DEV Community: Aniket Kumar Sinha

Deploy Airbyte on AKS

Aniket Kumar Sinha — Thu, 03 Oct 2024 16:57:46 +0000

What is Airbyte?

Airbyte is an open-source data movement infrastructure for building extract and load (EL) data pipelines. It is designed for versatility, scalability, and ease-of-use.

In simple terms, it is a platform to unanimously fetch your data from various platforms and use it for your data analysis purposes.

What is AKS?

Azure Kubernetes Service (AKS) is a managed Kubernetes service that you can use to deploy and manage containerized applications.

What is Kubernetes?

Kubernetes is a portable, extensible, open source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation.

Why to use AKS (K8s) for Airbyte?

To understand this, let's first understand the available options to deploy Airbyte.

So, as suggested by Airbyte, we can use Virtual machine to run Airbyte locally in VM. It is a fantastic idea for keep the VM running all the time to run Airbyte locally on it. But the issues comes where we have multiple data pipelines with loads and loads on data getting fetched via Airbyte. It can make the VM go out of service. And to make it run all the time with such load, it will incur lot of cost. So, here comes the scaling and cost as an issue.

Thus comes the better option to deploy it over K8s in Azure using Azure Kubernetes Service for easy scaling!

Even Airbyte too suggest K8s as the best option to deploy it over. But they don't have enough documents for AKS and thus we are here to understand it better.

Using Helm Charts

A Helm Chart is a collection of templates and settings that describe a set of Kubernetes resources.

We will use Helm Charts to deploy Airbyte on AKS. Airbyte has predefined Helm charts with some specific general values for Airbyte. You can even alter those values. We will see later in the article, how we can update the helm chart as per our usage.

Let's start with the actual work

Assuming that you've already created the AKS using UI or IaC, let's move ahead to connect with it and deploy Airbyte.

Steps to connect with AKS locally

Sign in to Azure in your terminal.
Set your specific Azure subscription where you have created your AKS cluster.

az account set --subscription <subscription_id>

Download the credentials to your cluster.

az aks get-credentials --resource-group <aks_rg_name> --name <aks_cluster_name> --overwrite-existing

Using Helm to deploy Airbyte

Install Helm in your system.
Run command

helm repo add airbyte https://airbytehq.github.io/airbyte/charts

You can get all the helm charts present via the ArtifactHub platform.

Now we will install Airbyte on our AKS cluster.

helm install airbyte airbyte/airbyte --namespace <namespace_name> --create-namespace --kubeconfig '<path_to_downloaded_cluster_credential_file>'

After running the above command, you can check your AKS cluster, in the namespace you can see your deployed Airbyte namespace.

To connect with your Airbyte locally, use below command.

kubectl port-forward pod/<airbyte_webapp_pod_name> 8080:8080 --namespace <namespace_name>

You can get the running pod name from AKS cluster --> Workloads --> Pods.

** Note that the pod name can be different every time the cluster scales up or down.

How to modify Airbyte pods configuration as per your need?

To modify, you just need to pull helm chart locally and alter the values file and push it again as an update to the cluster. Or you can use your altered Helm chart folder to directly push to your new cluster.

Steps to follow:

Pull Helm chart locally

helm pull --untar airbyte/airbyte

Open the unzipped airbyte folder.
From the list of files and folders, open values.yaml and update the configurations as per your need.
Use the local helm chart folder to install Airbyte on AKS.

helm install airbyte <path_to_local_helm_chart> --namespace <namespace_name> --create-namespace --kubeconfig '<path_to_downloaded_cluster_credential_file>'

Or say you have airbyte already functional in your AKS, then you can even simply upgrade the values.yaml file present in AKS.

helm upgrade --install airbyte airbyte/airbyte -f <path_to_values.yaml_file_present_in_local> --namespace <namespace_name>

Conclusion

You are set to scale Airbyte in AKS!

Integrating Terraform Cloud with GitHub Actions workflow

Aniket Kumar Sinha — Sun, 22 Oct 2023 15:55:26 +0000

What is Terraform Cloud?

Terraform Cloud is a web-based SaaS (Software as a Service) platform provided by HashiCorp, the creators of Terraform. It serves as a central hub for managing and automating infrastructure provisioning using HashiCorp's Infrastructure as Code (IaC) tool, Terraform. Terraform Cloud enhances the deployment workflow by offering features such as remote execution, collaboration, version control integration, and secure state management.

