca1-8c06-41c8-b69c-783c3ee85a41 is connected!
-Message published: temp_sensor,id=client-7219bca1-8c06-41c8-b69c-783c3ee85a41,room=hall temp=29 1668932805475181112
-Message published: temp_sensor,id=client-7219bca1-8c06-41c8-b69c-783c3ee85a41,room=hall temp=24 1668932806476308869
-Message published: temp_sensor,id=client-7219bca1-8c06-41c8-b69c-783c3ee85a41,room=lobby temp=24 1668932807477465026
-```
-
-Press Ctrl C when you want to stop the code.
-
-Now, let's launch InfluxDB, you may get a cloud subscription from the AWS
-[marketplace](https://aws.amazon.com/marketplace/pp/prodview-4e7raoxoxsl4y?ref_=unifiedsearch), or directly from the
-[influxdata](https://cloud2.influxdata.com/) portal.
-
-On InfluxDB, Goto Load Data > Native Subscriptions and create a new suscription. Set the subscription name as *temp_sensor*. Enter some
-description like *Messages from AWS MQTT*. Go to Security details > certificate and copy/paste the ca certificate, private key and public
-certificate downloaded from AWS while creating the thing in IoT. Set the topic as *temperature* because that's where we were publishing the
-messages to. And then set the write destination to a bucket, which can be created if it doesn't exist yet.
-
-
-That's it, save the subscription.
-
-We can now visit the data explorer, and see the graph for the data sent. If we hover over the graph, we should be able to see the values
-for each of the tags(rooms) that have different colors.
-
-
-This way we can send MQTT metrics to InfluxDB with subscriptions and visualize those. A couple of things before finishing, you may stop the
-subscription, when you don't want to keep it running,
-
-
-and there is a notifications link on the subscription that should help you with logs for troubleshooting errors.
-
-
-Thank you for reading !!!
diff --git a/_posts/2023-01-09-harperdb-on-eks.md b/_posts/2023-01-09-harperdb-on-eks.md
deleted file mode 100644
index 574557c..0000000
--- a/_posts/2023-01-09-harperdb-on-eks.md
+++ /dev/null
@@ -1,423 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/harperdb-on-eks-1bcb
-categories: aws, eks, harperdb, kubernetes
-date: 2023-01-09
-tags: aws, eks, harperdb, kubernetes
-title: HarperDB on EKS
----
-
-This post first appeared on [dev.to](https://dev.to/aws-builders/harperdb-on-eks-1bcb)
-
-Hi there :wave:, let's see how to deploy HarperDB on EKS, and then test it with an API call from CURL. You can get the Kubernetes manifests
-that we make in this post from this [link](https://github.com/networkandcode/harperdb-deployments/tree/main/kubernetes-manifests).
-
-Hope you are already familiar with topics such as [Deployment](https://youtu.be/udSPJXMU9L4?t=1094), [Load
-Balancer](https://www.youtube.com/watch?v=7o6koGCsoSc) service, [Secret](https://www.youtube.com/watch?v=iTkz1bIacHM) and [Persistent volume
-claim](https://www.youtube.com/watch?v=vqk0Ccd7sio)
-
-Ensure you have the required IAM permissions, have installed the aws, eksctl & kubectl cli tools, and have setup the config and credentials.
-
-For me the config is as follows.
-```
-$ cat ~/.aws/config
-[default]
-region=us-east-1
-```
-
-## Cluster
-We can now create an EKS cluster with eksctl. You may see this [video](https://www.youtube.com/watch?v=rJQb_whepEY) for cluster creation
-from the CLI.
-```
-$ eksctl create cluster --name eks-cluster --zones=us-east-1a,us-east-1b
-```
-
-This has taken around 20 mins for me. Once it's done we can update the kubeconfig.
-```
-$ aws eks update-kubeconfig --name eks-cluster
-```
-
-## Docker hub
-We can visit the docker [hub](https://hub.docker.com/r/harperdb/harperdb) page of harperdb to get an idea on the ports, environment
-variables, volume path etc.
-
-They have given an example docker command as below.
-```
-docker run -d \
- -v /host/directory:/opt/harperdb/hdb \
- -e HDB_ADMIN_USERNAME=HDB_ADMIN \
- -e HDB_ADMIN_PASSWORD=password \
- -p 9925:9925 \
- harperdb/harperdb
-```
-
-This tells us the volume mount path in the container is /opt/harperdb/hdb, there are 2 environment variables for username and password, and
-the container port is 9925. Finally the image is harperdb/harperdb.
-
-We now have enough info to start writing our Kubernetes manifests.
-
-## Kubernetes manifests
-I am going to create a directory by name harperdb where I would keep all the manifests.
-```
-$ mkdir harperdb
-$ cd harperdb
-```
-
-Let's begin with the environment variables, we can write both username and password in a secret object.
-```
-$ cat < secret.yaml
----
-apiVersion: v1
-kind: Secret
-metadata:
- name: harperdb
- namespace: harperdb
-stringData:
- HDB_ADMIN_USERNAME: admin
- HDB_ADMIN_PASSWORD: password12345
-...
-EOF
-```
-
-We can now go with a persistent volume claim, that can dynamically create an EBS volume of size 5Gi in AWS.
-```
-$ cat < pvc.yaml
----
-apiVersion: v1
-kind: PersistentVolumeClaim
-metadata:
- name: harperdb
- namespace: harperdb
-spec:
- accessModes:
- - ReadWriteOnce
- resources:
- requests:
- storage: 5Gi
-...
-EOF
-```
-
-Then comes the deployment manifest, where we can define the container image, refer to the secret for the env vars, and pvc for the volume.
-Note that the volume mount path matches with that in the docker command.
-```
-$ cat < deploy.yaml
----
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: harperdb
- namespace: harperdb
-spec:
- selector:
- matchLabels:
- app: harperdb
- template:
- metadata:
- labels:
- app: harperdb
- spec:
- containers:
- - name: harperdb
- image: harperdb/harperdb
- envFrom:
- - secretRef:
- name: harperdb
- volumeMounts:
- - name: data
- mountPath: /opt/harperdb/hdb
- volumes:
- - name: data
- persistentVolumeClaim:
- claimName: harperdb
-...
-EOF
-```
-
-Finally, we have to expose the deployment with a service, we know from the docker command that the container port is 9925.
-```
-$ cat < svc.yaml
----
-apiVersion: v1
-kind: Service
-metadata:
- name: harperdb
- namespace: harperdb
-spec:
- selector:
- app: harperdb
- type: LoadBalancer
- ports:
- - name: http
- port: 8080
- targetPort: 9925
-...
-EOF
-```
-Note that we have used 8080 as the service port.
-
-## Workloads
-
-Create a namespace by name harperdb, where we can create our objects.
-```
-$ kubectl create ns harperdb
-namespace/harperdb created
-```
-
-We are good to create objects with the 4 manifests.
-```
-$ ls
-deploy.yaml pvc.yaml secret.yaml svc.yaml
-
-$ kubectl create -f .
-deployment.apps/harperdb created
-persistentvolumeclaim/harperdb created
-secret/harperdb created
-service/harperdb created
-```
-
-## Fix PVC
-The pvc should be in pending status.
-```
-$ kubectl get pvc
-NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE
-harperdb Pending gp2 7m3s
-```
-
-Please follow this [link](https://aws.amazon.com/premiumsupport/knowledge-center/eks-persistent-storage/) to add IAM role in AWS cloud, and
-ebs csi objects on the cluster. This should fix the PVC issue.
-
-Once done, the pvc should be bound to a persistent volume(pv).
-```
-$ kubectl get pvc -n harperdb
-NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE
-harperdb Bound pvc-7c83e38c-b00a-4194-8c67-ba5c9c1118e7 5Gi RWO gp2 9s
-```
-
-And the pv should be mapped to an EBS volume.
-```
-$ kubectl get pv
-NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON
-AGE
-pvc-7c83e38c-b00a-4194-8c67-ba5c9c1118e7 5Gi RWO Delete Bound harperdb/harperdb gp2
-64s
-
-$ kubectl describe pv pvc-7c83e38c-b00a-4194-8c67-ba5c9c1118e7 | grep VolumeID
- VolumeID: vol-0bbca736346f02aa1
-```
-
-Note that a persistent volume is a cluster level object and not bound to a namespace. We can check the volume details from the aws cli.
-```
-$ aws ec2 describe-volumes --volume-ids vol-0bbca736346f02aa1 --query "Volumes[0].Size"
-5
-
-$ aws ec2 describe-volumes --volume-ids vol-0bbca736346f02aa1 --query "Volumes[0].Tags"
-[
- {
- "Key": "ebs.csi.aws.com/cluster",
- "Value": "true"
- },
- {
- "Key": "CSIVolumeName",
- "Value": "pvc-7c83e38c-b00a-4194-8c67-ba5c9c1118e7"
- },
- {
- "Key": "kubernetes.io/created-for/pv/name",
- "Value": "pvc-7c83e38c-b00a-4194-8c67-ba5c9c1118e7"
- },
- {
- "Key": "kubernetes.io/created-for/pvc/namespace",
- "Value": "harperdb"
- },
- {
- "Key": "kubernetes.io/created-for/pvc/name",
- "Value": "harperdb"
- }
-]
-```
-
-## Volume permission fix
-
-So the pvc seems good. Let's check our application status.
-```
-$ kubectl get po -n harperdb
-NAME READY STATUS RESTARTS AGE
-harperdb-79694c8b75-6ckn7 0/1 CrashLoopBackOff 4 (80s ago) 3m25s
-```
-
-The application was crashing, but the volume was getting mounted, and the env vars were fine too. I tried commenting out volumeMounts and
-volume and updated the deployment.
-```
-$ cat deploy.yaml | grep #
- #volumeMounts:
- #- name: data
- #mountPath: /opt/harperdb/hdb
- #volumes:
- #- name: data
- #persistentVolumeClaim:
- #claimName: harperdb
-
-$ kubectl apply -f deploy.yaml
-```
-
-The pod was running, and I checked the permissions of the directory where we need to mount the volume. And subsequently the id of the group.
-```
-$ kubectl exec -it deploy/harperdb -n harperdb -- bash
-
-ubuntu@harperdb-858cc7967d-5jcqm:~$ ls -l /opt/harperdb
-total 0
-drwxr-xr-x 11 ubuntu ubuntu 155 Jan 9 06:59 hdb
-
-ubuntu@harperdb-858cc7967d-5jcqm:~$ id
-uid=1000(ubuntu) gid=1000(ubuntu) groups=1000(ubuntu)
-
-ubuntu@harperdb-858cc7967d-5jcqm:~$ exit
-```
-
-So the group id of the running user is 1000, hence we can set this as the group owner for the volume directory with the fsGroup option. If
-we don't specify this then the mountPath would by default be set with root(user) and root(group) as the owner for the directory and the
-running user ubuntu wouldn't have permissions on the mountPath to create any new files. This
-[video](https://www.youtube.com/watch?v=PzzFsvadZdY) has information about fsGroup.
-
-We have to change the deployment as follows. We have added the security context with the fsGroup.
-```
-$ cat deploy.yaml
----
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: harperdb
- namespace: harperdb
-spec:
- selector:
- matchLabels:
- app: harperdb
- template:
- metadata:
- labels:
- app: harperdb
- spec:
- securityContext:
- fsGroup: 1000
- containers:
- - name: harperdb
- image: harperdb/harperdb
- envFrom:
- - secretRef:
- name: harperdb
- volumeMounts:
- - name: data
- mountPath: /opt/harperdb/hdb
- volumes:
- - name: data
- persistentVolumeClaim:
- claimName: harperdb
-...
-```
-
-Alternately, we could also set mountPath to just /opt/harperdb, where we wouldn't have to set the securityContext. But I thought this is a
-good use case to know about the fsGroup.
-
-Update the deployment.
-```
-$ kubectl apply -f deploy.yaml
-```
-
-Check the workloads.
-```
-$ kubectl get all -n harperdb
-NAME READY STATUS RESTARTS AGE
-pod/harperdb-cc4f49dfc-m7d5p 1/1 Running 0 55s
-
-NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
-AGE
-service/harperdb LoadBalancer 10.100.54.78 a0ba701c9c5a4463bb636551c79b4158-169592876.us-east-1.elb.amazonaws.com 8080:31819/TCP
-55s
-
-NAME READY UP-TO-DATE AVAILABLE AGE
-deployment.apps/harperdb 1/1 1 1 57s
-
-NAME DESIRED CURRENT READY AGE
-replicaset.apps/harperdb-cc4f49dfc 1 1 1 57s
-```
-
-## API call
-
-Send a CURL command to test schema creation. The endpoint is from the external IP column in the service. You may check this
-[video](https://www.youtube.com/watch?v=25L8VvXgx8w) to know how to obtain the curl command for harperdb.
-```
-$ HDB_API_ENDPOINT=http://a0ba701c9c5a4463bb636551c79b4158-169592876.us-east-1.elb.amazonaws.com:8080
-
-$ curl --location --request POST ${HDB_API_ENDPOINT} \
---header 'Content-Type: application/json' \
---header 'Authorization: Basic YWRtaW46cGFzc3dvcmQxMjM0NQ==' \
---data-raw '{
- "operation": "create_schema",
- "schema": "qa"
-}'
-
-{"message":"schema 'qa' successfully created"}
-```
-
-All good, it's working...
-
-## Persistence
-
-Test persistence by deleting the pod.
-```
-$ kubectl delete po -n harperdb -l app=harperdb
-pod "harperdb-cc4f49dfc-m7d5p" deleted
-```
-
-This should launch a new pod.
-```
-$ kubectl get po -n harperdb
-NAME READY STATUS RESTARTS AGE
-harperdb-cc4f49dfc-c6vnc 1/1 Running 0 57s
-```
-
-We can try sending the same API call again.
-```
-$ curl --location --request POST ${HDB_API_ENDPOINT} \
---header 'Content-Type: application/json' \
---header 'Authorization: Basic YWRtaW46cGFzc3dvcmQxMjM0NQ==' \
---data-raw '{
- "operation": "create_schema",
- "schema": "qa"
-}'
-
-{"error":"Schema 'qa' already exists"}
-```
-
-It's not creating a new schema, because the existing schema is restored from the attached volume. Hence, it's persistent.
-
-## Clean up
-
-Let's do the clean up...
-
-Delete all the objects that were created via manifests.
-```
-$ kubectl delete -f .
-deployment.apps "harperdb" deleted
-persistentvolumeclaim "harperdb" deleted
-secret "harperdb" deleted
-service "harperdb" deleted
-```
-
-Then delete the namespace.
-```
-$ kubectl delete ns harperdb
-namespace "harperdb" deleted
-```
-
-Delete the folder.
-```
-$ cd ..
-$ rm -rf harperdb
-```
-
-Finally delete the cluster.
-```
-$ eksctl delete cluster --name eks-cluster
-```
-
-That's it for the post, Thank you for reading !!!
diff --git a/_posts/2023-01-13-harperdb-with-helm-on-eks.md b/_posts/2023-01-13-harperdb-with-helm-on-eks.md
deleted file mode 100644
index cf3cace..0000000
--- a/_posts/2023-01-13-harperdb-with-helm-on-eks.md
+++ /dev/null
@@ -1,211 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/harperdb-with-helm-on-eks-3fb9
-categories: aws, harperdb, helm, kubernetes
-date: 2023-01-13
-tags: aws, harperdb, helm, kubernetes
-title: HarperDB with Helm on EKS
----
-
-This post first appeared on [dev.to](https://dev.to/aws-builders/harperdb-with-helm-on-eks-3fb9)
-
-This post builds on top of [this](https://dev.to/aws-builders/harperdb-on-eks-1bcb) where we discussed how to launch HarperDB on EKS with
-kubectl. Here, we would use those same manifests. But, we would go with the helm cli tool instead of kubectl for the deployment. Please
-check this [link](https://github.com/networkandcode/harperdb-deployments/tree/main/helm-charts/minimal/harperdb) for the final chart we make
-in this post.
-
-Get set go :fire:
-
-First, ensure [helm](https://dev.to/aws-builders/harperdb-on-eks-1bcb) is installed. If you want to use AWS cloud shell for this, please
-click on the shell icon on the top navigation bar of the cloud console, and execute the following.
-```
-$ curl -fsSL -o get_helm.sh https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3
-$ chmod 700 get_helm.sh
-$ sudo yum install openssl -y
-$ ./get_helm.sh
-```
-
-Ensure the kubeconfig is updated.
-```
-$ aws eks update-kubeconfig --name k8s-cluster-01
-```
-
-Pl. change the cluster name above with what you have created.
-
-Let's just create the namespace with kubectl, rest will be created with helm.
-```
-$ kubectl create ns harperdb
-namespace/harperdb created
-```
-
-Create a directory for the helm chart.
-```
-$ mkdir harperdb
-$ cd harperdb
-```
-
-Create a directory for templates in the chart.
-```
-$ mkdir templates
-```
-
-Copy the manifests from this [post](https://dev.to/aws-builders/harperdb-on-eks-1bcb) and keep it in the templates directory.
-```
-$ ls templates/
-deploy.yaml pvc.yaml secret.yaml svc.yaml
-```
-
-Create the chart file where we would just keep the name and version, we are keeping to hold just the mandatory information, though we can
-add more.
-```
-$ cat < Chart.yaml
-name: harperdb
-version: 1.0.0
-EOF
-```
-
-So what we created so far is our harperdb helm chart, we are staring with chart version 1.0.0.
-
-We can use this to install the release in a separate namespace. The namespace below means the helm release namespace and not the kubernetes
-namespace. And `.` refers to the chart directory which is the current directory.
-```
-$ helm install harperdb . -n harperdb
-NAME: harperdb
-LAST DEPLOYED: Fri Jan 13 09:52:08 2023
-NAMESPACE: harperdb
-STATUS: deployed
-REVISION: 1
-TEST SUITE: None
-```
-
-We are using the same name for both the helm and kubernetes namespaces. Note that the kubernetes namespace is mentioned in all of the
-manifests.
-```
-$ cat templates/deploy.yaml | grep namespace
- namespace: harperdb
-```
-
-The helm release is deployed.
-```
-$ helm list -n harperdb
-NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
-harperdb harperdb 1 2023-01-13 09:52:08.953758683 +0000 UTC deployed harperdb-1.0.0
-```
-
-This has deployed the workloads in kubernetes, which we can check with kubectl.
-```
-$ kubectl get deploy,pvc,secret,svc -n harperdb
-NAME READY UP-TO-DATE AVAILABLE AGE
-deployment.apps/harperdb 1/1 1 1 5m11s
-
-NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE
-persistentvolumeclaim/harperdb Bound pvc-6ef558ee-86ad-460d-8379-c34a12aaf283 5Gi RWO gp2 5m11s
-
-NAME TYPE DATA AGE
-secret/default-token-llbqm kubernetes.io/service-account-token 3 3h50m
-secret/harperdb Opaque 2 5m11s
-secret/sh.helm.release.v1.harperdb.v1 helm.sh/release.v1 1 5m11s
-
-NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
-AGE
-service/harperdb LoadBalancer 10.100.29.79 a86501cc7a7024fff92b7212cd844e45-1677629392.us-east-1.elb.amazonaws.com 8080:31549/TCP
-5m11s
-```
-
-Let's test with an API call. The endpoint refers to the loadbalancer service.