Why should we use Terraform Cloud over Terraform Open Source?

HashiCorp announced that now Terraform will not be fully open source. Link to article
Better and secure State management - HashiCorp provides feature of keeping the state file in TFC workspace and also provides an option to lock that state i.e, one cannot write upon the locked state.
Remote execution.
TFC has their own agents which works well with Terraform.
TFC provides HashiCorp's Sentinel policies which can help in integrating Policy-as-Code in our infrastructure.

Why integrating TFC with GH Actions workflow?

TFC can handle only Terraform steps/commands ,i.e, terraform init, terraform validate, terraform plan, terraform apply. So, if you are having any other step, or any of your jobs are using some other scripts, then you might need GitHub Action for running those scripts, which will run on either GitHub runners or Self hosted runners.

Integration Steps

Create a new Workspace in Terraform Cloud.
Choose API-driven workflow. We choose API-driven workflow because we are integrating TFC with GitHub Actions so the API token will be used by GitHub Actions for authentication in TFC workspace. Read more on API-driven workflow
Provide the workspace a name.
Tap on Create Workspace button.
Create a GitHub repository where you would be adding your TF code and GitHub Actions workflow files.
Let's now create the API token in TFC.
- Go to the home page of your TFC organization - https://app.terraform.io/app/ORGANIZATION_NAME/workspaces
- Open Settings.
- Choose API tokens section. There are 3 categories of token which one can generate:
  - User Token - In a TFC organization, many users can be a part. So, this token is generated by a single user.
  - Team Token - This token is generated by a team.
  - Organization Token - This token is generated for the whole organization.
All tokens have similar access, it's just that all users or teams should not have access to all tokens.
- We are creating the User token.
- Add a description and set the expiration time period of that token, and Generate the token.
- Copy and store the generated API token.
Now get back to your repository Settings->Secrets and variables->Actions. And tap on New repository secret to add the TFC API token as secret in the GitHub repository.
Add the secret name(prefer adding the same name as you added while creating the token. In the Secret section add the generated token. Click Add secret.
Add your SPN details (such as Client ID, Client Secret, Tenant ID) and subscription details in TFC workspace variables.
Now it's time to add some TF code in your GitHub repo along with the Terraform providers block with specific details of your TFC workspace. These details are important for your connection and deployment via TFC.

terraform {
  required_providers {
    azurerm = {
        source = "hashicorp/azurerm"
    }

    random = {
        source = "hashicorp/random"
    }
  }

  cloud {
    organization = "aniketkumarsinha"

    workspaces {
      name = "tfc-integration-with-gh-actions"
    }
  }
}

Time to work on the integrated GitHub Actions workflow creation! .github/workflows/deploy.yml

name: WORKFLOW

on:
  workflow_dispatch:

jobs:
  terraform:
    name: "Terraform"
    runs-on: ubuntu-latest
    steps:
    - name: Checkout
      uses: actions/checkout@v2

    - name: Setup Terraform
      uses: hashicorp/setup-terraform@v2
      with:
        terraform_version: 1.1.7
        cli_config_credentials_token: ${{ secrets. TF_API_TOKEN }}

    - name: Terraform Init
      id: init
      run: terraform init

    - name: Terraform Validate
      id: validate
      run: terraform validate -no-color

    - name: Terraform Plan
      id: plan
      run: terraform plan -no-color -input=false

    - name: Terraform Apply
      id: apply
      run: terraform apply -auto-approve -input=false

We created an integrated workflow file that connects the GitHub actions workflow with the TFC workspace run. When you run this workflow, you can see a simultaneous run over TFC workflow, both the runs are the same, it's just that the real TF code run is running on TFC workspace and a copy/replica is shown up in the GitHub actions workflow run.

Hola!! Pipeline running successfully ✅

You can check the TFC workflow run and you can also get that link from the Terraform Plan or Terraform Apply phase:

You have attained Integration Nirvana!

Checkout this repository:

aniketkumarsinha / tfc-integration-gh-action

Integrating Terraform Cloud with GitHub Actions workflow

What is Terraform Cloud?

Why should we use Terraform Cloud over Terraform Open Source?