-```
-$ HDB_API_ENDPOINT=a86501cc7a7024fff92b7212cd844e45-1677629392.us-east-1.elb.amazonaws.com:8080
-
-$ curl --location --request POST ${HDB_API_ENDPOINT} --header 'Content-Type: application/json' --header 'Authorization: Basic
-YWRtaW46cGFzc3dvcmQxMjM0NQ==' --data-raw '{
- "operation": "create_schema",
- "schema": "uat"
-}'
-{"message":"schema 'uat' successfully created"}
-```
-Awesome, works !!!.
-
-Let's now revisit the helm chart and do a couple changes. For now, we haven't used any values file, which is commonly used with any helm
-chart. We need values when we would like to parameterize certain things in our manifests. For instance, let's say we want to parameterize
-the service port.
-```
-$ cat < values.yaml
-servicePort: 8080
-EOF
-```
-
-We can the change the port section in the service template to refer to the value from values file.
-```
-$ cat templates/svc.yaml | grep port
- ports:
- port: {{ .Values.servicePort }}
-```
-
-Let's call this chart version 2.0.0 and upgrade our release.
-```
-$ cat Chart.yaml | grep version
-version: 2.0.0
-
-$ helm upgrade harperdb . -n harperdb
-Release "harperdb" has been upgraded. Happy Helming!
-NAME: harperdb
-LAST DEPLOYED: Fri Jan 13 12:35:53 2023
-NAMESPACE: harperdb
-STATUS: deployed
-REVISION: 2
-TEST SUITE: None
-```
-
-We can verify the service port.
-```
-$ kubectl get svc harperdb -n harperdb -o jsonpath={.spec.ports[0].port}
-8080
-```
-
-Let's do another change, this time we would try to refer to the release name and namespace as the name and namespace for each of the
-resources.
-```
-$ grep -ir .Release templates/
-templates/pvc.yaml: name: {{ .Release.Name }}
-templates/pvc.yaml: namespace: {{ .Release.Namespace }}
-templates/svc.yaml: name: {{ .Release.Name }}
-templates/svc.yaml: namespace: {{ .Release.Namespace }}
-templates/deploy.yaml: name: {{ .Release.Name }}
-templates/deploy.yaml: namespace: {{ .Release.Namespace }}
-templates/secret.yaml: name: {{ .Release.Name }}
-templates/secret.yaml: namespace: {{ .Release.Namespace }}
-```
-Note you have to modify each file, so that the grep output looks like above.
-
-Let's change the chart version to 3.0.0, and upgrade the release.
-```
-$ cat Chart.yaml
-name: harperdb
-version: 3.0.0
-
-$ helm upgrade harperdb . -n harperdb
-```
-
-We can validate.
-```
-$ kubectl get deploy,pvc,secret,svc -n harperdb | awk '{print $1}'
-NAME
-deployment.apps/harperdb
-
-NAME
-persistentvolumeclaim/harperdb
-
-NAME
-secret/default-token-llbqm
-secret/harperdb
-secret/sh.helm.release.v1.harperdb.v1
-
-NAME
-service/harperdb
-```
-
-You could see the workload details on the EKS page. Here is a sample screenshot.
-
-
-
-All good, so we have reached the end of this post, we saw how to install harperdb with a minimal helm chart, tested it with an API call, and
-tweaked the helm chart a bit to understand some fundamentals of it. Thank you for reading !!!.
diff --git a/_posts/2023-01-18-harperdb-with-anthos-on-gke.md b/_posts/2023-01-18-harperdb-with-anthos-on-gke.md
deleted file mode 100644
index 8a1b314..0000000
--- a/_posts/2023-01-18-harperdb-with-anthos-on-gke.md
+++ /dev/null
@@ -1,156 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/harperdb-with-anthos-on-gke-2nef
-categories: anthos, gke, harperdb, kubernetes
-date: 2023-01-18
-tags: anthos, gke, harperdb, kubernetes
-title: HarperDB with Anthos on GKE
----
-
-This post first appeared on [dev.to](https://dev.to/networkandcode/harperdb-with-anthos-on-gke-2nef)
-
-## Introduction
-[Anthos](https://cloud.google.com/anthos) is a service from Google cloud using which we can deploy and manage workloads using various
-options such as cloud run, GKE, self managed clusters, hybrid cloud clusters, edge based workloads and so on. In this post, we would focus
-on the autopilot GKE based cluster and deploy [HarperDB](https://harperdb.io) on it with a Helm chart. Please check this
-[link](https://github.com/networkandcode/harperdb-deployments/tree/main/helm-charts/minimal/harperdb) for the helm chart, we use in this
-post.
-
-Let's get started...
-
-## Enable Anthos
-Search for Anthos on the Google cloud console and enable the Anthos API.
-
-
-## GKE
-We would be going with an Anthos managed GKE cluster, so click on the configure option in the auto pilot option.
-
-
-I have kept all options to their defaults. Wait for the cluster to get created. The notifications link should show the status of creation.
-
-
-We should now have a GKE cluster by name autopilot-cluster-1.
-![Notification for cluster creation completed]
-(https://dev-to-uploads.s3.amazonaws.com/uploads/articles/2h66wwysiu3al2u44ync.png)
-
-Refresh the page to see the cluster.
-
-
-## Register
-We have created the GKE cluster via Anthos, however we also need to register it. Click register and go back to the clusters page, the
-cluster should show under Anthos managed clusters.
-
-
-We can now use the GKE cluster to launch any applications in the usual way with kubectl or helm.
-
-## Kubeconfig
-Go the cloud shell and run the following command to update kubeconfig.
-```
-$ gcloud container clusters get-credentials autopilot-cluster-1 --region us-central1
-Fetching cluster endpoint and auth data.
-kubeconfig entry generated for autopilot-cluster-1.
-```
-
-Both kubectl and helm would use this kubeconfig to interact with the cluster.
-
-## Namespace
-Let's create a namespace with kubectl.
-```
-$ kubectl create ns harperdb
-namespace/harperdb created
-```
-
-## Helm
-We can deploy the Kubernetes objects with Helm, for which let's check if there is any publicly available helm chart for harperdb chart in
-the artifact hub.
-```
-$ helm search hub harperdb
-No results found
-```
-
-We don't have a chart yet on the hub. Hence, I would be using a local minimal helm chart, whose files are as follows.
-```
-$ ls harperdb -tR
-harperdb:
-templates Chart.yaml values.yaml
-
-harperdb/templates:
-svc.yaml deploy.yaml pvc.yaml secret.yaml
-```
-
-For more info on the contents of files in this chart, pl. checkout this [post](https://dev.to/aws-builders/harperdb-with-helm-on-eks-3fb9).
-
-Alright, so let's install our helm release on the GKE cluster managed by Anthos.
-```
-$ helm install harperdb . -n harperdb
-W0114 05:34:47.808566 817 warnings.go:70] Autopilot set default resource requests for Deployment harperdb/harperdb, as resource requests
-were not specified. See http://g.co/gke/autopilot-defaults
-NAME: harperdb
-LAST DEPLOYED: Sat Jan 14 05:34:39 2023
-NAMESPACE: harperdb
-STATUS: deployed
-REVISION: 1
-TEST SUITE: None
-```
-
-## Resources
-Though we have not setup any resource requests in the deployment template, the autopilot cluster had enabled it for us. We can check the
-deployment spec to see what they have set. Note that it's a good practice to mention resource requests and limits in the template.
-```
-$ kubectl get deploy harperdb -n harperdb -o jsonpath={.spec.template.spec.containers[].resources} | jq
-{
- "limits": {
- "cpu": "500m",
- "ephemeral-storage": "1Gi",
- "memory": "2Gi"
- },
- "requests": {
- "cpu": "500m",
- "ephemeral-storage": "1Gi",
- "memory": "2Gi"
- }
-}
-```
-
-## Pod
-Check the pod status.
-```
-$ kubectl get po -n harperdb
-NAME READY STATUS RESTARTS AGE
-harperdb-559d48f4f7-6dftw 1/1 Running 0 6m9s
-```
-
-## API test
-The pod is running, we can get the service IP and try sending an API call.
-```
-$ HDB_API_ENDPOINT_IP=$(kubectl get svc harperdb -n harperdb -o jsonpath={.status.loadBalancer.ingress[0].ip})
-
-$ curl --location --request POST http://${HDB_API_ENDPOINT_IP}:8080 --header 'Content-Type: application/json' --header 'Authorization: Basic
-YWRtaW46cGFzc3dvcmQxMjM0NQ==' --data-raw '{
- "operation": "create_schema",
- "schema": "prod"
-}'
-{"message":"schema 'prod' successfully created"}
-```
-
-So our installation went smooth and it's working.
-
-## Clean up
-The clean up involves four steps. Deleting the helm chart directory from cloudshell `rm -rf harperdb`.
-
-Unregistering the cluster from the Anthos console.
-
-
-Delete the cluster from the GKE console.
-
-
-Finally disable the Anthos API.
-```
-$ gcloud services disable anthos.googleapis.com
-Warning: Disabling this service will also automatically disable any running Anthos clusters.
-
-Do you want to continue (y/N)? y
-```
-
-## Summary
-So we have seen how to create an autopilot cluster from the Anthos console, installed a helm release for HarperDB on it, and tested it with
-a sample schema creation. Thank you for reading !!!
diff --git a/_posts/2023-02-03-harperdb-helm-chart-on-artifact-hub.md b/_posts/2023-02-03-harperdb-helm-chart-on-artifact-hub.md
deleted file mode 100644
index 044943c..0000000
--- a/_posts/2023-02-03-harperdb-helm-chart-on-artifact-hub.md
+++ /dev/null
@@ -1,564 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/harperdb-helm-chart-on-artifact-hub-3066
-categories: eks, harperdb, helm, kubernetes
-date: 2023-02-03
-tags: eks, harperdb, helm, kubernetes
-title: HarperDB Helm chart on Artifact Hub
----
-
-This post first appeared on [dev.to](https://dev.to/networkandcode/harperdb-helm-chart-on-artifact-hub-3066)
-
-## Introduction
-Hey :wave:, in this post, we shall see how to create a helm chart for HarperDB based on the boilerplate helm chart with the helm cli,
-lint/dry run it and push it to the artifact [hub](https://artifacthub.io), and then reuse it to install a helm release on a Kubernetes
-cluster. You can get the helm chart used in this post from this
-[link](https://github.com/networkandcode/harperdb-deployments/tree/main/helm-charts/standard/harperdb).
-
-You may check this [post](https://dev.to/aws-builders/harperdb-with-helm-on-eks-3fb9) if you are looking to install harperdb with a custom,
-minimal helm chart.
-
-## Search
-As of this writing, there is no chart available on artifact hub for harperdb, the screenshot below should validate that.
-
-
-So our goal is to push the harpderdb chart to artifact hub, so that the search result shows an entry.
-
-Let's give a try on ChatGPT.
-
-
-We could also search from the helm cli, to see if there exists a chart for harperdb. For which you have to first install
-[helm](https://helm.sh/docs/intro/install/) in your system.
-
-On Mac, it could be installed as follows.
-```
-$ brew install helm
-```
-
-Now, we can search for the chart.
-```
-$ helm search hub harperdb
-No results found
-```
-
-This result matches with the search we did on website.
-
-## Chart
-Ok, we can create our chart. Let's first create a boilerplate chart with the name harperdb.
-```
-$ helm create harperdb
-Creating harperdb
-```
-
-A chart is created for us, it's nothing but a directory with a specific layout.
-```
-$ ls -R harperdb
-Chart.yaml charts templates values.yaml
-
-harperdb/charts:
-
-harperdb/templates:
-NOTES.txt deployment.yaml ingress.yaml serviceaccount.yaml
-_helpers.tpl hpa.yaml service.yaml tests
-
-harperdb/templates/tests:
-test-connection.yaml
-```
-
-Let's make a few changes.
-
-Change the appVersion, I am going to use the latest version of harperdb found in the [tags](https://hub.docker.com/r/harperdb/harperdb/tags)
-section at docker hub.
-```
-$ cat harperdb/Chart.yaml| grep appVersion
-appVersion: "1.16.0"
-
-$ sed -i 's/appVersion: "1.16.0"/appVersion: "4.0.4"/g' harperdb/Chart.yaml
-
-$ cat harperdb/Chart.yaml| grep appVersion
-appVersion: "4.0.4"
-```
-
-We don't need any sub charts for now, so we can remove that directory.
-```
-$ rm -r harperdb/charts
-```
-
-We can also remove the tests directory.
-```
-$ rm -r harperdb/templates/tests
-```
-
-## Values
-We need to make a few modifications in the values file.
-
-### Image
-Let's set the image.
-```
-$ cat harperdb/templates/deployment.yaml | grep image:
- image: "{{ .Values.image.repository }}:{{ .Values.image.tag | default .Chart.AppVersion }}"
-```
-
-The tag can come from the appVersion, we just need to set the image repository in values. By default, it would have nginx.
-```
-$ grep repository: harperdb/values.yaml
- repository: nginx
-```
-
-Edit values by replacing nginx with harperdb/harperdb.
-```
-$ sed -i 's#repository: nginx#repository: harperdb/harperdb#g' harperdb/values.yaml
-
-$ grep repository: harperdb/values.yaml
- repository: harperdb/harperdb
-```
-
-### Service
-HarperDB uses the port 9925 for the rest API, we would be exposing only this here, though there are other ports like 9926, 9932 for custom
-functions, clustering etc.
-
-In our chart they are setting the service port in `.Values.service.port` and the same port is used as port the container port too, we can
-stick with that for simplicity.
-```
-$ grep -ir service.port harperdb
-harperdb/templates/NOTES.txt: echo http://$SERVICE_IP:{{ .Values.service.port }}
-harperdb/templates/ingress.yaml:{{- $svcPort := .Values.service.port -}}
-harperdb/templates/service.yaml: - port: {{ .Values.service.port }}
-harperdb/templates/deployment.yaml: containerPort: {{ .Values.service.port }}
-```
-
-Let' change the service port in values.
-```
-$ grep port: harperdb/values.yaml
- port: 80
-
-$ sed -i 's/port: 80/port: 9925/g' harperdb/values.yaml
-
-$ grep port: harperdb/values.yaml
- port: 9925
-```
-
-Also set the service type to LoadBlancer
-```
-
-$ sed -i 's/type: ClusterIP/type: LoadBalancer/g' harperdb/values.yaml
-
-$ cat harperdb/values.yaml
---TRUNCATED--
-service:
- type: LoadBalancer
- port: 9925
---TRUNCATED
-```
-
-### Security context
-Modify the pod security context, you may check this [post](https://dev.to/aws-builders/harperdb-on-eks-1bcb) to know why we used 1000 as the
-fsGroup.
-```
-$ grep -i -A 2 podSecurityContext harperdb/values.yaml
-podSecurityContext:
- fsGroup: 1000
-```
-
-### Resources
-Similary set the cpu and memory requirements in values.
-```
-$ grep -A 6 resources harperdb/values.yaml
-resources:
- limits:
- cpu: 500m
- memory: 1Gi
- requests:
- cpu: 100m
- memory: 128Mi
-```
-
-## Secret
-The chart we created doesn't have a secret manifest, we can create it. This manifest follows standards similar to the service account
-manifest.
-```
-$ cat < harperdb/templates/secret.yaml
-{{- if .Values.secret.create }}
-apiVersion: v1
-kind: Secret
-metadata:
- name: {{ include "harperdb.secretName" . }}
- labels:
- {{- include "harperdb.labels" . | nindent 4 }}
-stringData:
- {{- toYaml .Values.secret.entries | nindent 2 }}
-{{- end }}
-EOF
-```
-
-We can set the appropriate values for the secret manifest.
-```
-$ cat <> harperdb/values.yaml
-
-secret:
- entries:
- HDB_ADMIN_USERNAME: admin
- HDB_ADMIN_PASSWORD: password12345
- create: true
- name: harperdb
-EOF
-```
-
-We can then modify the helpers file.
-```
-$ cat <> harperdb/templates/_helpers.tpl
-
-{{/*
-Create the name of the secret to use
-*/}}
-{{- define "harperdb.secretName" -}}
-{{- default "default" .Values.secret.name }}
-{{- end }}
-EOF
-```
-
-## PVC
-Likewise, there is no pvc template in the chart. So we can add that.
-```
-$ cat < harperdb/templates/pvc.yaml
-{{- if .Values.pvc.create }}
-apiVersion: v1
-kind: PersistentVolumeClaim
-metadata:
- name: {{ include "harperdb.pvcName" . }}
- labels:
- {{- include "harperdb.labels" . | nindent 4 }}
-spec:
- accessModes:
- - {{ .Values.pvc.accessMode }}
- resources:
- requests:
- storage: {{ .Values.pvc.storage }}
-{{- end }}
-EOF
-```
-
-Set the appropriate values for pvc.
-```
-$ cat <> harperdb/values.yaml
-
-pvc:
- accessMode: ReadWriteOnce
- create: true
- mountPath: /opt/harperdb/hdb
- name: harperdb
- storage: 5Gi
-EOF
-```
-
-We can then modify the helpers file.
-```
-$ cat <> harperdb/templates/_helpers.tpl
-
-{{/*
-Create the name of the pvc to use
-*/}}
-{{- define "harperdb.pvcName" -}}
-{{- default "default" .Values.pvc.name }}
-{{- end }}
-EOF
-```
-
-## Deployment
-We are going to make a few changes to the deployment manifest. So that it looks like below.
-```
-$ cat < harperdb/templates/deployment.yaml
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: {{ include "harperdb.fullname" . }}
- labels:
- {{- include "harperdb.labels" . | nindent 4 }}
-spec:
- {{- if not .Values.autoscaling.enabled }}
- replicas: {{ .Values.replicaCount }}
- {{- end }}
- selector:
- matchLabels:
- {{- include "harperdb.selectorLabels" . | nindent 6 }}
- template:
- metadata:
- {{- with .Values.podAnnotations }}
- annotations:
- {{- toYaml . | nindent 8 }}
- {{- end }}
- labels:
- {{- include "harperdb.selectorLabels" . | nindent 8 }}
- spec:
- {{- with .Values.imagePullSecrets }}
- imagePullSecrets:
- {{- toYaml . | nindent 8 }}
- {{- end }}
- serviceAccountName: {{ include "harperdb.serviceAccountName" . }}
- securityContext:
- {{- toYaml .Values.podSecurityContext | nindent 8 }}
- {{- if .Values.pvc.create }}
- volumes:
- - name: data
- persistentVolumeClaim:
- claimName: {{ include "harperdb.pvcName" . }}
- {{- end }}
- containers:
- - name: {{ .Chart.Name }}
- {{- if .Values.pvc.create }}
- volumeMounts:
- - name: data
- mountPath: {{ .Values.pvc.mountPath }}
- {{- end }}
- {{- if .Values.secret.create }}
- envFrom:
- - secretRef:
- name: {{ include "harperdb.secretName" . }}
- {{- end }}
- securityContext:
- {{- toYaml .Values.securityContext | nindent 12 }}
- image: "{{ .Values.image.repository }}:{{ .Values.image.tag | default .Chart.AppVersion }}"
- imagePullPolicy: {{ .Values.image.pullPolicy }}
- ports:
- - name: http
- containerPort: {{ .Values.service.port }}
- protocol: TCP
- resources:
- {{- toYaml .Values.resources | nindent 12 }}
- {{- with .Values.nodeSelector }}
- nodeSelector:
- {{- toYaml . | nindent 8 }}
- {{- end }}
- {{- with .Values.affinity }}
- affinity:
- {{- toYaml . | nindent 8 }}
- {{- end }}
- {{- with .Values.tolerations }}
- tolerations:
- {{- toYaml . | nindent 8 }}
- {{- end }}
-EOF
-```
-
-In the template above, we have injected the secrets as env vars in the envFrom section of the container. And made changes related to the
-volume by defining the volume in the pod and mount it in the container.