HashiCorp announced that now Terraform will not be fully open source. Link to article
Better and secure State management - HashiCorp provides feature of keeping the state file in TFC workspace and also provides an option to lock that state i.e, one cannot write upon the locked state.
Remote execution.
TFC has their own agents which works well with Terraform.
TFC provides HashiCorp's Sentinel policies which can help in integrating…

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Aniket Kumar SinhaFollow

Cloud Consultant at Rapid Circle | Gold Microsoft Learn Student Ambassador | GDSC Lead'21

Migration of Terraform State file from Azure Storage Account to Terraform Cloud workspace

Aniket Kumar Sinha — Wed, 23 Aug 2023 18:00:06 +0000

What is Terraform State file?

Terraform stores information about your infrastructure in a State file. This state file keeps track of resources created by your configuration and maps them to real-world resources.

Migration Steps involves:

Download the latest State file from the Azure storage account, and rename it to terraform.tfstate.
Create a new directory/folder and create a new main.tf file with following configurations:

terraform {
 cloud {
  organization = "YOUR_TFC_ORGANIZATION"

  workspaces {
   name = "WORKSPACE_NAME"
  }
 }
}

Copy the downloaded state file into this new directory/folder in which you created the new main.tf file.
Make sure that the local version of Terraform match with the Terraform version of your Terraform Cloud workspace. If not install the required version.
Now run terraform init command. It will show you something similar:

Initializing Terraform Cloud...
Do you wish to proceed?
  As part of migrating to Terraform Cloud, Terraform can optionally copy your
  current workspace state to the configured Terraform Cloud workspace.

  Answer "yes" to copy the latest state snapshot to the configured
  Terraform Cloud workspace.

  Answer "no" to ignore the existing state and just activate the configured
  Terraform Cloud workspace with its existing state, if any.

  Should Terraform migrate your existing state?

  Enter a value:

Type "yes".

Now you can check over your TFC workspace and you should see the migrated state file.

After Migration:

Go back to your actual directory/folder containing your Terraform infrastructure code.
Add this same code block to your main.tf file or providers.tf file:

terraform {
 cloud {
  organization = "YOUR_TFC_ORGANIZATION"

  workspaces {
   name = "WORKSPACE_NAME"
  }
 }
}

Run terraform init and terraform plan commands or initiate a run over Terraform Cloud. You should see that Terraform Plan phase is not showing any changes to be done.

You have successfully migrated your TF state file from storage account to TFC workspace.

Note:

One TFC workspace can hold only a single state file. If you have multiple environments with multiple state files, you need to create a separate workspace for individual environment's state files respectively and follow the same migration steps.

Checkout this repository:

aniketkumarsinha / migration-of-terraform-state-file-to-terraform-cloud-workspace

Migration of Terraform State file from Azure Storage Account to Terraform Cloud workspace

What is Terraform State file?

Terraform stores information about your infrastructure in a State file. This state file keeps track of resources created by your configuration and maps them to real-world resources.

Migration Steps involves:

Download the latest State file from the Azure storage account, and rename it to terraform.tfstate.
Create a new directory/folder and create a new main.tf file with following configurations:

terraform {
 cloud {
  organization = "YOUR_TFC_ORGANIZATION"

  workspaces {
   name = "WORKSPACE_NAME"
  }
 }
}

Copy the downloaded state file into this new directory/folder in which you created the new main.tf file.
Make sure that the local version of Terraform match with the Terraform version of your Terraform Cloud workspace. If not install the required version.
Now run terraform init command. It will show you something similar:

Initializing Terraform Cloud
Do you wish

…

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Aniket Kumar SinhaFollow

Cloud Consultant at Rapid Circle | Gold Microsoft Learn Student Ambassador | GDSC Lead'21

Implementing Policy-as-Code to Terraform workflow using Hashicorp Sentinel

Aniket Kumar Sinha — Tue, 13 Jun 2023 07:45:34 +0000

In this blog post, I will show you how to implement Policy-as-Code (PaC) to your Terraform workflow using Hashicorp Sentinel. PaC is a way of defining and enforcing policies for your infrastructure as code, which can help you ensure compliance, security and best practices across your organization. Sentinel is a language and framework for writing and applying policies to Terraform and other Hashicorp products.

Why use Policy-as-Code?

Policy-as-Code has many benefits for managing your infrastructure as code. Some of them are:

It allows you to codify your policies and store them in version control, which makes them easier to track, review and audit.
It enables you to apply your policies consistently and automatically across your environments, which reduces human errors and increases efficiency.
It empowers you to enforce your policies at different stages of your workflow, such as plan, apply or destroy, which gives you more control and visibility over your infrastructure changes.
It supports you to write policies that are flexible and expressive, which can handle complex scenarios and logic.