-
-## Lint
-Our chart is kinda ready...
-
-Ok so now let's do the linting to see if it's proper.
-```
-$ helm lint harperdb
-==> Linting harperdb
-[INFO] Chart.yaml: icon is recommended
-
-1 chart(s) linted, 0 chart(s) failed
-```
-
-Seems good.
-
-We can now try generating the kubernetes manifests, it won't deploy yet. You can try `helm template harperdb` or `helm template harperdb
---debug`, the debug flag helps debugging issues.
-
-## Kubeconfig
-Make sure you have a running kubernetes cluster. I have an EKS cluster, and I would be using the [aws](https://aws.amazon.com/cli/) cli to
-update the kubeconfig.
-```
-$ aws eks update-kubeconfig --name k8s-cluster-01 --region us-east-1
-```
-
-There are two nodes in my cluster.
-```
-$ kubectl get nodes
-NAME STATUS ROLES AGE VERSION
-ip-192-168-22-158.ec2.internal Ready 24d v1.23.13-eks-fb459a0
-ip-192-168-38-226.ec2.internal Ready 24d v1.23.13-eks-fb459a0
-```
-
-Create a namespace with kubectl.
-```
-$ kubectl create ns harperdb
-```
-
-## Dry run
-As the cluster is ready we can try to do a dry run installation with helm.
-```
-$ helm install harperdb harperdb -n harperdb --dry-run --debug
-```
-
-If there are no errors, we can proceed to the packaging.
-
-## Package
-Our chart seems good so we can package it.
-```
-$ helm package harperdb
-```
-
-This should create a compressed file.
-```
-$ ls | grep tgz
-harperdb-0.1.0.tgz
-```
-
-Here 0.1.0 refers to the chart version.
-```
-$ cat harperdb/Chart.yaml | grep version:
-version: 0.1.0
-```
-
-## Repo
-We should need a repo where we can keep this package. I am using this [repo](https://github.com/networkandcode/networkandcode.github.io) for
-this purpose. And this repo is also setup with GitHub pages and the website is accessible on this [URL](https://networkandcode.github.io).
-So you may create a github repo with [pages](https://pages.github.com) setup.
-
-Alright I am cloning my repo.
-```
-git clone git@github.com:networkandcode/networkandcode.github.io.git
-```
-
-Create a directory there for helm packages.
-```
-$ cd networkandcode.github.io/
-$ mkdir helm-packages
-```
-
-We can move the package we created earlier in to this directory.
-```
-$ mv ~/harperdb-0.1.0.tgz helm-packages/
-
-$ ls helm-packages/
-harperdb-0.1.0.tgz
-```
-
-We need to now create an index file.
-```
-$ helm repo index helm-packages/
-
-$ ls helm-packages/
-harperdb-0.1.0.tgz index.yaml
-```
-
-The index file is populated automatically with these details.
-```
-$ cat helm-packages/index.yaml
-apiVersion: v1
-entries:
- harperdb:
- - apiVersion: v2
- appVersion: 4.0.1
- created: "2023-02-02T05:58:37.022518464Z"
- description: A Helm chart for Kubernetes
- digest: 1282e5919f2d6889f1e3dd849f27f2992d8288087502e1872ec736240dfd6ebf
- name: harperdb
- type: application
- urls:
- - harperdb-0.1.0.tgz
- version: 0.1.0
-generated: "2023-02-02T05:58:37.020383374Z"
-```
-
-You can also add the artifacthub repo [file](https://github.com/artifacthub/hub/blob/master/docs/metadata/artifacthub-repo.yml
-), to claim ownership, it's optional though.
-
-Ok we can now push the changes to GitHub, note that I am directly pushing to the master branch.
-```
-$ git add --all
-$ git commit -m 'add helm package for harperdb'
-
-$ git push
-```
-
-## Add repository
-Our repository is ready with the package, we need to add it to artifact hub. Login to artifact hub, and go to control panel and click add
-repository.
-
-
-
-The repository is added, but it takes some to process. You need to wait until there is a green tick in the Last processed section.
-
-## Search again
-Once the repo is processed, we can repeat the searching process we did while starting this post.
-
-
-
-Well, worth to know that ChatGPT's knowledge is cut off in 2021.
-
-
-Now let's do the cli way.
-```
-$ helm search hub harperdb --max-col-width 1000
-URL CHART VERSION APP VERSION DESCRIPTION
-https://artifacthub.io/packages/helm/networkandcode/harperdb 0.1.0 4.0.1 A Helm chart for Kubernetes
-```
-
-Wow our chart is showing up…
-
-## Install
-We can open the URL shown above and see the installation instructions.
-
-
-
-Let's run those commands, I am going to use -n for installing it in a separate namespace.
-```
-$ helm repo add networkandcode https://networkandcode.github.io/helm-packages
-"networkandcode" has been added to your repositories
-
-$ helm install my-harperdb networkandcode/harperdb --version 0.1.0 -n harperdb
-```
-
-## Validate
-Alright, so the release is installed, it's time to validate. First let's check the helm release status.
-```
-$ helm list -n harperdb
-NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
-my-harperdb harperdb 1 2023-02-02 07:14:59.586892384 +0000 UTC deployed harperdb-0.1.0 4.0.1
-```
-
-Check the Kubernetes workloads.
-```
-$ kubectl get all -n harperdb
-NAME READY STATUS RESTARTS AGE
-pod/my-harperdb-7b66d4f7c5-xtpvw 1/1 Running 0 2m7s
-
-NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
-AGE
-service/my-harperdb LoadBalancer 10.100.127.117 a6e762ccc1e2d482a8528a7760544761-2140283724.us-east-1.elb.amazonaws.com
-9925:30478/TCP 2m9s
-
-NAME READY UP-TO-DATE AVAILABLE AGE
-deployment.apps/my-harperdb 1/1 1 1 2m8s
-
-NAME DESIRED CURRENT READY AGE
-replicaset.apps/my-harperdb-7b66d4f7c5 1 1 1 2m9s
-```
-
-## API
-We can test schema creation with an API call.
-```
-$ HDB_API_ENDPOINT_HOSTNAME=$(kubectl get svc my-harperdb -n harperdb -o jsonpath={.status.loadBalancer.ingress[0].hostname})
-
-$ curl --location --request POST http://${HDB_API_ENDPOINT_HOSTNAME}:9925 --header 'Content-Type: application/json' --header 'Authorization:
-Basic YWRtaW46cGFzc3dvcmQxMjM0NQ==' --data-raw '{
- "operation": "create_schema",
- "schema": "my-schema"
-}'
-{"message":"schema 'my-schema' successfully created"}
-```
-Note that I have parsed the hostname as it gives a hostname for the external IP in EKS. Well, so the API call was successful. Nice, we were
-able to accomplish the goal !!!
-
-## Clean up
-I am going to just clean up the helm and Kubernetes objects.
-```
-$ helm uninstall my-harperdb -n harperdb
-release "my-harperdb" uninstalled
-
-$ kubectl delete ns harperdb
-namespace "harperdb" deleted
-```
-
-## Summary
-So we have seen some constructs of helm, and understood how we can make a chart for harperdb, push it to artifact hub and subsequently use
-it to install a harperdb release. Note that you can customise the chart with more options such as adding readme, enabling tests, claiming
-ownership for the chart, adding more harperdb specific variables w.r.t clustering, custom functions etc.
-
-Thank you for reading!!!
diff --git a/_posts/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md b/_posts/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
deleted file mode 100644
index c73ab5b..0000000
--- a/_posts/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
+++ /dev/null
@@ -1,614 +0,0 @@
----
-canonical_url: https://dev.to/networkandcode/query-harperdbs-rest-api-via-apollo-graphql-21n1
-date: 2023-02-17
-title: Query HarperDB's REST API via Apollo GraphQL
-categories: apolloserver, graphql, harperdb, rest
-cover_image: https://source.unsplash.com/featured/?coding
-tags: apolloserver, graphql, harperdb, rest
----
-
-**This post first appeared on [dev.to](https://dev.to/networkandcode/query-harperdbs-rest-api-via-apollo-graphql-21n1)
-## Introduction
-Hi there :wave:, in this post, we shall launch an Apollo server with node,
-and perform some read & write operations from the Apollo studio sandbox to
-a HarperDB instance. Having some graphql fundamentals would be beneficial
-to understand better, though some parts of the code would be explained.
-
-## Studio
-I have an account in HarperDB [studio](https://studio.harperdb.io) and
-have setup an organisation and a free trier instance there. Once logged in
-to the instance, the config tab would give the instance credentials we
-would need to connect from our code.
-
-
-
-Note that the studio credentials(email/password) are different from the
-instance credentials(username/password). You can have more than one
-instance in the studio. You can have only one free tier instance though
-across organisations.
-
-Copy the instance url and the basic token from the config shown in the
-image above, as we would need those while sending API calls.
-
-## Clone
-Clone the code from GitHub.
-```
-$ git clone git@github.com:networkandcode/fruits-apollo-hdb.git
-```
-
-## Dependencies
-The
-[dependencies](https://github.com/networkandcode/fruits-apollo-hdb/blob/main/server/package.json#L13-L18)
-for the code are as follows.
-```
- "dependencies": {
- "@apollo/datasource-rest": "^5.0.2",
- "@apollo/server": "^4.3.3",
- "dotenv": "^16.0.3",
- "graphql": "^16.6.0"
- }
-```
-
-We can install these.
-```
-$ npm i
-```
-
-About the packages above:
-- `@apollo/datasource-rest` is used to make rest api calls from apollo to
-endpoints such as HarperDB's instance url.
-- `@apollo/server` is used to launch the apollo server itself.
-- `dotenv` is used to read env vars.
-- `graphql` is the core graphql library.
-
-You may refer to this
-[guide](https://www.apollographql.com/docs/apollo-server/getting-started/#step-2-install-dependencies)
-for more info.
-
-## Variable
-Add an `.env` file, we just need one variable.
-```
-$ cat .env
-HDB_INSTANCE_URL=https://.harperdbcloud.com
-```
-
-## Start
-There is a start script with invokes the index file.
-```
-$ cat package.json| grep start
- "start": "node index.js"
-```
-
-Good to start the server
-```
-$ npm start
-
-> server@1.0.0 start
-> node index.js
-
-🚀 Server ready at: http://localhost:4000/
-```
-
-## Apollo studio
-Once the server is started we should be able to see the sandbox studio on
-the browser at http://localhost:4000/.
-
-
-## Token
-Let's set the authorisation header, you may paste the basic token obtained
-from HarperDB studio here.
-
-
-We are setting this
-[token](https://github.com/networkandcode/fruits-apollo-hdb/blob/main/server/index.js#L20)
-in the server context.
-```
- const token = req.headers.authorization;
-```
-
-Which would be
-[passed](https://github.com/networkandcode/fruits-apollo-hdb/blob/main/server/datasource.js#L46-L48)
-to HarperDB while the REST API call is being made.
-```
- willSendRequest(_path, request) {
- request.headers['authorization'] = this.token;
- };
-```
-
-## Code
-Let's see what code files we have and their purpose.
-```
-$ ls *.js
-datasource.js index.js resolvers.js schema.js
-```
-- `datasource.js` is where we are making calls to HarperDB via REST API.
-- `index.js` has code that wraps the schema and resolvers in the server
-and starts it.
-- `resolvers.js` contains resolvers that resolves all of the queries and
-mutations defined in `schema.js` by sending calls to HarperDB API defined
-in `datasource.js`
-- `schema.js` contains our graphql schema that has built in types Query
-and Mutation as well as other user defined types and inputs.
-
-
-### Schema
-Our graphql
-[schema](https://www.apollographql.com/docs/apollo-server/schema/schema/)
-is a collection of type definitions. And hence it's common to use typeDefs
-as our schema variable.
-```
-$ cat schema.js
-const typeDefs = `
- input CreateTableBody {
- schema: String!
- table: String!
- hash_attribute: String!
- }
-
- input FruitInput {
- name: String!
- "calories per 100 gm"
- calories: Int!
- }
-
- type Query {
- fruits(schema: String!, table: String!): [Fruit]
- fruit(schema: String!, table: String!, name: String!): [Fruit]
- }
-
- type Mutation {
- createSchema(schema: String!): ApiResponse!
- createTable(body: CreateTableBody!): ApiResponse!
- insertRecords(schema: String!, table: String!, records: [FruitInput!]!
-): ApiResponse!
- }
-
- type Fruit {
- id: ID!
- name: String!
- calories: Int!
- }
-
- type ApiResponse {
- status: Int!
- message: String!
- }
-`;
-
-export default typeDefs;
-```
-
-In the schema, there are two built in types Query and Mutation. Query is
-meant for read operations where as Mutation refers to operations that
-involve create, update or deletion of data.
-
-In Query, we have defined two fields fruits and fruit. `fruits` takes two
-arguments schema and table, both are strings and are mandatory or non
-nullable as denoted with `!`. Both fruits and fruit fields return same
-type of data denoted by [Fruit], this indicates an array of records, where
-each record is of type Fruit, this is not a built in type like String or
-Int, hence we have defined it as type Fruit. The type definition for Fruit
-denotes it’s structure, it would have three fields id, name and calories
-which are of types ID, String and Int respectively, and all 3 fields are
-non nullable. To summarise, we can have two Query operations one is fruits
-and the other is fruit both return a list of fruits(records from
-HarperDB).
-
-Like wise for Mutation, we have three fields createSchema, createTable and
-insertRecords with their respective arguments, and all of them would
-return the same type of response as denoted by ApiResponse, that would
-have only 2 fields status and message.
-
-Note that when a field type is not built in, we would define it with type,
-like we have defined type `Fruit` and type `ApiResponse` in our schema.
-Likewise, when an argument type is not built in, we would delete it with
-input, like we have defined input `CreateTableBody` and `FruitInput` in
-our schema.
-
-### Datasource
-Here, we create a new class by name HdpApi that inherits from
-RESTDataSource. Note that we obtain the baseURL from the env var.
-
-The willSendRequest function is used to add the header while calls are
-being sent to the base url. There are just two functions we are defining
-here, as in HarperDB all the calls are of type
-[POST](https://api.harperdb.io), and there mainly two types of calls, one
-that sends SQL style statements and the other which they call as NoSQL
-operations.
-
-```
-$ cat datasource.js
-import { RESTDataSource } from '@apollo/datasource-rest';
-
-class HdbApi extends RESTDataSource {
- baseURL = process.env.HDB_INSTANCE_URL;
-
- constructor(options) {
- super(options);
- this.token = options.token;
- };
-
- async sqlQuery(body) {
- // for read operations
- return await this.post(
- '',
- {
- body,
- }
- ).then((res) => {
- return res;
- })
- };
-
- async noSqlQuery(body) {
- return await this.post(
- '',
- {
- body,
- }
- ).then((res) => {
- const { message } = res;
- return {
- status: 200,
- message
- }
- }).catch((err) => {
- const { status, body } = err.extensions.response;
- const message = body.error;
-
- return {
- status,
- message
- }
- });
- };
-
- willSendRequest(_path, request) {
- request.headers['authorization'] = this.token;
- };
-
- };
-
- export default HdbApi;
-```
-
-### Index
-In the index file, we import the modules first. And then, we import the
-schema, resolvers and our datasource. We use dotenv to read the var
-defines in `.env`.
-
-We then create an Apollo server instance that takes two arguments: schema
-and resolvers.
-
-We start the server finally, and we give options such as the listening
-port, and the context.
-
-```
-$ cat index.js
-import { ApolloServer } from '@apollo/server';
-import { startStandaloneServer } from '@apollo/server/standalone';
-import dotenv from 'dotenv';
-
-import typeDefs from './schema.js';
-import resolvers from './resolvers.js';
-import HdbApi from './datasource.js';
-
-dotenv.config();
-console.log(process.env)
-
-const server = new ApolloServer({
- typeDefs,
- resolvers,
-});
-
-const { url } = await startStandaloneServer(server, {
- listen: { port: 4000 },
- context: async({ req }) => {
- const { cache } = server;
- const token = req.headers.authorization;
- return {
- dataSources: {
- hdbApi: new HdbApi({ cache, token }),
- }
- }
- }
-});
-
-console.log(`🚀 Server ready at: ${url}`);
-```
-
-The context returns a dataSources dictionary that has a hdpApi key in it,
-and this points to a new HdpApi object which is defined in the datasource.
-
-We can refer to this context in the resolvers.
-
-### Resolvers
-There are 2 main resolvers for the built in types Query and Mutation.
-Inside each resolver, we have a function for each field inside the type.
-In our schema we have defines two types fruits and fruit, hence there are
-two such functions inside the Query resolver too. Similarly we have three
-functions for the Mutations: createSchema, createTable and insertRecords.
-
-What these functions return will come as the result in the Apollo Studio
-for our GraphQL operation. The return statements are referring to
-contextValue which is the context function we defined in index. So, the
-resolvers are able to use the context defined in the server, which
-subsequently points to the api calls we defined in the datasource.
-
-Note that there are four
-[arguments](https://www.apollographql.com/docs/apollo-server/data/resolvers/#resolver-arguments)
-for each function: parent, args, contextValue and info. We would only need
-the 2nd and 3rd args for this exercise though. We have already seen about
-`contextValue` above, and `args` refer to the variables we set while
-running an operation in the Apollo studio.
-```
-$ cat resolvers.js
-const resolvers = {
- Query: {
- fruits: (_, args, contextValue) => {
- const { schema, table } = args;
- const body = {
- "operation": "sql",
- "sql": `SELECT * FROM ${schema}.${table}`,
- }
-
- return contextValue.dataSources.hdbApi.sqlQuery(body);
- },
- fruit: (_, args, contextValue) => {
- const { schema, table, name } = args;
- const body = {
- "operation": "sql",
- "sql": `SELECT * FROM ${schema}.${table} where name = "${name}"`
- };
-
- return contextValue.dataSources.hdbApi.sqlQuery(body);
- },
- },
- Mutation: {
- // There are four args parent, args, contextValue and info
- createSchema: (_, { schema }, contextValue) => {
- const body = {
- operation: "create_schema",
- schema,
- };
-
- return contextValue.dataSources.hdbApi.noSqlQuery(body);
- },
- createTable: (parent, { body }, contextValue, info) => {
- body = {
- ...body,
- operation: "create_table",
- }
-
- return contextValue.dataSources.hdbApi.noSqlQuery(body);
- },
- insertRecords: (parent, { schema, table, records }, contextValue,
-info) => {
- const body = {
- operation: "insert",
- schema,
- table,
- records
- }
-
- return contextValue.dataSources.hdbApi.noSqlQuery(body);
- }
- }
- };
-
- export default resolvers;
-```
-
-### Operations
-Ok so all the setup is done. We are good to go with the Query / Mutation
-operations. Let's start with Mutations.