How to use Sentinel with Terraform?

Sentinel integrates seamlessly with Terraform Cloud and Terraform Enterprise, which are platforms for collaborating and automating your Terraform workflows. To use Sentinel with Terraform, you need to:

Write your policies in Sentinel language and save them as .sentinel files in your repository.
Configure your Terraform organization and workspace to enable Sentinel and specify which policies to apply.
Run your Terraform commands as usual and see how Sentinel evaluates your policies against your configuration and state.

Sentinel policies can be applied at different levels of granularity, such as organization, workspace or run. You can also use different enforcement modes, such as advisory, soft-mandatory or hard-mandatory, depending on how strict you want your policies to be.

Advisory: Failed policies never interrupt the run, just post a warning.
Soft-mandatory: lets an organization owner or a user with override privileges proceed with the run in the event of failure. Terraform Cloud logs all overrides.
Hard-mandatory: requires that the policy passes. If a policy fails, the run stops. You must resolve the failure to proceed.

Learn more about Sentinel: Introduction to Sentinel, HashiCorp Policy as Code Framework By Armon Dadgar, CTO Hashicorp.

Terraform without Sentinel:

Terraform with Sentinel:

We are using a policy to restrict VM size, which basically means that if the VM size mentioned in our infrastructure matches the list VM sizes mentioned in our policy, then the Policy checks will pass and proceed to Apply phase, otherwise it will stop with the error.

And we are adding this policy directly to Terraform Cloud via UI.

So go to your workspace page in Terraform Cloud - https://app.terraform.io/app/{username}/workspaces
Move in to Settings from left pane.
Move to Policies tab from left pane and tap on 'Create a new policy' button. This will lead to the page where you can add your sentinel policy code.
Finally Create a new policy
- Choose Sentinel in Policy framework.
- Add the policy name.
- Add the description.
- Choose the enforcement level (advisory, soft-mandatory or hard-mandatory)
- Add the Policy Code. We are using this code:
- For now keep the Policy set as blank because we haven't created any policy set yet.
- And then tap on Create policy button.
It's time to create a Policy Set. Policy sets are groups of policies which may be enforced on workspaces. In settings itself, move to Policy Set from left pane, and click on 'Create a new policy set'.
- In Connect to VCS, choose 'No VCS Connection', as we not using any GitHub repo for our policy. We can also use any repository containing policies.
- It will directly lead you to Configure settings page.
- Choose Sentinel in Policy framework.
- Add a name.
- Add description to policy set.
- In Scope of policy, choose the scope according to your need. We are restricting the scope to selected workspace.
- Choose the workspace. We are using an already created workspace. To learn how to create a workspace and deploy to Azure using the workspace, check out this blog: Deploy Azure Infrastructure using Terraform Cloud
- And tap on to Connect policy set button to create the policy set.
- We are done with creation of the policy set.
Move back to policies to add this created policy set to your policy. And tap on Update policy button.

So, finally we are done with adding our sentinel policy to Terraform Cloud.

It's time to check the workflow.
So, in our infra, we have used VM with size, "Standard_D1_v2", which is a part of allowed VM sizes, so let's see the workflow outcome.

We can that we have new phase named as 'Sentinel policies passed', and since the infra matches the policy condition it passes and proceeded to Apply phase.

Let's try with some different VM size.
We are changing the VM size to "Standard_D2_v5" which is not a part of allowed VM sizes, and running the workflow.

We can see that the sentinel policy phase failed and stop the workflow there itself because we applied enforcement mode as hard-mandatory.

Error message: Resource azurerm_virtual_machine.vm[0] has attribute vm_size with value Standard_D2_v5 that is not in the allowed list: ["Standard_A1" "Standard_A2" "Standard_D1_v2" "Standard_D2_v2"]

Let's me just give you a small brief that how the policies are working. So, the Plan phase generates the mock files (containing the output of Plan phase) which is used as input to Sentinel policy phase, and then the policy phase checks with the policy and accordingly pass or fail.

You can even download those mock files to see the results.

If you want to learn how to use Terraform Cloud to deploy over Azure, checkout this blog:

Article No Longer Available

You can get the whole Policy-as-Code from this repo:

aniketkumarsinha / terraform-sentinel-policy

This Project uses Terraform Sentinel to apply Policy-as-Code on Terraform Workflow. Get more details:

Implementing Policy-as-Code to Terraform workflow using Hashicorp Sentinel

In this project, we are implementing Policy-as-Code (PaC) to our Terraform workflow using Hashicorp Sentinel. PaC is a way of defining and enforcing policies for your infrastructure as code, which can help you ensure compliance, security and best practices across your organization. Sentinel is a language and framework for writing and applying policies to Terraform and other Hashicorp products.