-
-## Create schema
-Let's try creating a schema in HarperDB with the mutation in Apollo
-GraphQl. Make a note that this schema is not the GraphQL schema, it's the
-schema in HarperDB.
-
-
-Building the operation and variables is easy, you just need to click on
-the plus sign next to the operation and field.
-
-We can validate this in the browse section of HarperDB studio.
-
-
-If we try to run the mutation again on Apollo studio, we should see an
-error message that says the schema already exists.
-
-
-## Create table
-The schema is created, we can now try to add a table in this schema.
-
-
-The operation is ready however we need to fill the data for the body
-variable, for which we can click on the argument.
-
-
-We should be able to see all the input data fields defined for the
-argument. We can add them all with the plus button.
-
-
-The variable should be populated for us with null fields.
-
-
-We can replace null with the actual values.
-
-
-We can run the operation and see the response.
-
-
-If you try again, you should see an error message.
-
-
-## Add entries to table
-The operation in this case would be:
-```
-mutation Mutation($schema: String!, $table: String!, $records:
-[FruitInput!]!) {
- insertRecords(schema: $schema, table: $table, records: $records) {
- message
- status
- }
-}
-```
-
-The variables would be:
-```
- "schema": "myschema",
- "table": "fruits",
- "records": [
- {
- "name": "Apple",
- "calories": 52
- },
- {
- "name": "Banana",
- "calories": 89
- }
- ]
-}
-```
-
-And the response as follows, after running the mutation:
-```
-{
- "data": {
- "insertRecords": {
- "message": "inserted 2 of 2 records",
- "status": 200
- }
- }
-}
-```
-
-## Retrieve records
-Let's try a query operation this time, for retrieving all records from the
-table.
-
-The operation is:
-```
-query Fruits($schema: String!, $table: String!) {
- fruits(schema: $schema, table: $table) {
- calories
- id
- name
- }
-}
-```
-
-The variables are:
-```
-{
- "schema": "myschema",
- "table": "fruits"
-}
-```
-
-And the result of the query operation would be:
-```
-{
- "data": {
- "fruits": [
- {
- "calories": 52,
- "id": "3963a29c-d696-44ae-a3d8-e11de48bf339",
- "name": "Apple"
- },
- {
- "calories": 89,
- "id": "eec06bc5-85cf-48eb-87d2-89a25fd9f3c1",
- "name": "Banana"
- }
- ]
- }
-}
-```
-
-## Retrieve selective records
-And one final query to retrieve selective records.
-The query is:
-```
-query Query($schema: String!, $table: String!, $name: String!) {
- fruit(schema: $schema, table: $table, name: $name) {
- calories
- id
- name
- }
-}
-```
-
-Variables:
-```
-{
- "schema": "myschema",
- "table": "fruits",
- "name": "Apple"
-}
-```
-
-And result of the query:
-```
-{
- "data": {
- "fruit": [
- {
- "calories": 52,
- "id": "3963a29c-d696-44ae-a3d8-e11de48bf339",
- "name": "Apple"
- }
- ]
- }
-}
-```
-
-## Summary
-Thus we were able to access the Apollo studio on the browser and send
-queries and mutations to HarperDB. HarperDB is considering GraphQL
-functionality on their roadmap. Check out their [Feedback
-Board](https://feedback.harperdb.io/) and give it an upvote if you think
-it would be helpful!
-
-Feel free to ask questions if the flow is not clear, and correct if there
-are any mistakes. Thank you for reading !!!
-
-Image credit: [unsplash](https://source.unsplash.com/featured/?coding)
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/_posts/2024-04-26/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md b/_posts/2024-04-26/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
deleted file mode 100644
index 7fe97d6..0000000
--- a/_posts/2024-04-26/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
+++ /dev/null
@@ -1,218 +0,0 @@
----
-canonical_url: https://dev.to/aws-builders/tracing-demo-with-aws-x-ray-and-grafana-1pb5
-date: 2024-04-26
-title: OTEL Tracing demo with AWS X-Ray and Grafana
-categories: aws, grafana, otel, xray
-cover_image: https://source.unsplash.com/featured?trace
-tags: aws, grafana, kubernetes, otel
----
-
-**This post first appeared on [dev.to](https://dev.to/aws-builders/tracing-demo-with-aws-x-ray-and-grafana-1pb5)**
-
-## Introduction
-Hello :wave:, In this post we'll see about sending traces from a demo app to AWS X-Ray via the ADOT(AWS Distro for OpenTelemetry) collector. We would then visualize this on Grafana. Note that we'd deploy the workloads on a kubernetes cluster.
-
-Here is a picture of what we are trying to accomplish:
-
-
-Alright, let's get started!!!
-
-## Namespace
-We shall deploy the workloads on a separate namespace. Let's create one.
-```
-kubectl create ns adot-traces-demo
-```
-
-## Credentials
-Store the AWS credentials as a kubernetes secret.
-```
-kubectl create secret generic aws-credentials \
- --from-literal=AWS_ACCESS_KEY_ID= \
- --from-literal=AWS_SECRET_ACCESS_KEY= \
- -n adot-traces-demo
-```
-
-## ADOT Config
-Set the ADOT config in a file.
-```
-$ cat adot-config.yaml
-exporters:
- awsxray:
- region: ap-south-2
-receivers:
- otlp:
- protocols:
- grpc:
- endpoint: 0.0.0.0:4317
-service:
- pipelines:
- traces:
- exporters:
- - awsxray
- receivers:
- - otlp
-```
-
-And create a config map with this file.
-```
-kubectl create configmap adot-config --from-file=adot-config.yaml -n adot-traces-demo
-```
-
-## ADOT Deployment
-Setup deployment spec in a file, that injects the secret we created earlier as environment variables and the configmap as a volume.
-```
-$ cat adot-deploy.yaml
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- labels:
- app: adot-collector
- name: adot-collector
-spec:
- replicas: 1
- selector:
- matchLabels:
- app: adot-collector
- template:
- metadata:
- labels:
- app: adot-collector
- spec:
- containers:
- - args:
- - '--config=/etc/adot-config.yaml'
- envFrom:
- - secretRef:
- name: aws-credentials
- image: public.ecr.aws/aws-observability/aws-otel-collector:latest
- name: adot-collector
- volumeMounts:
- - mountPath: /etc/adot-config.yaml
- name: config-volume
- subPath: adot-config.yaml
- volumes:
- - configMap:
- name: adot-config
- name: config-volume
-```
-
-Create the deployment.
-```
-kubectl create -f adot-deploy.yaml -n adot-traces-demo
-```
-
-The pod in the deployment should be running.
-```
-$ kubectl get po -n adot-traces-demo
-NAME READY STATUS RESTARTS AGE
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 3m26s
-```
-
-## ADOT Service
-We can expose the ADOT deployment with a service spec that exposes the grpc port 4317 as follows.
-```
-$ cat adot-svc.yaml
-apiVersion: v1
-kind: Service
-metadata:
- name: adot-collector-service
-spec:
- selector:
- app: adot-collector
- ports:
- - protocol: TCP
- port: 4317
- targetPort: 4317
-```
-
-We can now create the service.
-```
-kubectl create -f adot-svc.yaml -n adot-traces-demo
-```
-
-The endpoint IP should match with the pod IP.
-```
-$ kubectl get ep -n adot-traces-demo
-NAME ENDPOINTS AGE
-adot-collector-service 10.1.3.187:4317 22s
-
-$ kubectl get po -n adot-traces-demo -o wide
-NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 7m11s 10.1.3.187 docker-desktop
-```
-
-## Demo app
-We can now deploy the sample demo app which can send traces to ADOT collector, with the following manifest.
-```
-$ cat k6-tracing-deploy.yaml
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: xk6-tracing
-spec:
- replicas: 1
- selector:
- matchLabels:
- app: xk6-tracing
- template:
- metadata:
- labels:
- app: xk6-tracing
- spec:
- containers:
- - env:
- - name: ENDPOINT
- value: adot-collector-service:4317
- image: ghcr.io/grafana/xk6-client-tracing:v0.0.2
- name: xk6-tracing
-```
-
-Let's create the deployment.
-```
-kubectl create -f k6-tracing-deploy.yaml -n adot-traces-demo
-```
-
-Both the ADOT collector and k6-tracing pods should now be running.
-```
-$ kubectl get po -n adot-traces-demo
-NAME READY STATUS RESTARTS AGE
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 14m
-xk6-tracing-69b48fcfd9-bjzbd 1/1 Running 0 24s
-```
-
-## X-Ray
-We can now headover to AWS X-Ray, in `ap-south-2` region that we mentioned in the adot-config.
-
-
-The nodes(services) shown in the screenshot belong to our demo application. We could filter for traces that passes through a particular service name for ex. article service, like below.
-
-
-If we click on a single trace we should be able to see a complete service map for that trace, that shows all the services that trace traverses.
-
-
-If we go a further down on this we should be able to see the details for segments/spans with in this trace.
-
-
-## Grafana
-So we far we were able to see the traces in AWS X-Ray, we can do a similar exercise on Grafana. I am using a Grafana Cloud Free subscription for this lab.
-
-Go to Connections, Add a new connection and search for X-Ray and install it.
-
-
-You can then go to datasources, add a new X-Ray datasource with the access key id, secret access key, and default region(I have chosen ap-south-2 which matches with adot config).
-
-
-
-All good, we can try adding a new panel, go to dashboards > new dashboard and a new visualization with table as panel type and a sample query for ex. `service(id(name: "article-service" ))`
-
-
-We can click on one of the traces we should take us to the explore view where we can see the node graph(service map)
-
-
-We should also see the trace explorer that shows the individual spans.
-
-
-Okay so we reached this far, that was some fun exploring traces on AWS and Grafana with Open Telemetry. Thank you for reading !!!
-
-## CleanUp
-Just delete the namespace with `kubectl delete ns adot-traces-demo` and it should remove the workloads we deployed from kubernetes and stop sending any new data to the cloud.
diff --git a/_posts/aws/2021-10-16-aws-eks-setup-cluster-and-deploy-owasp-juice-shop.md b/_posts/aws/2021-10-16-aws-eks-setup-cluster-and-deploy-owasp-juice-shop.md
index 7f8c82e..6fac08d 100644
--- a/_posts/aws/2021-10-16-aws-eks-setup-cluster-and-deploy-owasp-juice-shop.md
+++ b/_posts/aws/2021-10-16-aws-eks-setup-cluster-and-deploy-owasp-juice-shop.md
@@ -1,6 +1,6 @@
---
-categories: aws eks
-title: aws eks > setup cluster and deploy owasp juice shop
+categories: "aws eks"
+title: "aws eks > setup cluster and deploy owasp juice shop"
---
Let's setup an EKS cluster and then install the
diff --git a/_posts/aws/2021-11-14-aws-ec2-launch-instances-the-hard-way-with-cli.md b/_posts/aws/2021-11-14-aws-ec2-launch-instances-the-hard-way-with-cli.md
index 6033a5a..17ad8c9 100644
--- a/_posts/aws/2021-11-14-aws-ec2-launch-instances-the-hard-way-with-cli.md
+++ b/_posts/aws/2021-11-14-aws-ec2-launch-instances-the-hard-way-with-cli.md
@@ -1,6 +1,6 @@
---
-categories: aws ec2
-title: aws ec2 > launch instances the hard way with cli
+categories: "aws ec2"
+title: "aws ec2 > launch instances the hard way with cli"
---
Hey All :wave:, in this post we shall launch 3 AWS EC2 instances and test SSH connectivity to those...
diff --git a/_posts/aws/2021-12-05-aws-iam-setup-user-via-cli.md b/_posts/aws/2021-12-05-aws-iam-setup-user-via-cli.md
index 70f726c..8fd0c00 100644
--- a/_posts/aws/2021-12-05-aws-iam-setup-user-via-cli.md
+++ b/_posts/aws/2021-12-05-aws-iam-setup-user-via-cli.md
@@ -1,6 +1,6 @@
---
-title: aws iam > setup user via cli
-categories: aws
+title: "aws iam > setup user via cli"
+categories: "aws"
---
Hey all, :wave: we shall see the following in this post: :scroll:
diff --git a/_posts/kubernetes/.2021-08-14-kubernetes-build-a-private-docker-registry.md b/_posts/kubernetes/.2021-08-14-kubernetes-build-a-private-docker-registry.md
index 09c17ec..e33eec5 100644
--- a/_posts/kubernetes/.2021-08-14-kubernetes-build-a-private-docker-registry.md
+++ b/_posts/kubernetes/.2021-08-14-kubernetes-build-a-private-docker-registry.md
@@ -1,6 +1,6 @@
---
-#title: kubernetes > build a private docker registry
-#categories: kubernetes
+#title: "kubernetes > build a private docker registry"
+#categories: "kubernetes"
---
Let's see how we can build our own private docker registry as a kubernetes workload. You need
diff --git a/_posts/kubernetes/2020-08-17-kubernetes-set-user-and-group-with-security-context.md b/_posts/kubernetes/2020-08-17-kubernetes-set-user-and-group-with-security-context.md
index 2def04e..0d6ab9b 100644
--- a/_posts/kubernetes/2020-08-17-kubernetes-set-user-and-group-with-security-context.md
+++ b/_posts/kubernetes/2020-08-17-kubernetes-set-user-and-group-with-security-context.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > set user and group with security context
-categories: kubernetes
+title: "kubernetes > set user and group with security context"
+categories: "kubernetes"
---
We are going to enhance security in a running container with the use of security context, by setting the user and group for running processes and filesystem in the container.
diff --git a/_posts/kubernetes/2021-03-18-kubernetes-retrieve-container-image-inventory.md b/_posts/kubernetes/2021-03-18-kubernetes-retrieve-container-image-inventory.md
index fe75914..bd66205 100644
--- a/_posts/kubernetes/2021-03-18-kubernetes-retrieve-container-image-inventory.md
+++ b/_posts/kubernetes/2021-03-18-kubernetes-retrieve-container-image-inventory.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > retrieve container image inventory
-categories: kubernetes
+title: "kubernetes > retrieve container image inventory"
+categories: "kubernetes"
---
We would be using kubectl and then write some Python code to retrieve the list of images of containers
running in a GKE Kubernetes cluster. Some familiarity with YAML, Python, Kubectl and fundamentals of
diff --git a/_posts/kubernetes/2021-08-07-kubernetes-launch-a-cluster-with-kind.md b/_posts/kubernetes/2021-08-07-kubernetes-launch-a-cluster-with-kind.md
index cd0da0a..03f4788 100644
--- a/_posts/kubernetes/2021-08-07-kubernetes-launch-a-cluster-with-kind.md
+++ b/_posts/kubernetes/2021-08-07-kubernetes-launch-a-cluster-with-kind.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > launch a cluster with kind
-categories: kind
+title: "kubernetes > launch a cluster with kind"
+categories: "kind"
---
We can launch a cluster easily with kind on our Linux system. Lets see how to do it.
diff --git a/_posts/kubernetes/2021-08-07-owasp-juice-shop-run-as-pod.md b/_posts/kubernetes/2021-08-07-owasp-juice-shop-run-as-pod.md
index b6dd78c..86d52c9 100644
--- a/_posts/kubernetes/2021-08-07-owasp-juice-shop-run-as-pod.md
+++ b/_posts/kubernetes/2021-08-07-owasp-juice-shop-run-as-pod.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > run as pod
-categories: owasp juice shop
+title: "owasp juice shop > run as pod"
+categories: "owasp juice shop"
---
In this post, we will see h
diff --git a/_posts/kubernetes/2021-08-15-kubernetes-bootstrap-a-cluster-with-rke.md b/_posts/kubernetes/2021-08-15-kubernetes-bootstrap-a-cluster-with-rke.md
index 3eb2029..235a220 100644
--- a/_posts/kubernetes/2021-08-15-kubernetes-bootstrap-a-cluster-with-rke.md
+++ b/_posts/kubernetes/2021-08-15-kubernetes-bootstrap-a-cluster-with-rke.md
@@ -1,7 +1,7 @@
---
-title: kubernetes > bootstrap a cluster with rke
-categories: kubernetes
-...
+title: "kubernetes > bootstrap a cluster with rke"
+categories: "kubernetes"
+---
Rancher Kubernetes Engine ( RKE ) is a popular tool using which we can bootstrap kubernetes clusters
quickly. We are going to excatly see that in this post. Please ensure kubectl is installed in your
diff --git a/_posts/kubernetes/2021-11-29-kubernetes-prerequisites-for-kubeadm-cluster-in-aws.md b/_posts/kubernetes/2021-11-29-kubernetes-prerequisites-for-kubeadm-cluster-in-aws.md
index 68e5ea4..00b4da9 100644
--- a/_posts/kubernetes/2021-11-29-kubernetes-prerequisites-for-kubeadm-cluster-in-aws.md
+++ b/_posts/kubernetes/2021-11-29-kubernetes-prerequisites-for-kubeadm-cluster-in-aws.md
@@ -1,6 +1,6 @@
---
-categories: kubernetes
-title: kubernetes > prerequisites for kubeadm cluster in aws
+categories: "kubernetes"
+title: "kubernetes > prerequisites for kubeadm cluster in aws"
---
[kubeadm](https://kubernetes.io/docs/setup/production-environment/tools/kubeadm/install-kubeadm/) is one of the popular tools used for bootstrapping kubernetes, here we would be setting up the [prerequisites](https://theithollow.com/2020/01/13/deploy-kubernetes-on-aws/) on AWS that are essential before launching the cluster.
diff --git a/2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md b/_posts/kubernetes/2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md
similarity index 99%
rename from 2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md
rename to _posts/kubernetes/2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md
index a21ad7a..baed320 100644
--- a/2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md
+++ b/_posts/kubernetes/2021-12-04-kubernetes-bootstrap-cluster-with-kubeadm.md
@@ -1,6 +1,6 @@
---
-#title: kubernetes > bootstrap cluster in aws with kubeadm
-#categories: kubernetes
+#title: "kubernetes > bootstrap cluster in aws with kubeadm"
+#categories: "kubernetes"
---
In this post, we would be installing the cluster in AWS with kubeadm, so please ensure the [prerequisites](\kubernetes-prerequisites-for-cluster-in-aws) are set.
diff --git a/_posts/kubernetes/access-control/2020-02-25-add-a-kubectl-user-with-token.md b/_posts/kubernetes/access-control/2020-02-25-add-a-kubectl-user-with-token.md
index 73ed397..22fdcbd 100644
--- a/_posts/kubernetes/access-control/2020-02-25-add-a-kubectl-user-with-token.md
+++ b/_posts/kubernetes/access-control/2020-02-25-add-a-kubectl-user-with-token.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > add a kubectl user with token
-categories: kubernetes
+title: "kubernetes > add a kubectl user with token"
+categories: "kubernetes"
---
We are going to see how to add an extra kubectl user.