Why use Policy-as-Code?

Policy-as-Code has many benefits for managing your infrastructure as code. Some of them are:

It allows you to codify your policies and store them in version control, which makes them easier to track, review and audit.
It enables you to apply your policies consistently and automatically across your environments, which reduces human errors and increases efficiency.
It empowers you to enforce your policies at different stages of your workflow, such as plan, apply or destroy, which gives you more control…

View on GitHub

Share if your like the blog and follow for more!!

Aniket Kumar SinhaFollow

Cloud Consultant at Rapid Circle | Gold Microsoft Learn Student Ambassador | GDSC Lead'21

Deploy Azure Infrastructure using Terraform Cloud

Aniket Kumar Sinha — Sun, 11 Jun 2023 07:21:34 +0000

Note: You can get the whole code from this repository: aniketkumarsinha/azure-terraform-infrastructure

What is Terraform?
Terraform is an infrastructure as code tool that lets you define both cloud and on-prem resources in human-readable configuration files that you can version, reuse, and share.

Terraform Flow

First you have the terraform code.
Then we have Terraform Plan phase. The terraform plan command creates an execution plan, which lets you preview the changes that Terraform plans to make to your infrastructure.
Terraform Apply phase executes the actions proposed in a Terraform plan.
And everything gets deployed over the CSP, here Azure.

What is Terraform Cloud?
Terraform Cloud is a managed service offering by HashiCorp that eliminates the need for unnecessary tooling and documentation for practitioners, teams, and organizations to use Terraform in production. It allows you to provision infrastructure in a remote environment that is optimized for the Terraform workflow.

In this blog, we will be creating Azure Infrastructure using Terraform and will be deploying it over to Azure using Terraform Cloud.

Infrastructure Code
We are creating a VM and resources related to it.

Setting up Terraform Cloud

Create Terraform Cloud Account - Terraform Cloud
Create a Project in Terraform Cloud:
Create a Workspace.
- Choose Version control workflow
- Connect to a version control provider
- Choose your Azure Infrastructure repository from your repository list. You can check the advance settings if you want to configure the workflow.
- Tap on Create Workspace button to create your workspace in terraform cloud Or Start new run from workspace overview page.
You can directly start your plan phase.
You can verify in your projects page that your workspace has been created.
Open your workspace to start new run.
Choose your run type and start run.
Ouch!! Errors!! We are getting error in provider phase. The reason behind this is that we have authorized our infrastructure to connect and write over our Azure. We will be creating an App provide all the necessary details to our infrastructure.

Authorizing Terraform Infrastructure to write over Azure

We are creating an App over Azure to authorize using Client Id, Client Secret and Tenant Id. So in your Azure Portal move into Azure Active Directory, and open App registrations from left pane, And add a new registration.
Add your App details and register.
So we have finally created our app.
To connect our Infrastructure we need 4 details
- Client Id
- Client Secret
- Tenant Id
- Subscription Id We would be getting this one by one.
Application (client) ID is Client Id. Directory (tenant) ID is Tenant Id.
To get the Client Secret, we first need to create the secret.
- Add description and expiry of this secret which you're creating.
- Copy this value under Value column, and save it somewhere as we wouldn't be able to access this later. This is our Client secret.
Search Subscription from search box and open your subscription. Copy your subscription id. So now we have all the required values.
Let's add these values in our Infrastructure.
- In the provider block add all four details. We would be saving the values in Terraform Cloud variables for security purpose.

provider "azurerm" {
  features {}

  skip_provider_registration = "true"

  # Connection to Azure
  subscription_id = var.subscription_id
  client_id = var.client_id
  client_secret = var.client_secret
  tenant_id = var.tenant_id
}

Add variables in Variables page.
- In Key add the words with var, i.e., var.key, and in Value add required Ids' and Secret.

Let's rerun the workflow!

Ohhhhh!!!! ERROR AGAIN!!!!

But we are still left with some more code :P
We need to add variables.tf file mentioning about these variables.

And now finally we can get the results from Plan and Apply phase. Let's rerun the pipeline.