diff --git a/_posts/kubernetes/access-control/2020-02-27-add-a-kubectl-user-with-tls.md b/_posts/kubernetes/access-control/2020-02-27-add-a-kubectl-user-with-tls.md
index 4a30754..1fbeb8e 100644
--- a/_posts/kubernetes/access-control/2020-02-27-add-a-kubectl-user-with-tls.md
+++ b/_posts/kubernetes/access-control/2020-02-27-add-a-kubectl-user-with-tls.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > add a user with tls
-categories: kubernetes
+title: "kubernetes > add a user with tls"
+categories: "kubernetes"
---
In this exercise we would add an extra user to kubeconfig, that uses TLS for authentication. Its good to have some
diff --git a/_posts/kubernetes/access-control/2020-03-08-rbac-with-rolebinding.md b/_posts/kubernetes/access-control/2020-03-08-rbac-with-rolebinding.md
index b6c2f0f..a633ab4 100644
--- a/_posts/kubernetes/access-control/2020-03-08-rbac-with-rolebinding.md
+++ b/_posts/kubernetes/access-control/2020-03-08-rbac-with-rolebinding.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > rbac with rolebinding
-categories: kubernetes
+title: "kubernetes > rbac with rolebinding"
+categories: "kubernetes"
---
RBAC(Role Based Access Control) is one of the authorization modes supported by the Kube api server. And in this post we would see
diff --git a/_posts/kubernetes/access-control/2020-03-14-rbac-with-clusterrolebinding.md b/_posts/kubernetes/access-control/2020-03-14-rbac-with-clusterrolebinding.md
index 4c64e05..56a6396 100644
--- a/_posts/kubernetes/access-control/2020-03-14-rbac-with-clusterrolebinding.md
+++ b/_posts/kubernetes/access-control/2020-03-14-rbac-with-clusterrolebinding.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > rbac with clusterrolebinding
-categories: kubernetes
+title: "kubernetes > rbac with clusterrolebinding"
+categories: "kubernetes"
---
A cluster role binding could be used to bind a user with a cluster role which is bound to a cluster irrespective of
diff --git a/_posts/kubernetes/access-control/2020-03-16-cluster-admin.md b/_posts/kubernetes/access-control/2020-03-16-cluster-admin.md
index 9df50c7..f4bc59f 100644
--- a/_posts/kubernetes/access-control/2020-03-16-cluster-admin.md
+++ b/_posts/kubernetes/access-control/2020-03-16-cluster-admin.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > about the cluster-admin cluster role binding
-categories: kubernetes
+title: "kubernetes > about the cluster-admin cluster role binding"
+categories: "kubernetes"
---
When a cluster is launched with kubeadm, the kubeconfig is set to use the default 'kubernetes-admin' user that has
diff --git a/_posts/kubernetes/components/2019-10-24-check-the-components-of-a-cluster.md b/_posts/kubernetes/components/2019-10-24-check-the-components-of-a-cluster.md
index fcc740c..f1365be 100644
--- a/_posts/kubernetes/components/2019-10-24-check-the-components-of-a-cluster.md
+++ b/_posts/kubernetes/components/2019-10-24-check-the-components-of-a-cluster.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > check the components of a cluster
-categories: kubernetes
+title: "kubernetes > check the components of a cluster"
+categories: "kubernetes"
---
We are going to see the installed components of a Kubernetes cluster
diff --git a/_posts/kubernetes/components/2019-10-24-etcd.md b/_posts/kubernetes/components/2019-10-24-etcd.md
index a8ff012..c43ab4f 100644
--- a/_posts/kubernetes/components/2019-10-24-etcd.md
+++ b/_posts/kubernetes/components/2019-10-24-etcd.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > etcd as a component in the cluster
-categories: kubernetes
+title: "kubernetes > etcd as a component in the cluster"
+categories: "kubernetes"
---
etcd is a consistent key value datastore that Kubernetes leverages to store the cluster configuration. However etcd is not a native Kubernetes component. ectd could be installed on separate dedicated instances or on master instances. In production, etcd is installed in HA (High Availability) mode i.e. etcd server is installed on more than instance. In HA, an etcd cluster is comprised of odd number of instances - 1, 3, 5 etc. however 5 is the recommended number of etcd instances for production environments
diff --git a/_posts/kubernetes/components/2019-12-21-add-an-extra-scheduler.md b/_posts/kubernetes/components/2019-12-21-add-an-extra-scheduler.md
index f5868fa..97bf350 100644
--- a/_posts/kubernetes/components/2019-12-21-add-an-extra-scheduler.md
+++ b/_posts/kubernetes/components/2019-12-21-add-an-extra-scheduler.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > add an extra scheduler
-categories: kubernetes
+title: "kubernetes > add an extra scheduler"
+categories: "kubernetes"
---
The kube-scheduler is responsible for scheduling Pods on Nodes, i.e. it would assign Pods to available Nodes, however it is not responsible for running the Pods, which is kubelet's job. A cluster needs to have atleast one scheduler, and its also possible to run multiple schedulers based on the need
diff --git a/_posts/kubernetes/components/2019-12-26-addStaticPodsUsingKubelet.md b/_posts/kubernetes/components/2019-12-26-addStaticPodsUsingKubelet.md
index d38dda7..7a24819 100644
--- a/_posts/kubernetes/components/2019-12-26-addStaticPodsUsingKubelet.md
+++ b/_posts/kubernetes/components/2019-12-26-addStaticPodsUsingKubelet.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > add static pods
-categories: kubernetes
+title: "kubernetes > add static pods"
+categories: "kubernetes"
---
We are going to see some information about Kubelet and how to add static Pods to a cluster. It is good to have some knowledge of the components of a Kubernetes cluster and some basics of services in Linux, for better understanding of this post.
diff --git a/_posts/kubernetes/components/2020-02-22-backup-and-restore-master.md b/_posts/kubernetes/components/2020-02-22-backup-and-restore-master.md
index 99d4684..ba81e7a 100644
--- a/_posts/kubernetes/components/2020-02-22-backup-and-restore-master.md
+++ b/_posts/kubernetes/components/2020-02-22-backup-and-restore-master.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > backup and restore the master
-categories: kubernetes
+title: "kubernetes > backup and restore the master"
+categories: "kubernetes"
---
This post covers information about how to backup and restore a Kubernetes master. The prerequisite is to have knowledge of launching a cluster using kubeadm.
diff --git a/_posts/kubernetes/components/2020-04-26-modify-kubelet-config.md b/_posts/kubernetes/components/2020-04-26-modify-kubelet-config.md
index bd9ca57..e19f58d 100644
--- a/_posts/kubernetes/components/2020-04-26-modify-kubelet-config.md
+++ b/_posts/kubernetes/components/2020-04-26-modify-kubelet-config.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > modify kubelet config
-categories: kubernetes
+title: "kubernetes > modify kubelet config"
+categories: "kubernetes"
---
We are going to see, some overview of kubelet and its config. The prerequisites are to have basic understanding of kubeadm, kubeconfig and jsonpath.
diff --git a/_posts/kubernetes/launch-cluster/2020-02-13-kubernetes-launch-a-cluster-gcloud-shell.markdown b/_posts/kubernetes/launch-cluster/2020-02-13-kubernetes-launch-a-cluster-gcloud-shell.markdown
index 3e3a362..7aaddd2 100644
--- a/_posts/kubernetes/launch-cluster/2020-02-13-kubernetes-launch-a-cluster-gcloud-shell.markdown
+++ b/_posts/kubernetes/launch-cluster/2020-02-13-kubernetes-launch-a-cluster-gcloud-shell.markdown
@@ -1,8 +1,8 @@
---
-layout: page
+layout: "page"
title: "kubernetes > launch a cluster with kubeadm and gcloud shell"
-date: 2020-02-13 07:56:00 +0530
-categories: kubernetes gcp
+date: "2020-02-13 07:56:00 +0530"
+categories: "kubernetes gcp"
---
Task: Create a Kubernetes cluster using VMs with kubeadm, not GKE
diff --git a/_posts/kubernetes/launch-cluster/2020-02-29-launch-micro-k8s-on-ubuntu.md b/_posts/kubernetes/launch-cluster/2020-02-29-launch-micro-k8s-on-ubuntu.md
index 2ac46c9..bdeeafb 100644
--- a/_posts/kubernetes/launch-cluster/2020-02-29-launch-micro-k8s-on-ubuntu.md
+++ b/_posts/kubernetes/launch-cluster/2020-02-29-launch-micro-k8s-on-ubuntu.md
@@ -1,77 +1,77 @@
---
-title: kubernetes > launch microk8s on ubuntu
-categories: kubernetes
+title: "kubernetes > launch microk8s on ubuntu"
+categories: "kubernetes"
...
MicroK8s is an all-in-one kubernetes deployment with all it's native services on a single machine
This exercise is carried out on Ubuntu 18.04
```
-root@microk8s:~# lsb_release -a
+root@microk8s: "~# lsb_release -a"
No LSB modules are available.
-Distributor ID: Ubuntu
-Description: Ubuntu 18.04.4 LTS
-Release: 18.04
-Codename: bionic
+Distributor ID: "Ubuntu"
+Description: "Ubuntu 18.04.4 LTS"
+Release: "18.04"
+Codename: "bionic"
```
Execute the following command to install microk8s on ubuntu
```
-root@microk8s:~# snap install microk8s --classic
-2020-02-29T11:53:47Z INFO Waiting for restart...
+root@microk8s: "~# snap install microk8s --classic"
+2020-02-29T11: "53:47Z INFO Waiting for restart..."
microk8s v1.17.3 from Canonical* installed
-root@microk8s:~#
+root@microk8s: "~#"
```
And that's it your all-in-one Kubernetes cluster is ready in a jiffy. You may start operating your Kubernetes cluster using kubectl, the only difference is that
you would have to use the microk8s prefix
```
-root@microk8s:~# microk8s.kubectl get nodes
+root@microk8s: "~# microk8s.kubectl get nodes"
NAME STATUS ROLES AGE VERSION
microk8s Ready 11s v1.17.3
-root@microk8s:~# microk8s.kubectl get pods
+root@microk8s: "~# microk8s.kubectl get pods"
No resources found in default namespace.
-root@microk8s:~# microk8s.kubectl cluster-info
-Kubernetes master is running at https://127.0.0.1:16443
+root@microk8s: "~# microk8s.kubectl cluster-info"
+Kubernetes master is running at https: "//127.0.0.1:16443"
To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.
```
The following command could be used to view the list of available addons and their status
```
-root@microk8s:~# microk8s.status
+root@microk8s: "~# microk8s.status"
microk8s is running
-addons:
-cilium: disabled
-dashboard: disabled
-dns: disabled
-fluentd: disabled
-gpu: disabled
-helm3: disabled
-helm: disabled
-ingress: disabled
-istio: disabled
-jaeger: disabled
-juju: disabled
-knative: disabled
-kubeflow: disabled
-linkerd: disabled
-metallb: disabled
-metrics-server: disabled
-prometheus: disabled
-rbac: disabled
-registry: disabled
-storage: disabled
+addons: ""
+cilium: "disabled"
+dashboard: "disabled"
+dns: "disabled"
+fluentd: "disabled"
+gpu: "disabled"
+helm3: "disabled"
+helm: "disabled"
+ingress: "disabled"
+istio: "disabled"
+jaeger: "disabled"
+juju: "disabled"
+knative: "disabled"
+kubeflow: "disabled"
+linkerd: "disabled"
+metallb: "disabled"
+metrics-server: "disabled"
+prometheus: "disabled"
+rbac: "disabled"
+registry: "disabled"
+storage: "disabled"
```
For instance we may enable prometheus now, as follows
```
-root@microk8s:~# microk8s.enable prometheus
+root@microk8s: "~# microk8s.enable prometheus"
--TRUNCATED--
-The Prometheus operator is enabled (user/pass: admin/admin)
+The Prometheus operator is enabled (user/pass: "admin/admin)"
```
--end-of-post--
diff --git a/_posts/kubernetes/miscellaneous/2020-02-22-notes-from-forum-2020-blr.markdown b/_posts/kubernetes/miscellaneous/2020-02-22-notes-from-forum-2020-blr.markdown
index 08c1a22..62fa05f 100644
--- a/_posts/kubernetes/miscellaneous/2020-02-22-notes-from-forum-2020-blr.markdown
+++ b/_posts/kubernetes/miscellaneous/2020-02-22-notes-from-forum-2020-blr.markdown
@@ -1,6 +1,6 @@
---
-title: kubernetes > notes from forum 2020 in bangalore, india
-categories: kubernetes
+title: "kubernetes > notes from forum 2020 in bangalore, india"
+categories: "kubernetes"
---
I had the privilege of getting sponsored by the company for attending the Kubernetes forum 2020 in Bangalore, India. I wanted
diff --git a/_posts/kubernetes/node-preference/2019-12-20-hard-node-affinity.md b/_posts/kubernetes/node-preference/2019-12-20-hard-node-affinity.md
index d8dc2ba..53814f4 100644
--- a/_posts/kubernetes/node-preference/2019-12-20-hard-node-affinity.md
+++ b/_posts/kubernetes/node-preference/2019-12-20-hard-node-affinity.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > configure hard node affinity
-categories: kubernetes
+title: "kubernetes > configure hard node affinity"
+categories: "kubernetes"
---
We are going to see how to specify hard requirements for Pod(s) to select a Node using ```spec.affinity.nodeAffinity.requiredDuringSchedulingIgnoredDuringExecution```. With this the Pods could be only launched on the Node(s) that matches with the configuration
diff --git a/_posts/kubernetes/node-preference/2019-12-20-soft-node-affinity.md b/_posts/kubernetes/node-preference/2019-12-20-soft-node-affinity.md
index efa21be..bb5cf70 100644
--- a/_posts/kubernetes/node-preference/2019-12-20-soft-node-affinity.md
+++ b/_posts/kubernetes/node-preference/2019-12-20-soft-node-affinity.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > configure soft node affinity
-categories: kubernetes
+title: "kubernetes > configure soft node affinity"
+categories: "kubernetes"
---
The Node Affinity feature we are going to see here helps the Pod(s) to prefer launching on Node(s) of choice, the associated section in the Pod manifest is ```spec.affinity.nodeAffinity.preferredDuringSchedulingIgnoredDuringExecution```
diff --git a/_posts/kubernetes/pod/2020-02-14-role-of-docker.md b/_posts/kubernetes/pod/2020-02-14-role-of-docker.md
index 272e813..2dcfc8e 100644
--- a/_posts/kubernetes/pod/2020-02-14-role-of-docker.md
+++ b/_posts/kubernetes/pod/2020-02-14-role-of-docker.md
@@ -1,6 +1,6 @@
---
-title: kubernetes > role of docker
-categories: kubernetes
+title: "kubernetes > role of docker"
+categories: "kubernetes"
---
The fundamental API object in kubernetes is a pod which contains one or more containers in it.
diff --git a/_posts/kubernetes/pod/container-probes.markdown b/_posts/kubernetes/pod/container-probes.markdown
index e54d3eb..e70e60d 100644
--- a/_posts/kubernetes/pod/container-probes.markdown
+++ b/_posts/kubernetes/pod/container-probes.markdown
@@ -1,6 +1,6 @@
---
-title: kubernetes > container probes
-categories: kubernetes
+title: "kubernetes > container probes"
+categories: "kubernetes"
---
Kubelets runnig on nodes, can periodically probe containers that are launched on those nodes, and ensure the app is running as it is intended to. In this post we are going to see 2 such standard probes used in production environments, namely liveness and readiness probes, and the standard HttpGetAction handler these probes use, to peform period health checks on web apps.
diff --git a/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-configmap-as-pod-volume.markdown b/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-configmap-as-pod-volume.markdown
index 7ef5b04..065f415 100644
--- a/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-configmap-as-pod-volume.markdown
+++ b/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-configmap-as-pod-volume.markdown
@@ -1,6 +1,6 @@
---
-title: kubernetes > attach config map as pod volume
-categories: kubernetes
+title: "kubernetes > attach config map as pod volume"
+categories: "kubernetes"
---
We could create Pod volumes based on Config Maps and mount those into containers. It's good to have some understanding of Config Maps and Volumes to make most use of this post.
diff --git a/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-secret-as-pod-volume.markdown b/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-secret-as-pod-volume.markdown
index 14ea1b8..d5b938b 100644
--- a/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-secret-as-pod-volume.markdown
+++ b/_posts/kubernetes/volumes/2020-02-05-kubernetes-attach-secret-as-pod-volume.markdown
@@ -1,8 +1,8 @@
---
-layout: page
+layout: "page"
title: "kubernetes > attach secret as pod volume"
-date: 2020-02-05
-categories: kubernetes
+date: "2020-02-05"
+categories: "kubernetes"
---
We could create Pod volumes based on Secrets and mount those into containers. It's good to have some understanding of Secrets and Volumes to make most use of this post.
diff --git a/_posts/otel/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md b/_posts/otel/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
deleted file mode 100644
index d4aeaaf..0000000
--- a/_posts/otel/2023-02-17-query-harperdbs-rest-api-via-apollo-graphql.md
+++ /dev/null
@@ -1,217 +0,0 @@
-
-
----
-canonical_url: https://dev.to/aws-builders/tracing-demo-with-aws-x-ray-and-grafana-1pb5
-date: 2024-04-26
-title: Tracing demo with AWS X-Ray and Grafana
-categories: aws, grafana, otel, xray
-cover_image: https://source.unsplash.com/featured?trace
-tags: aws, grafana, kubernetes, otel
----
-
-**This post first appeared on [dev.to](https://dev.to/aws-builders/tracing-demo-with-aws-x-ray-and-grafana-1pb5)**
-
-## Introduction
-Hello :wave:, In this post we'll see about sending traces from a demo app to AWS X-Ray via the ADOT(AWS Distro for OpenTelemetry) collector. We would then visualize this on Grafana. Note that we'd deploy the workloads on a kubernetes cluster.
-
-Here is a picture of what we are trying to accomplish:
-
-
-Alright, let's get started!!!
-
-## Namespace
-We shall deploy the workloads on a separate namespace. Let's create one.
-```
-kubectl create ns adot-traces-demo
-```
-
-## Credentials
-Store the AWS credentials as a kubernetes secret.
-```
-kubectl create secret generic aws-credentials \
- --from-literal=AWS_ACCESS_KEY_ID= \
- --from-literal=AWS_SECRET_ACCESS_KEY= \
- -n adot-traces-demo
-```
-
-## ADOT Config
-Set the ADOT config in a file.
-```
-$ cat adot-config.yaml
-exporters:
- awsxray:
- region: ap-south-2
-receivers:
- otlp:
- protocols:
- grpc:
- endpoint: 0.0.0.0:4317
-service:
- pipelines:
- traces:
- exporters:
- - awsxray
- receivers:
- - otlp
-```
-
-And create a config map with this file.
-```
-kubectl create configmap adot-config --from-file=adot-config.yaml -n adot-traces-demo
-```
-
-## ADOT Deployment
-Setup deployment spec in a file, that injects the secret we created earlier as environment variables and the configmap as a volume.
-```
-$ cat adot-deploy.yaml
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- labels:
- app: adot-collector
- name: adot-collector
-spec:
- replicas: 1
- selector:
- matchLabels:
- app: adot-collector
- template:
- metadata:
- labels:
- app: adot-collector
- spec:
- containers:
- - args:
- - '--config=/etc/adot-config.yaml'
- envFrom:
- - secretRef:
- name: aws-credentials
- image: public.ecr.aws/aws-observability/aws-otel-collector:latest
- name: adot-collector
- volumeMounts:
- - mountPath: /etc/adot-config.yaml
- name: config-volume
- subPath: adot-config.yaml
- volumes:
- - configMap:
- name: adot-config
- name: config-volume
-```
-
-Create the deployment.
-```
-kubectl create -f adot-deploy.yaml -n adot-traces-demo
-```
-
-The pod in the deployment should be running.
-```
-$ kubectl get po -n adot-traces-demo
-NAME READY STATUS RESTARTS AGE
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 3m26s
-```
-
-## ADOT Service
-We can expose the ADOT deployment with a service spec that exposes the grpc port 4317 as follows.
-```
-$ cat adot-svc.yaml
-apiVersion: v1
-kind: Service
-metadata:
- name: adot-collector-service
-spec:
- selector:
- app: adot-collector
- ports:
- - protocol: TCP
- port: 4317
- targetPort: 4317
-```
-
-We can now create the service.
-```
-kubectl create -f adot-svc.yaml -n adot-traces-demo
-```
-
-The endpoint IP should match with the pod IP.
-```
-$ kubectl get ep -n adot-traces-demo
-NAME ENDPOINTS AGE
-adot-collector-service 10.1.3.187:4317 22s
-
-$ kubectl get po -n adot-traces-demo -o wide
-NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 7m11s 10.1.3.187 docker-desktop
-```
-
-## Demo app
-We can now deploy the sample demo app which can send traces to ADOT collector, with the following manifest.
-```
-$ cat k6-tracing-deploy.yaml
-apiVersion: apps/v1
-kind: Deployment
-metadata:
- name: xk6-tracing
-spec:
- replicas: 1
- selector:
- matchLabels:
- app: xk6-tracing
- template:
- metadata:
- labels:
- app: xk6-tracing
- spec:
- containers:
- - env:
- - name: ENDPOINT
- value: adot-collector-service:4317
- image: ghcr.io/grafana/xk6-client-tracing:v0.0.2
- name: xk6-tracing
-```
-
-Let's create the deployment.
-```
-kubectl create -f k6-tracing-deploy.yaml -n adot-traces-demo
-```
-
-Both the ADOT collector and k6-tracing pods should now be running.
-```
-$ kubectl get po -n adot-traces-demo
-NAME READY STATUS RESTARTS AGE
-adot-collector-7cbf849b89-b4bkl 1/1 Running 0 14m
-xk6-tracing-69b48fcfd9-bjzbd 1/1 Running 0 24s
-```
-
-## X-Ray
-We can now headover to AWS X-Ray, in `ap-south-2` region that we mentioned in the adot-config.
-
-
-The nodes(services) shown in the screenshot belong to our demo application. We could filter for traces that passes through a particular service name for ex. article service, like below.
-
-
-If we click on a single trace we should be able to see a complete service map for that trace, that shows all the services that trace traverses.
-
-
-If we go a further down on this we should be able to see the details for segments/spans with in this trace.
-
-
-## Grafana
-So we far we were able to see the traces in AWS X-Ray, we can do a similar exercise on Grafana. I am using a Grafana Cloud Free subscription for this lab.
-
-Go to Connections, Add a new connection and search for X-Ray and install it.
-
-
-You can then go to datasources, add a new X-Ray datasource with the access key id, secret access key, and default region(I have chosen ap-south-2 which matches with adot config).
-
-
-
-All good, we can try adding a new panel, go to dashboards > new dashboard and a new visualization with table as panel type and a sample query for ex. `service(id(name: "article-service" ))`
-
-
-We can click on one of the traces we should take us to the explore view where we can see the node graph(service map)
-
-
-We should also see the trace explorer that shows the individual spans.
-
-
-Okay so we reached this far, that was some fun exploring traces on AWS and Grafana with Open Telemetry. Thank you for reading !!!
diff --git a/_posts/owaspjuiceshop/2021-07-08-owasp-juice-shop-scan-container-with-trivy.md b/_posts/owaspjuiceshop/2021-07-08-owasp-juice-shop-scan-container-with-trivy.md
index 8f6c758..ae14856 100644
--- a/_posts/owaspjuiceshop/2021-07-08-owasp-juice-shop-scan-container-with-trivy.md
+++ b/_posts/owaspjuiceshop/2021-07-08-owasp-juice-shop-scan-container-with-trivy.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > scan container with trivy
-categories: owasp juice shop
+title: "owasp juice shop > scan container with trivy"
+categories: "owasp juice shop"
---
In this post, we would be using an opensource container scanning tool called Trivy, developed by
diff --git a/_posts/owaspjuiceshop/2021-07-23-owasp-juice-shop-run-the-app-locally.md b/_posts/owaspjuiceshop/2021-07-23-owasp-juice-shop-run-the-app-locally.md
index 6c9536a..8839de5 100644
--- a/_posts/owaspjuiceshop/2021-07-23-owasp-juice-shop-run-the-app-locally.md
+++ b/_posts/owaspjuiceshop/2021-07-23-owasp-juice-shop-run-the-app-locally.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > run the app locally
-categories: owasp juice shop
+title: "owasp juice shop > run the app locally"
+categories: "owasp juice shop"
---
OWASP juice shop is an open source AngularJS application developed with known vulnerabilities
diff --git a/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-npm-audit.md b/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-npm-audit.md
index 1c1bc1a..dd76509 100644
--- a/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-npm-audit.md
+++ b/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-npm-audit.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > npm audit
-categories: owasp juice shop
+title: "owasp juice shop > npm audit"
+categories: "owasp juice shop"
---
In this post, we will audit the OWASP juice shop app with npm. You should have already cloned the juice
shop code and installed the modules with NPM. Some familiarity with jq for filtering json is assumed.
diff --git a/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-run-as-container.md b/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-run-as-container.md
index 999c998..7dcc368 100644
--- a/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-run-as-container.md
+++ b/_posts/owaspjuiceshop/2021-08-07-owasp-juice-shop-run-as-container.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > run as container
-categories: owasp juice shop
+title: "owasp juice shop > run as container"
+categories: "owasp juice shop"
---
Let's run the juice shop as a docker container on our local system, you should have already
diff --git a/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-launch-with-own-docker-image.md b/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-launch-with-own-docker-image.md
index 5e85c6c..f1828f0 100644
--- a/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-launch-with-own-docker-image.md
+++ b/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-launch-with-own-docker-image.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > launch with own docker image
-categories: owasp juice shop
+title: "owasp juice shop > launch with own docker image"
+categories: "owasp juice shop"
---
There is already an offical docker image for the juice shop application at the repo
diff --git a/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-run-as-kubernetes-service.md b/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-run-as-kubernetes-service.md
index 8585d12..292f174 100644
--- a/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-run-as-kubernetes-service.md
+++ b/_posts/owaspjuiceshop/2021-08-08-owasp-juice-shop-run-as-kubernetes-service.md
@@ -1,6 +1,6 @@
---
-title: owasp juice shop > run as kubernetes service
-categories: owasp juice shop
+title: "owasp juice shop > run as kubernetes service"
+categories: "owasp juice shop"
---
Hello, we shall run the OWASP juice shop as a deployment, and expose it as a service in a local
diff --git a/_posts/python/2020-05-02-python-lists-tuples-and-sets.md b/_posts/python/2020-05-02-python-lists-tuples-and-sets.md
index 575bd9a..63f7c35 100644
--- a/_posts/python/2020-05-02-python-lists-tuples-and-sets.md
+++ b/_posts/python/2020-05-02-python-lists-tuples-and-sets.md
@@ -1,6 +1,6 @@
---
-title: python > lists, tuples, and sets
-categories: python
+title: "python > lists, tuples, and sets"
+categories: "python"
---
A comparitive study of Lists, Tuples, and Sets should help in better understanding of these objects as they look kind
diff --git a/_posts/python/2020-06-14-python-string-methods.md b/_posts/python/2020-06-14-python-string-methods.md
index ca4e646..374d1b9 100644
--- a/_posts/python/2020-06-14-python-string-methods.md
+++ b/_posts/python/2020-06-14-python-string-methods.md
@@ -1,6 +1,6 @@
---
-title: python > string methods and functions
-categories: python
+title: "python > string methods and functions"
+categories: "python"
---
Strings are one of the most used datatypes, and some practice on string
diff --git a/_posts/python/2020-06-21-python-prepare-networking-configuration-with-jinja2-templates.md b/_posts/python/2020-06-21-python-prepare-networking-configuration-with-jinja2-templates.md
index 7e89210..eaddcce 100644
--- a/_posts/python/2020-06-21-python-prepare-networking-configuration-with-jinja2-templates.md
+++ b/_posts/python/2020-06-21-python-prepare-networking-configuration-with-jinja2-templates.md
@@ -1,6 +1,6 @@
---
-categories: python
-title: python > prepare networking configuration with jinja2 templates
+categories: "python"
+title: "python > prepare networking configuration with jinja2 templates"
---
### Topic
Jinja2 is a templating language used within Python, and we are going to
diff --git a/_posts/python/2020-06-22-python-functions-or-methods.md b/_posts/python/2020-06-22-python-functions-or-methods.md
index cce6006..8cfe9ff 100644
--- a/_posts/python/2020-06-22-python-functions-or-methods.md
+++ b/_posts/python/2020-06-22-python-functions-or-methods.md
@@ -1,6 +1,6 @@
---
-title: python > functions or methods
-categories: python
+title: "python > functions or methods"
+categories: "python"
---
### Topic
diff --git a/_posts/python/2020-06-23-python-define-network-configuration-in-yaml.md b/_posts/python/2020-06-23-python-define-network-configuration-in-yaml.md
index 5561906..1cc106c 100644
--- a/_posts/python/2020-06-23-python-define-network-configuration-in-yaml.md
+++ b/_posts/python/2020-06-23-python-define-network-configuration-in-yaml.md
@@ -1,5 +1,5 @@
---
-title: python > define network configuration in yaml
-categories: python
+title: "python > define network configuration in yaml"
+categories: "python"
---
diff --git a/_posts/python/2020-06-27-python-errors-and-exceptions.md b/_posts/python/2020-06-27-python-errors-and-exceptions.md
index f4b100c..575709d 100644
--- a/_posts/python/2020-06-27-python-errors-and-exceptions.md
+++ b/_posts/python/2020-06-27-python-errors-and-exceptions.md
@@ -1,324 +1,324 @@
----
-title: python > errors and exceptions
-categories: python
----
-
-A Python program can break due to various types of Errors. We shall explore few of these errors in the post. To make best use of this post, you should know certain topics in Python3 such as datatypes, expression, pass statement, etc.
-
-Not all errors are significant, and hence there would be cases where we can skip certain errors to uninterrupt execution of our code, and this is achieved with ```try except``` blocks.
-
-### ZeroDivisionError
-This error is returned when we try to divide any number by 0
-```
->>> 50 / 0
-Traceback (most recent call last):
- File "", line 1, in
-ZeroDivisionError: division by zero
-```
-This time we tell Python not to break execution, by including things in a ```try except``` block.
-```
->>> try:
-... 0 /0
-... except ZeroDivisionError:
-... pass
-...
-```
-The expression 00/0 in the try block should have produced a ZeroDivisionError, but since we are saying ```except ZeroDivisionError```, that error would be excepted. So there wont be any error and there should'nt be any output as well as we have included ```pass``` in the except block. Note that ```pass``` is used as a placeholder where you don't want the program to any program, and just to go the next line of the code in sequence if any.
-
-Let's try a different example, and also try printing some info instead of pass.
-```
->>> try:
-... 120 / 0
-... except:
-... print('oh there was an exception')
-...
-oh there was an exception
-```
-
-### TypeError
-We can try to do an unsupported math operation, for example division, between a string and an integer, to trigger this error
-```
->>> 30 / 'hello'
-Traceback (most recent call last):
- File "", line 1, in
-TypeError: unsupported operand type(s) for /: 'int' and 'str'
-```
-Another example, but we include an exception for the error this time
-```
->>> try:
-... 'text' + 20
-... except TypeError:
-... print('There was a type error')
-...
-There was a type error
-```
-
-### NameError
-When we try calling a variable a.k.a object name, that was not defined before, we should get a NameError
-```
->>> print(name)
-Traceback (most recent call last):
- File "", line 1, in
-NameError: name 'name' is not defined
-```
-
-### Error on improper exception
-Error would still occur if the except statement doesn't include the correct error type.
-```
->>> try:
-... 'text' + 20
-... except ValueError: # wont process as we get TypeError above
-... print('There was a value error')
-...
-Traceback (most recent call last):
- File "", line 2, in
-TypeError: can only concatenate str (not "int") to str
-```
-We get an error cause, as we tried to except ValueError, where as the statement in try block was producing TypeError
-
-
-### Exception for Multiple Errors
-We can include exceptions for multiple error types by separating each error type by a comma. The following example should have produced NameError.
-```
->>> try:
-... print(name)
-... except(NameError, TypeError):
-... print('There was a NameError or TypeError')
-...
-There was a NameError or TypeError
->>>
-```
-Another example for multiple exceptions, however it should have generated a TypeError
-```
->>> name = 'Michael'
->>>
->>> try:
-... print(name)
-... 'text' - 20
-... except(NameError, TypeError):
-... print('There was a NameError or TypeError')
-...
-Michael
-There was a NameError or TypeError
-```
-
-Or we could even provide exceptions for any error by jus saying expect with out any error type. Let's try printing the variable city, which is not defined before, this should have caused a NameError
-```
->>> try:
-... print(city)
-... except:
-... print('oh! there was an exception error')
-...
-oh! there was an exception error
-```
-Note that in the snippet above, we have excepted all types of Errors and not just NameError.
-
-One more example for providing exception to all errors
-```
->>> try:
-... print(y)
-... except:
-... print('There was an error, But that\'s ok, go ahead with the rest of the code')
-...
-There was an error, But that's ok, go ahead with the rest of the code
->>> print('Thank you')
-Thank you
->>>
-```
-### Print the standard message
-Its sometimes much apt to print the message the error would have been generated for, instead of printing a user defined message
-```
->>> try:
-... print(name)
-... except NameError as n:
-... print(n)
-...
-name 'name' is not defined
-```
-So the mesage ```name 'name' is not defined``` is coming straight from the NameError itself, and says why there was a NameError. Here we have caught the error message as variable ```n``` by saying ```NameError as n```, and then we ```print(n)``` it displays the error message or reason stored.
-
-One more example
-```
->>> try:
-... 'string ' + 2
-... except TypeError as t:
-... print(t)
-...
-can only concatenate str (not "int") to str
-```
-This time it printed the reason for the TypeError
-
-### Raise Errors
-We could even raise errors manually with the ```raise``` statement.
-```
->>> try:
-... raise TypeError()
-... except TypeError as t:
-... print(t)
-...
-
-```
-It shouldn't print anything cause we raised the error manually, and there wasn't any standard error message, providing the reason on why it was generated.
-
-We could however print a user defined message.
-```
->>> try:
-... raise TypeError()
-... except TypeError:
-... print('The type error was raised manually')
-...
-The type error was raised manually
-```
-
-### Class with Multi level inheritance
-The errors we have seen so far belong to a predefined class called Exception.
-```
->>> print(ValueError.__bases__)
-(,)
-
->>> print(TypeError.__bases__)
-(,)
-```
-Note that __bases__ is used to find the base class of a class.
-
-Let's define a class called Base that would inherit the Exception class. We are not defininig any unique attributes or methods for this class,
-and hence say pass.
-```
->>> class Base(Exception):
-... pass
-...
-```
-Now another class called Child, which would inherit the class 'Base'.
-```
->>> class Child(Base):
-... pass
-...
-```
-And the Grandchild class to further inherit from Child.
-```
->>> class Grandchild(Child):
-... pass
-...
-```
-We are going to loop over these classes, to raise that exception in each iteration, so that the except block would be executed.
-```
->>> for i in [ Base, Child, Grandchild ]:
-... try:
-... raise i()
-... except Grandchild:
-... print("Grand child exception")
-... except Child:
-... print("Child exception")
-... except Base:
-... print("Base exception")
-...
-Base exception
-Child exception
-Grand child exception
-```
-The loop above was straight forward, i.e. when the Base exception was raised, it would print 'Base exception'.
-
-Let's now reverse the order of except statements and try.
-```
->>> for i in [ Base, Child, Grandchild ]:
-... try:
-... raise i()
-... except Base:
-... print("Base exception")
-... except Child:
-... print("Child exception")
-... except Grandchild:
-... print("Grand child exception")
-...
-Base exception
-Base exception
-Base exception
->>>
-```
-Each time the Base exception will be caught, as both Child and Grandchild inherit Base. And the except block for Base was written first.
-
-### Custom message
-Define a custom exception as a sub / derived class of the Exception class.
-Define a new class MyException as a derived class of the Exception class.
-```
->>> class MyException(Exception):
-... pass
-...
-```
-Define InputException as a derived class of MyException. So InputException also inherits Exception.
-However a custom message is defined for InputException, so it won't inherit this message from Exception.
-```
->>> class InputException(MyException):
-... def __init__(self, message):
-... self.message = message
-...
-```
-Create an instance 'i' of the InputException class, and pass argument for message.
-```
->>> i = InputException('This is a user defined exception')
->>>
-```
-We can now raise i, i.e. an InputException instance, to create an error manually, and the screen would throw the custom message.
-```
->>> raise i
-Traceback (most recent call last):
- File "", line 1, in
-__main__.InputException: This is a user defined exception
-```
-```__main__``` is the value of the ```__name__``` keyword, its used to fetch the name of an object, and by default it's ```__main__```.
-It means the value of ```__name__``` in our program or module is always ```__main__```, and it has global scope, its like the name of the
-overall current module.
-```
->>> print(__name__)
-__main__
-```
-Each class will also have this attribute. For instance the ```__name__``` atrribute of InputException is its name itself,
-same is the case for Exception.
-```
->>> print(InputException.__name__)
-InputException
-
->>> print(Exception.__name__)
-Exception
-```
-
-### SyntaxError
-We have seen errors than can be excepted, but there are also Errors that can not be excepted.
-For instance IndentationError can not be excepted.
-```
->>> if True:
-... print('hi')
-... print('hello')
- File "", line 3
- print('hello')
- ^
-IndentationError: unindent does not match any outer indentation level
-```
-Indentation error is derived class of SyntaxError.
-```
->>> print(IndentationError.__bases__)
-(,)
-```
-
-Make a syntax error directly.
-```
->>> print('Hello)
- File "", line 1
- print('Hello)
- ^
-SyntaxError: EOL while scanning string literal
-```
-SyntaxError inherits Exception, which in turn inherits BaseException.
-```
->>> print(SyntaxError.__bases__)
-(,)
->>> print(Exception.__bases__)
-(,)
->>> print(BaseException.__bases__)
-(,)
->>> print(object.__bases__)
-()
->>>
-```
-
---end-of-post--
+---
+title: "python > errors and exceptions"
+categories: "python"
+---
+
+A Python program can break due to various types of Errors. We shall explore few of these errors in the post. To make best use of this post, you should know certain topics in Python3 such as datatypes, expression, pass statement, etc.
+
+Not all errors are significant, and hence there would be cases where we can skip certain errors to uninterrupt execution of our code, and this is achieved with ```try except``` blocks.
+
+### ZeroDivisionError
+This error is returned when we try to divide any number by 0
+```
+>>> 50 / 0
+Traceback (most recent call last):
+ File "", line 1, in
+ZeroDivisionError: division by zero
+```
+This time we tell Python not to break execution, by including things in a ```try except``` block.
+```
+>>> try:
+... 0 /0
+... except ZeroDivisionError:
+... pass
+...
+```
+The expression 00/0 in the try block should have produced a ZeroDivisionError, but since we are saying ```except ZeroDivisionError```, that error would be excepted. So there wont be any error and there should'nt be any output as well as we have included ```pass``` in the except block. Note that ```pass``` is used as a placeholder where you don't want the program to any program, and just to go the next line of the code in sequence if any.
+
+Let's try a different example, and also try printing some info instead of pass.
+```
+>>> try:
+... 120 / 0
+... except:
+... print('oh there was an exception')
+...
+oh there was an exception
+```
+
+### TypeError
+We can try to do an unsupported math operation, for example division, between a string and an integer, to trigger this error
+```
+>>> 30 / 'hello'
+Traceback (most recent call last):
+ File "", line 1, in
+TypeError: unsupported operand type(s) for /: 'int' and 'str'
+```
+Another example, but we include an exception for the error this time
+```
+>>> try:
+... 'text' + 20
+... except TypeError:
+... print('There was a type error')
+...
+There was a type error
+```
+
+### NameError
+When we try calling a variable a.k.a object name, that was not defined before, we should get a NameError
+```
+>>> print(name)
+Traceback (most recent call last):
+ File "", line 1, in
+NameError: name 'name' is not defined
+```
+
+### Error on improper exception
+Error would still occur if the except statement doesn't include the correct error type.
+```
+>>> try:
+... 'text' + 20
+... except ValueError: # wont process as we get TypeError above
+... print('There was a value error')
+...
+Traceback (most recent call last):
+ File "", line 2, in
+TypeError: can only concatenate str (not "int") to str
+```
+We get an error cause, as we tried to except ValueError, where as the statement in try block was producing TypeError
+
+
+### Exception for Multiple Errors
+We can include exceptions for multiple error types by separating each error type by a comma. The following example should have produced NameError.
+```
+>>> try:
+... print(name)
+... except(NameError, TypeError):
+... print('There was a NameError or TypeError')
+...
+There was a NameError or TypeError
+>>>
+```
+Another example for multiple exceptions, however it should have generated a TypeError
+```
+>>> name = 'Michael'
+>>>
+>>> try:
+... print(name)
+... 'text' - 20
+... except(NameError, TypeError):
+... print('There was a NameError or TypeError')
+...
+Michael
+There was a NameError or TypeError
+```
+
+Or we could even provide exceptions for any error by jus saying expect with out any error type. Let's try printing the variable city, which is not defined before, this should have caused a NameError
+```
+>>> try:
+... print(city)
+... except:
+... print('oh! there was an exception error')
+...
+oh! there was an exception error
+```
+Note that in the snippet above, we have excepted all types of Errors and not just NameError.
+
+One more example for providing exception to all errors
+```
+>>> try:
+... print(y)
+... except:
+... print('There was an error, But that\'s ok, go ahead with the rest of the code')
+...
+There was an error, But that's ok, go ahead with the rest of the code
+>>> print('Thank you')
+Thank you
+>>>
+```
+### Print the standard message
+Its sometimes much apt to print the message the error would have been generated for, instead of printing a user defined message
+```
+>>> try:
+... print(name)
+... except NameError as n:
+... print(n)
+...
+name 'name' is not defined
+```
+So the mesage ```name 'name' is not defined``` is coming straight from the NameError itself, and says why there was a NameError. Here we have caught the error message as variable ```n``` by saying ```NameError as n```, and then we ```print(n)``` it displays the error message or reason stored.
+
+One more example
+```
+>>> try:
+... 'string ' + 2
+... except TypeError as t:
+... print(t)
+...
+can only concatenate str (not "int") to str
+```
+This time it printed the reason for the TypeError
+
+### Raise Errors
+We could even raise errors manually with the ```raise``` statement.
+```
+>>> try:
+... raise TypeError()
+... except TypeError as t:
+... print(t)
+...
+
+```
+It shouldn't print anything cause we raised the error manually, and there wasn't any standard error message, providing the reason on why it was generated.
+
+We could however print a user defined message.
+```
+>>> try:
+... raise TypeError()
+... except TypeError:
+... print('The type error was raised manually')
+...
+The type error was raised manually
+```
+
+### Class with Multi level inheritance
+The errors we have seen so far belong to a predefined class called Exception.
+```
+>>> print(ValueError.__bases__)
+(,)
+
+>>> print(TypeError.__bases__)
+(,)
+```
+Note that __bases__ is used to find the base class of a class.
+
+Let's define a class called Base that would inherit the Exception class. We are not defininig any unique attributes or methods for this class,
+and hence say pass.
+```
+>>> class Base(Exception):
+... pass
+...
+```
+Now another class called Child, which would inherit the class 'Base'.
+```
+>>> class Child(Base):
+... pass
+...
+```
+And the Grandchild class to further inherit from Child.
+```
+>>> class Grandchild(Child):
+... pass
+...
+```
+We are going to loop over these classes, to raise that exception in each iteration, so that the except block would be executed.
+```
+>>> for i in [ Base, Child, Grandchild ]:
+... try:
+... raise i()
+... except Grandchild:
+... print("Grand child exception")
+... except Child:
+... print("Child exception")
+... except Base:
+... print("Base exception")
+...
+Base exception
+Child exception
+Grand child exception
+```
+The loop above was straight forward, i.e. when the Base exception was raised, it would print 'Base exception'.
+
+Let's now reverse the order of except statements and try.
+```
+>>> for i in [ Base, Child, Grandchild ]:
+... try:
+... raise i()
+... except Base:
+... print("Base exception")
+... except Child:
+... print("Child exception")
+... except Grandchild:
+... print("Grand child exception")
+...
+Base exception
+Base exception
+Base exception
+>>>
+```
+Each time the Base exception will be caught, as both Child and Grandchild inherit Base. And the except block for Base was written first.
+
+### Custom message
+Define a custom exception as a sub / derived class of the Exception class.
+Define a new class MyException as a derived class of the Exception class.
+```
+>>> class MyException(Exception):
+... pass
+...
+```
+Define InputException as a derived class of MyException. So InputException also inherits Exception.
+However a custom message is defined for InputException, so it won't inherit this message from Exception.
+```
+>>> class InputException(MyException):
+... def __init__(self, message):
+... self.message = message
+...
+```
+Create an instance 'i' of the InputException class, and pass argument for message.
+```
+>>> i = InputException('This is a user defined exception')
+>>>
+```
+We can now raise i, i.e. an InputException instance, to create an error manually, and the screen would throw the custom message.
+```
+>>> raise i
+Traceback (most recent call last):
+ File "", line 1, in
+__main__.InputException: This is a user defined exception
+```
+```__main__``` is the value of the ```__name__``` keyword, its used to fetch the name of an object, and by default it's ```__main__```.
+It means the value of ```__name__``` in our program or module is always ```__main__```, and it has global scope, its like the name of the
+overall current module.
+```
+>>> print(__name__)
+__main__
+```
+Each class will also have this attribute. For instance the ```__name__``` atrribute of InputException is its name itself,
+same is the case for Exception.
+```
+>>> print(InputException.__name__)
+InputException
+
+>>> print(Exception.__name__)
+Exception
+```
+
+### SyntaxError
+We have seen errors than can be excepted, but there are also Errors that can not be excepted.
+For instance IndentationError can not be excepted.
+```
+>>> if True:
+... print('hi')
+... print('hello')
+ File "", line 3
+ print('hello')
+ ^
+IndentationError: unindent does not match any outer indentation level
+```
+Indentation error is derived class of SyntaxError.
+```
+>>> print(IndentationError.__bases__)
+(,)
+```
+
+Make a syntax error directly.
+```
+>>> print('Hello)
+ File "", line 1
+ print('Hello)
+ ^
+SyntaxError: EOL while scanning string literal
+```
+SyntaxError inherits Exception, which in turn inherits BaseException.
+```
+>>> print(SyntaxError.__bases__)
+(,)
+>>> print(Exception.__bases__)
+(,)
+>>> print(BaseException.__bases__)
+(,)
+>>> print(object.__bases__)
+()
+>>>
+```
+
+--end-of-post--
diff --git a/_posts/python/2020-06-28-python-classes-and-instances.md b/_posts/python/2020-06-28-python-classes-and-instances.md
index fa4f8e5..f6e96fc 100644
--- a/_posts/python/2020-06-28-python-classes-and-instances.md
+++ b/_posts/python/2020-06-28-python-classes-and-instances.md
@@ -1,7 +1,7 @@
---
-title: python > classes and instances
-categories: python
-...
+title: "python > classes and instances"
+categories: "python"
+---
We are going to see some object oriented programming here.
Its nice to have fundamental understanding of Python functions or methods, datatypes for better understanding of this post.
diff --git a/_posts/python/2020-07-18-python-dictionaries.md b/_posts/python/2020-07-18-python-dictionaries.md
index aabb1e5..1464583 100644
--- a/_posts/python/2020-07-18-python-dictionaries.md
+++ b/_posts/python/2020-07-18-python-dictionaries.md
@@ -1,6 +1,6 @@
---
-title: python > dictionaries
-categories: python
+title: "python > dictionaries"
+categories: "python"
---
Dictionaries are datastructure objects that can store information in a key value pair format, in this post, we will explore some information about
dictionaries and their associated methods. The prerequisites are knowledge of boolean, exceptions, float, integers, methods, strings, etc.
diff --git a/_posts/python/2020-07-18-python-file-operations.md b/_posts/python/2020-07-18-python-file-operations.md
index 119787b..92d3cfd 100644
--- a/_posts/python/2020-07-18-python-file-operations.md
+++ b/_posts/python/2020-07-18-python-file-operations.md
@@ -1,6 +1,6 @@
---
-title: python > file operations
-categories: python
+title: "python > file operations"
+categories: "python"
---
Python's inbuilt open function could be used to interact with the file system of the underlying operating system. Let's see more on this. You
diff --git a/_posts/python/2020-07-25-python-user-input.md b/_posts/python/2020-07-25-python-user-input.md
index 0bc8f90..7158f81 100644
--- a/_posts/python/2020-07-25-python-user-input.md
+++ b/_posts/python/2020-07-25-python-user-input.md
@@ -1,6 +1,6 @@
---
-title: python > user input
-categories: python
+title: "python > user input"
+categories: "python"
---
Sometimes its necessary to take some input from the user and pass it to
diff --git a/_posts/python/2020-07-26-python-loops.md b/_posts/python/2020-07-26-python-loops.md
index ce4438f..e236972 100644
--- a/_posts/python/2020-07-26-python-loops.md
+++ b/_posts/python/2020-07-26-python-loops.md
@@ -1,6 +1,6 @@
---
-title: python > loops
-categories: python
+title: "python > loops"
+categories: "python"
---
Loops are common in all programmings languages, they help in executing tasks that are recurring in nature. Lets look at these loops in Python with few examples. The prerequisites are: knowing how to Python code through the Interpreter or as a script in a file.
diff --git a/_posts/python/2020-07-26-python-regular-expressions.md b/_posts/python/2020-07-26-python-regular-expressions.md
index 92d0bf6..71475c0 100644
--- a/_posts/python/2020-07-26-python-regular-expressions.md
+++ b/_posts/python/2020-07-26-python-regular-expressions.md
@@ -1,6 +1,6 @@
---
-title: python > regular expressions
-categories: python
+title: "python > regular expressions"
+categories: "python"
---
Let's learn some bits of regular expression here, hope you are already familiar with strings in Python.
diff --git a/_posts/python/2020-10-20-python-import-modules.md b/_posts/python/2020-10-20-python-import-modules.md
index c670708..6d74e95 100644
--- a/_posts/python/2020-10-20-python-import-modules.md
+++ b/_posts/python/2020-10-20-python-import-modules.md
@@ -1,6 +1,6 @@
---
-title: python > import modules
-categories: python
+title: "python > import modules"
+categories: "python"
---
There could be tasks that we intend to perform in Python, which are not doable straightway by a builtin function or class method, we would have to import specific
diff --git a/_posts/python/2020-10-25-python-ways-to-run-code.md b/_posts/python/2020-10-25-python-ways-to-run-code.md
index 28e1035..3e00c02 100644
--- a/_posts/python/2020-10-25-python-ways-to-run-code.md
+++ b/_posts/python/2020-10-25-python-ways-to-run-code.md
@@ -1,6 +1,6 @@
---
-title: python > ways to run code
-categories: python
+title: "python > ways to run code"
+categories: "python"
---
Let's see some ways of running Python. It's assumed you know some basics of Linux and its filesystem navigation.
diff --git a/about.markdown b/about.markdown
deleted file mode 100644
index 8dafbd7..0000000
--- a/about.markdown
+++ /dev/null
@@ -1,19 +0,0 @@
----
-layout: page
-title: "about"
-permalink: /about/
----
-
-
-
-```
-blog > practice > share | [ network coding cloud… ]
-```
-
-This site holds notes/posts related to technical topics such as cloud, containers, networking, automation, and so on.
-The tech keywords for search in the site include Kubernetes, OpenStack, Ansible, Python, etc.
----
-
-[](https://github.com/networkandcode)
-[](https://linkedin.com/in/networkandcode)
-[](https://www.youtube.com/channel/UCZTRMzFB2HJ6zCDM1n4FhHA)
\ No newline at end of file
diff --git a/astro.config.mjs b/astro.config.mjs
new file mode 100644
index 0000000..c36b7e8
--- /dev/null
+++ b/astro.config.mjs
@@ -0,0 +1,15 @@
+import { defineConfig } from 'astro/config';
+import mdx from '@astrojs/mdx';
+import tailwindcss from '@tailwindcss/vite';
+import { syncGoogleDocCv } from './src/lib/syncCv.ts';
+import { syncDevToPosts } from './src/lib/syncDevTo.ts';
+import { syncHashnodePosts } from './src/lib/syncHashnode.ts';
+
+// https://astro.build/config
+export default defineConfig({
+ site: 'https://networkandcode.github.io',
+ integrations: [mdx(), syncGoogleDocCv(), syncDevToPosts(), syncHashnodePosts()],
+ vite: {
+ plugins: [tailwindcss()]
+ }
+});
diff --git a/gemma4-try/agent.py b/gemma4-try/agent.py
index 5be104c..186a4aa 100644
--- a/gemma4-try/agent.py
+++ b/gemma4-try/agent.py
@@ -11,8 +11,4 @@
MODEL,
)
-search_agent = Agent(
- name=AGENT_NAME,
- model=MODEL,
- tools=[fetch_fruits, greet_user]
-)
+search_agent = Agent(name=AGENT_NAME, model=MODEL, tools=[fetch_fruits, greet_user])
diff --git a/gemma4-try/main.py b/gemma4-try/main.py
index ea526f4..e758dc7 100644
--- a/gemma4-try/main.py
+++ b/gemma4-try/main.py
@@ -9,27 +9,28 @@
SESSION_ID,
USER_ID,
)
-
+
+
async def main():
await session_service.create_session(
- app_name=APP_NAME,
- user_id=USER_ID,
- session_id=SESSION_ID
+ app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID
)
-
+
while True:
user_message = input("User: ")
- content = types.Content(role='user', parts=[types.Part(text=user_message)])
-
- async for event in runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=content):
+ content = types.Content(role="user", parts=[types.Part(text=user_message)])
+
+ async for event in runner.run_async(
+ user_id=USER_ID, session_id=SESSION_ID, new_message=content
+ ):
if event.is_final_response():
if event.content and event.content.parts:
for part in event.content.parts:
- if (not part.thought):
+ if not part.thought:
print(part.text)
else:
print(event)
-
+
if __name__ == "__main__":
asyncio.run(main())
diff --git a/gemma4-try/runner.py b/gemma4-try/runner.py
index 043a2ec..9d2e9c8 100644
--- a/gemma4-try/runner.py
+++ b/gemma4-try/runner.py
@@ -3,11 +3,7 @@
from agent import search_agent
from session_service import session_service
from vars import (
- APP_NAME,
+ APP_NAME,
)
-runner = Runner(
- agent=search_agent,
- app_name=APP_NAME,
- session_service=session_service
-)
+runner = Runner(agent=search_agent, app_name=APP_NAME, session_service=session_service)
diff --git a/gemma4-try/tool.py b/gemma4-try/tool.py
index 682f452..6324cfd 100644
--- a/gemma4-try/tool.py
+++ b/gemma4-try/tool.py
@@ -1,5 +1,6 @@
import httpx
+
def fetch_fruits(fruit: str):
url = f"https://api.example.com/api/fruit/{fruit}"
@@ -12,4 +13,4 @@ def fetch_fruits(fruit: str):
def greet_user(user: str):
- return f"Hello {user}"
\ No newline at end of file
+ return f"Hello {user}"
diff --git a/gemma4-try/vars.py b/gemma4-try/vars.py
index 888750e..2fe9d9d 100644
--- a/gemma4-try/vars.py
+++ b/gemma4-try/vars.py
@@ -1,5 +1,5 @@
-AGENT_NAME="test_agent"
+AGENT_NAME = "test_agent"
APP_NAME = "test_app"
-MODEL="gemma-4-31b-it" # gemma-4-26b-a4b-it is also supported
+MODEL = "gemma-4-31b-it" # gemma-4-26b-a4b-it is also supported
SESSION_ID = "test_session"
USER_ID = "test_user"
diff --git a/index.markdown b/index.markdown
deleted file mode 100644
index 0671507..0000000
--- a/index.markdown
+++ /dev/null
@@ -1,6 +0,0 @@
----
-# Feel free to add content and custom Front Matter to this file.
-# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults
-
-layout: home
----
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 0000000..33eaceb
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,6770 @@
+{
+ "name": "planetary-parallax",
+ "version": "0.0.1",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "name": "planetary-parallax",
+ "version": "0.0.1",
+ "dependencies": {
+ "@astrojs/mdx": "^7.0.5",
+ "@tailwindcss/vite": "^4.3.3",
+ "astro": "^7.2.0",
+ "tailwindcss": "^4.3.3"
+ },
+ "engines": {
+ "node": ">=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding/-/compiler-binding-0.3.2.tgz",
+ "integrity": "sha512-8w/9CWmYrAJJ8N0SY3O43ws2BgxoW6u3QsD8u2mE140lMYAlwh+tlNoUeSBq22wVheFuiBbR212l6ixZ2IIgCQ==",
+ "license": "MIT",
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ },
+ "optionalDependencies": {
+ "@astrojs/compiler-binding-darwin-arm64": "0.3.2",
+ "@astrojs/compiler-binding-darwin-x64": "0.3.2",
+ "@astrojs/compiler-binding-linux-arm64-gnu": "0.3.2",
+ "@astrojs/compiler-binding-linux-arm64-musl": "0.3.2",
+ "@astrojs/compiler-binding-linux-x64-gnu": "0.3.2",
+ "@astrojs/compiler-binding-linux-x64-musl": "0.3.2",
+ "@astrojs/compiler-binding-wasm32-wasi": "0.3.2",
+ "@astrojs/compiler-binding-win32-arm64-msvc": "0.3.2",
+ "@astrojs/compiler-binding-win32-x64-msvc": "0.3.2"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-darwin-arm64": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-darwin-arm64/-/compiler-binding-darwin-arm64-0.3.2.tgz",
+ "integrity": "sha512-MM8tn8CSimcfytaOla4b6acN8mKWiL/rlAA1fpT3/Wl7dNGSE4y8FjTN/zJVNnb63CsLWG5zZwCt01TXtDKh9g==",
+ "cpu": [
+ "arm64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "darwin"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-darwin-x64": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-darwin-x64/-/compiler-binding-darwin-x64-0.3.2.tgz",
+ "integrity": "sha512-2lXOlzf8xb7jLomRsf/aswh61/NnGusynB2OwFkK6k4pmOtpfXMYnG0PLfXrEvxXYj69NdCnmUYXtHDd+JOOag==",
+ "cpu": [
+ "x64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "darwin"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-linux-arm64-gnu": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-linux-arm64-gnu/-/compiler-binding-linux-arm64-gnu-0.3.2.tgz",
+ "integrity": "sha512-BmU3kWj7qnLrd4vzm49zFEPJ5oFnn1tCT4Vt9hZbqdU5Cmb8GZl7fn6VFsnNfe7B18a2gIFtVzbLINtYl5kBjQ==",
+ "cpu": [
+ "arm64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "linux"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-linux-arm64-musl": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-linux-arm64-musl/-/compiler-binding-linux-arm64-musl-0.3.2.tgz",
+ "integrity": "sha512-f0heT9ZZEseSu5bHCeb80eL2DH07ArE6U9xi1WT/PEusNjzPmEr3GJsjG1tRLo5VYUUYX7h3ScaqGmGrMOVGmw==",
+ "cpu": [
+ "arm64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "linux"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-linux-x64-gnu": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-linux-x64-gnu/-/compiler-binding-linux-x64-gnu-0.3.2.tgz",
+ "integrity": "sha512-M8fOUt0itRpqiGyoEA/ij184s8O+hqbCz3+YozRusOOM3osgGljpDThhbKAJjqh82wOo6FioQ4w8PBvU1XMD5Q==",
+ "cpu": [
+ "x64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "linux"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-linux-x64-musl": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-linux-x64-musl/-/compiler-binding-linux-x64-musl-0.3.2.tgz",
+ "integrity": "sha512-/Kebk8sO6HnLeSd691JkaAPfN7CqR9/KEXmWvyNPkaKNGmj8rTZ/lf2uXtnPu92Lan84UrKdIKVPy1fSo2encQ==",
+ "cpu": [
+ "x64"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "os": [
+ "linux"
+ ],
+ "engines": {
+ "node": "^20.19.0 || >=22.12.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-wasm32-wasi": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-wasm32-wasi/-/compiler-binding-wasm32-wasi-0.3.2.tgz",
+ "integrity": "sha512-pUA6xbcOSB7DhfzIArB8BCAkFfAIqriiR7zl5zOStd6oU2G0kIKj+GUdGnyXyhfiv881Hffyk5tC0mR18sDjDw==",
+ "cpu": [
+ "wasm32"
+ ],
+ "license": "MIT",
+ "optional": true,
+ "dependencies": {
+ "@napi-rs/wasm-runtime": "^1.2.0"
+ },
+ "engines": {
+ "node": ">=14.0.0"
+ }
+ },
+ "node_modules/@astrojs/compiler-binding-win32-arm64-msvc": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@astrojs/compiler-binding-win32-arm64-msvc/-/compiler-binding-win32-arm64-msvc-0.3.2.tgz",
+ "integrity": "sha512-ESruf+6Qkl1trHUFxI6GSf6t52j8yN2kCNSzMWdzt7V/T09tFHrYzrVaJQohb2C9bJUH76pNvX6Zb51+xCQc9Q==",
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----
-
-Get $25 credits at UpCloud
-
-
-
-
-
-
-
-
-
-
-Learn a language for free at Duolingo
-
-Buy cheap domains, hosting or other related services at namecheap
-
-Learn by reading and save time with super cool courses at
- Educative
-
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Techie with experience spanning DevOps/SRE, AI/ML, Fullstack development, Networking and Team leadership. Has experience as a product owner, defining and prioritizing features for UI, APIs and Platform integrations. Led cloud native solutions in automation, CI/CD, data, edge computing, serverless development and observability. Authored technical blogs covering topics in automation, cloud computing, databases, networking, observability, and software development. Designed and developed open source web applications, integrating authentication, UI frameworks, databases, and APIs. Built and deployed solutions across multiple platforms, leveraging modern development and hosting environments.
Solution Architect I - Enterprise Solutions | UST, Trivandrum, India | Jun 2019 – Present
Led development of AI chatbot with generative and agentic AI capabilities (observability, business insights, web automation, cost analysis with MCP tools and RAG) using Langgraph.
Involved in the development of a event driven full-stack application with angular UI and Fast API based backend services with interactions to components such as Bedrock/Gemini API, NATS, Milvus, Vault/Secret Manager.
Designed and developed an AI powered Data Analytics agent with failure handling, retry logic, and improved UX for tool progress messages.
Built and deployed a FinOps agent with Langfuse integration for cost observability, including Helm-based deployment and Dockerized packaging on AWS.
Diagnosed and resolved production issues in a Slack based conversational agent — fixing memory/context retention and message summarization capabilities.
Set up CDK infrastructure for FinOps cloud resources in AWS (Astra account), following IaC best practices.
Implemented Slack OAuth MCP for per-user credential management and integrated a Slack Remote MCP Server for seamless MCP framework communication.
Refactored integration warning messages for token based connections, improving developer and user experience.
Owned end to end development and delivery of the application with microservices, integrated with envoy gateway and OIDC based authentication with keycloak.
Was involved in PR reviews and github administration.
Setup GHAS enterprise with hard ended configurations for enterprise, org and repo levels
Involved in establishing GitHub actions based reusable workflows for app and infra code.
Led development of observability stacks with 200+ reusable assets; managed Agile projects, mentored teams, and drove knowledge sharing.
Lead/Mentor/Support a team of devops engineers
Domains worked on: Manufacturing, Retail, Healthcare, Food/Beverage
Lead and built along with the team, open telemetry compatible observability solutions with helm charts, dashboards and alerting templates meant to be consumed by clients and within the organization. Bootstrapped deployments for the complete observability stack that has tools such as Grafana, Prometheus, Mimir, Loki, Tempo, Keycloak for Authentication/RBAC etc. on Kubernetes. And GCP based observability solutions involving the GCP native stack such as GCP Monitoring, GCP Logging, GCP Tracing, GCP managed Prometheus
Implemented executive and operations hierarchical/drilldown dashboards for AKS, Confluent Kafka, APM, Linux system metrics in Grafana with Elastic as data source, with direct elastic index and prometheus collector index, and alerts with kibana for the same
Deployed Confluent kafka on Kubernetes(CFK), integrated it with LDAPS and enabled RBAC. Implemented traffic routing with Istio in TLS pass through mode. Provisioned self signed TLS certificates for each component. Added topics declaratively. Integrated with tibco source and cosmos sink connectors. Installed custom SMTs. Tested the setup with a Spring boot client
Supported the setup of CI/CD with Jenkins and Harness for 30+ microservices and their migration from OpenShift to AKS
Setup Azure dashboards to monitor metrics received from AKS & App insights logs, with azure cli and arm templates
Provided solution for implementing custom alert messages with Azure monitor, Azure communication service and Function app (Python)
Provided solution for implementing automated onebox deployments with ArgoCD, Argo workflow, Helm, Jenkins, and Python
Worked on a GCP project related to IoT & Serverless
Modified existing serverless NodeJS function handlers to support both Azure(existing) and Google cloud run(new)
Setup Dockerfiles for deploying cloud run services with express
Installed Telegraf with docker compose and configured input(http, opcua, mssql, socket) and output(cloud_pubsub, influxdb_v2) plugins
Setup simulators with python for ingesting data to telegraf
Deploy InfluxDB with Edge data replication (EDR)
Wrote code for instantiating neo4j drivers, sessions, and transactions and converted gremlin queries to neo4j cypher in the handlers.
Groom the team by taking knowledge sharing sessions on topics such as Neo4j / GraphDB fundamentals, InfluxDB
Plan stories on Jira for the team for each sprint
Setup Anthos GKE cluster and deploy workloads with helm
Written dataflow job with apache beam in python to ingest data from gcp pub/sub to mongodb
Setup GCP cloud workflow with cloud scheduler trigger and parallel steps calling cloud run endpoints
Troubleshoot Gitlab CI pipelines that are setup for linting, testing and building serverless functions
Taken sprint demos to the customer
Track projects’ progress with Jira and run the Kanban/Scrum boards
Implemented DevOps environment on Azure with Terraform
Setup CI/CD with Jenkins and Spinnaker, Helm , Kubernetes(AKS)
Write Istio manifests for gateway, virtual service, and service entry
Configuring cloud resources such as application gateway, APIM, storage account, sql server, keyvault
Involved in change management process initiated via service now
Databricks administration activities such as user / secret scope management, cluster creation
Setup CI/CD for notebooks and jobs on azure databricks via Jenkins
Worked on DevOps tasks assigned through Jira aligned with Platform or Support, centered around the lifecycle of web applications deployed as container workloads
Setup CI / CD pipelines using Jenkins / Spinnaker
Wrote code in groovy, bash, python for Jenkinsfiles and other scripts
Implemented housekeeping tasks for builds and container images
Troubleshoot App failures on the AKS cluster
Written queries in Kusto and PromQL for scraping metrics via Azure Log Analytics and Prometheus respectively
Provisioned Grafana dashboards for visualizing App and cluster metrics, with Azure AD integration, and configured email alerts for certain thresholds
Implemented the workflow for automatic secret management of containers in Kubernetes, with pipelines, and via Azure key vault and Twistlock
Added functionalities to the pipeline, such as NPM Audit with whitelisted CWEs and CVEs, OWASP dependency check for gradle and maven builds with suppression file
Wrote a pipeline stage as code, to do Pass / Fail check for ZAP scan on a target URL based on parameters such as number of warnings and Failures
Performed POCs on contract tests with Pact and validation using Pact Broker, UI tests on Zalenium
Exposed to platform / tooling ecosystem such as Artifactory, Azure, Helm, Kubernetes, SonarQube
Identified unused cloud components in Azure that could be removed and to save cost if applicable
Wrote Azure DevOps pipeline to automate start and stop of AKS clusters with cron
Product Consultant 3 | Juniper Networks, Bangalore, India | Feb 2019 – Jun 2019
Individual technical contributor, attend project calls with stakeholders, draft LLDs / HLDs, simulate Labs on VMM, assist ISP customers with implementation/support in both testbeds/POCs and Production.
Scope of Work involves Design, Validation, Testing, Deployment, Acceptance Testing, Knowledge transfer and Post Installation support
Installed AppFormix on standalone, Kubernetes and VMware ESXi platforms
Taken knowledge sharing sessions on AppFormix to other peers in the team
Installed Contrail HeathBot in a multinode environment, using Docker Swarm
Contributed to internal GIT Wiki with content such as installing HealthBot, installing AppFormix and Contrail Networking in an OpenStack environment
Worked on JunOS Space/Service Now project and Fixed Incident generation and SFTP access issue, upgraded AI Scripts on SRX
Partly involved in jQuery/JavaScript validation for an internal dashboard
Sr. Principal Infrastructure Engineer | Mphasis Ltd, Chennai, India | Sep 2016 – Jan 2019
Lead a team of 10+ members, and responsible for task assignment, activity reports, time tracking, performance review/rating, appreciations & award nominations. 90+ appreciation cards sent to the team members. Delegated value add on tasks such as Leave/Workload analysis, 4Eye forecast/updates, Training mentor, SOP reviewer, SDM call SPOC, Dashboard preparation, MTP auditing to individuals. The team has contributed with 40+ SOPs, received 50+ client appreciations, 2 promotions and 20+ monthly awards
Used Office 365 tools such as SharePoint lists (with formulae validation), OneNote (for shared Knowledge transfer), Power Bi (for visual reports) effectively for organizing the team in all aspects such as achieving goals, timesheets, comp-off / allowance trackers, new member onboarding guidance
Provided weekly SDM reports and monthly team dashboards to validate the team’s overall performance
Individually contributed by implementing the LAN & WLAN setups of 50+ sites in APJ & EMEA with varying scopes such as new setups, migration, split-up & merger, decommissioning, etc.
Project life cycle includes RFC submissions using SDLC manager / HPSM, attending CAB/TAB calls, following ITIL change management processes, project coordination, design validation, device monitoring (HPNA, HP NNM, Airwave, ClearPass) addition/removal/modification tasks
Majority of the work involved Re-IP and Redesigning networks including wireless, and WAN migration through the new service provider
Network router / switch activities include: HA concepts like VRRP, IRF; monitoring configuration like SNMP/TACACS; routing/switching configuration like OSPF, BFD, Multicast, BGP, STP
Wireless activities performed are migrating from MSM to Aruba, setting up the local controller (7200 series) including High Availability, GRE tunneling the local and master controller, dynamic AP provisioning, configuring the access switch ports to untag/tag proper VLANs to the access points, SSID, Other relevant sync up configuration between the master and local controller such as WAP groups, SSIDs, HA groups
Partly involved in incident and release management (patch upgrades for procurve, comware and Aruba devices)
Developed python-based scripts/tools in both CLI and GUI form using libraries like paramiko, netmiko, tkinter, kivy, to execute recurring day to day tasks such as Configuration preparation templates, Inventory checks for CMDB updates, Bulk DNS/Ping, PAC checks, disabling SNMP based on interface descriptions, Move to production (MTP) audits, remote commands executor, audit hundreds of configuration text files using regular expression pattern search
Used multithreading and multiprocessing with python code wherever applicable to fasten execution time
Assisted an internal project with 2 major automation tasks: SSH hardening on 3K plus HP Comware devices, and TACACS domain/server migration for approx. 5K HP Comware / Cisco IOS devices
Contributed to the Employee Development Program by conducting Knowledge sharing sessions on topics like Python for network automation, Linux for networking, NETCONF and OpenStack administration, webinar on Networking in the Cloud
Had contributed with 20+ SOPs on topics such as OS upgrades, Wireless ReIP
Assisted the TalentNext team with drafting the upskilling requirements for the SDN practice
Involved in auditing / assessing the network infrastructure for various accounts under the practice, w.r.t configuration, architecture, device support, capacity/uptime, Next Gen readiness
Coordinated with external and internal stakeholders vendors to carry out Proof of concepts on technologies like SD-WAN, spinning topologies on the AWS cloud, and for testing functionalities such as QoS, NGFW
Sr. Analyst | HCL Technologies, Chennai, India | Mar 2015 – Aug 2016
Sr. N/W Engineer | BRT India, Chennai, India | May 2013 – Mar 2015
Was part of the Global IT Networks Business Onboarding team, role: Network design, implementation and project coordination. Worked for project types such as expansion, redesign, migration, new setup etc.
Designed end-to-end networks, prepared RFP, HLD, LLD using Visio, BOM for LAN/WLAN/WAN inventory and links, raised change/incident requests, and coordinated with various stakeholders and vendors, until successful implementation & UAT
Implemented Microsoft Azure Express route setups, IPSEC (Client-to-Site / Site-to-Site) / MPLS L3 VPNs, shared/dedicated LANs, and thin client/zero client/VDI based connectivity
Submitted LLDs with firm quotes to give a more clearer picture to the Business on the costs involved, solution benefits, and timelines involved, dependencies from the business on certain factors such as local on-site or offshore infra readiness before link deployment, demark agreements, legal formalities with merging the MPLS VRF of two different service providers or between two different entities (example India and UK) of the same provider
Regular meetings held to update the link/hardware delivery/implementation progress
Installed and configured new devices that include Cisco IOS or Juniper JunOS EX/MX, configured protocols such as OSPF, BGP
ITIL change management process is followed for all backbone/operational changes such as adding a new VLAN / VRF for the new customer, assigning BW to the customer VRF, capacity management to cater BW forecasts, adding IP VPN routes for the customer destinations towards the shared internet gateway, and coordination is done with respective stakeholders and the required configuration is shared with them in predefined templates
Prepared an end to end document and handover liability to global NOC after successful implementation and UAT
Reviewed projects handled by the team reported highlights/challenges to the management every week
Sr. Consultant | Sutherland Global Services, Cochin, India | Feb 2012 – Sep 2012
Remote support over phone and chat, for Networking devices/links, Desktops, Printers, gadgets, applications such as Microsoft outlook, and fixing virus/malware infections.
The SLA was for each case had more time (more than an hour in average), as this was 3rd level of support and is a paid subscription which isn’t associated with any product
Issues could be complex and there were 3 ways to assist the customer according to the need – phone, chat or remote desktop
Occasionally assisted with fixing CCTV remote access issues where the router’s port forwarding had to be configured properly
Sr. Support Engineer | CSS Corp, Chennai, India | Mar 2011 – Feb 2012
Technical assistance over Phone, for new VOIP gateway installations, fixing audio errors & call completion issues, modems/routers, fax setup, and refreshing lines on VOIP adapters.
Worked for the technical support team, had to attend incoming calls and resolve customer’s issues
Assisted with both technical and billing issues
The calls had to be closed within the predefined Average SLA (approx. 15 to 20 min) and 100% CSATs are to be met
Handled calls from US and Canada regions
Sr. Project Engineer | Gecom, Bahrain | Jan 2010 – Jan 2011
Site survey, installation, commissioning, documentation, maintenance and support for networking devices such as modems/routers/wireless APs/switches, PABX/PBX, CCTVs/DVRs, biometric infra, Clipsal c-bus Intelligent lighting automation, security/alarm systems. Assisted with remote CCTV access using DYNDNS configuration.
The work is 100% on site, except for time entry and certain meetings in the office
Projects are segregated team wise, with each team handling its own set of projects, Worked for two different teams under different supervisors during this job, involved as a team and executed all the activities of a project from scratch, for instance a lighting project gave exposure from the initial phase of wiring (using cat5/6 for both electricity and network) until implementing the lighting scenarios including brightness levels based on switch/touch panel events that are orchestrated using the software provided by Clipsal
Was involved in setting up the CCTV & Security Panel systems at ATMs and various Bank premises, that was all part of one big project as a whole
Lighting implementations handled for few ministry projects and occasionally involved in the maintenance of the previously implemented lighting automation at the World Trade Center
Performed various other related work for Hotels, Villas (individual or a group owned by a single entity), Shops in Malls, etc.
Had deployed BOSE sound systems on few occasions, once for a private house party DJ setup
Education
BITS Pilani work integrated learning programmes, M.Tech.(CSI), CGPA 8.17, 2020
Crescent Engineering College, Bachelor of Engineering in E.C.E, 62%, 2008
Addons
Was involved in setting up curriculum and evaluation criteria in DevOps and AI for freshers
Was involved in showcasing agentic AI product at booths in UST events
Part of the UST ignite / colors community, gave computer science training for school students on programs such as Microsoft word, excel, power point
Part of the Generative AI initiative in UST, took trainings with in the organization
Winner of the secure code warrior competition organized by UST
Recipient of Google India challenge scholarship 2018
Participated in the Juniper haiku learning bytes challenge
Submitted network designs in the Juniper Idea2Design challenge 2015
Solved challenges in tournaments 3 and 4 of JunOS cup 2014
Past Freelancing Experience: Web Development with frameworks such as Flask, Gatsby, NextJS. Involved in part time tutoring – private, online and classroom based for subjects such as school mathematics, engineering mathematics, python, network automation, web development
Secured seat in college through merit with entrance cut-off 280+/300
Volunteered for electoral activities through NSS
Participated in Computer science events and won awards during school
Represented super senior level school cricket team
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