Wohooo!! Our Plan phase ran successfully:
Expand Plan phase to check what resources are getting created. And if every configuration is fine then tap on Confirm & Apply button at the end of phase. So by default the Apply phase does not run automatically, we need manual approval, this is to make sure that someone checks the Plan output and verifies everything and then accordingly approve for Apply or reject.
Error again 🫠
It seems our Azure app don't have permission to add anything. Let's provide the contributor role to our app.
- Under Subscription, got to Access Control (IAM) and Add a role there.
- Add a Contributor role under Privileged administrator roles.
- Under Members tab, select our app as member.
- And then tap on Review+Assign. So now our App has contributor role and can make changes over Azure subscription.
Rerun the pipeline. And wollaahh!! Everything ran successfully!

Let's confirm over our Azure Portal too.
Yes we can see all our resources present under our subscription.

🤩🤩🤩🤩🤩🤩🤩

Damn!!!! We learnt so many things today. We first created the Terraform Infrastructure, setup our Terraform Cloud profile and then used it to deploy resources over Azure too. Now you can say you're a pro in Terraform and Terraform Cloud.

Let me provide you a bonus happiness. So the project which we configured over Terraform Cloud, automatically runs the workflow any branch is merged to the main branch or any new pushes are done to main branch.

You can get the whole Infrastructure as Code from this repository:

aniketkumarsinha / azure-terraform-infrastructure

Deploy Azure Infrastructure using Terraform Cloud

Note: Tried of creating this doc as a demo with all process/steps in creating this project

What is Terraform?

Terraform is an infrastructure as code tool that lets you define both cloud and on-prem resources in human-readable configuration files that you can version, reuse, and share.

Terraform Flow

First you have the terraform code.
Then we have Terraform Plan phase. The terraform plan command creates an execution plan, which lets you preview the changes that Terraform plans to make to your infrastructure.
Terraform Apply phase executes the actions proposed in a Terraform plan.
And everything gets deployed over the CSP, here Azure.

What is Terraform Cloud?

Terraform Cloud is a managed service offering by HashiCorp that eliminates the need for unnecessary tooling and documentation for practitioners, teams, and organizations to use Terraform in production. It allows you to provision infrastructure in a remote environment…

View on GitHub

Share if your like the blog and follow for more!!

Aniket Kumar SinhaFollow

Cloud Consultant at Rapid Circle | Gold Microsoft Learn Student Ambassador | GDSC Lead'21

Creating Azure Virtual Machine using PowerShell

Aniket Kumar Sinha — Thu, 21 Jul 2022 05:03:34 +0000

What is Virtual Machine?
Virtual machine is a virtual environment over your a system. Assume you have a Linux OS on your system, but you want to use Windows for some specific functionality, but you don't want to install it over your system. What you can do is, just create a VM (Virtual Machine) with Windows OS and use in whatever way you want virtually over your system.
So basically, a virtual machine (VM) is a virtual environment that functions as a virtual computer system with its own CPU, memory, network interface, and storage, created on a physical hardware system.

What is PowerShell?
PowerShell is a cross-platform task automation solution made up of a command-line shell, a scripting language, and a configuration management framework.

So, now let's create a VM using PowerShell.

Before starting, you need to install some modules from the PowerShell Gallery:

Az.Accounts - Used to connect to Azure Account through PowerShell.
Az.Resources - Used to create/get the Resource Group for out VM.
Az.Compute - Used to create/connect the Virtual Machine.

Use the following syntax to install these modules:

Install-Module -Name ModuleName

Let's start by creating a PowerShell file first. Open Visual Studio Code or PowerShell ISE. You can install the PowerShell extension in the VS Code. Create a PowerShell file with extension .ps1. For example VMusingPS.ps1.

Now we need to connect to our Azure account using PowerShell script. Run the following command in VS Code.

Connect-AzAccount

Select the command and then tap on the key F8 to run this.
This command will open up an interface in your browser to sign-in to your Azure account.

To confirm your connection, run the command:

Get-AzContext

This command will show you some similar results to this, confirming your account and subscription.

If you want, you can create a new Resource Group for your VM using the command:

New-AzResourceGroup -Name "VM_RG" -Location "CentralIndia"

Or use any existing Resource Group.

I am using the existing Resource Group named as "VM_RG".
Run the following command to create a Virtual Machine machine using PowerShell:

New-AzVM -Name "VMusingPS" -ResourceGroupName "VM_RG" -Location "CentralIndia" -Credential (Get-Credential)

Since the VM needs a credential for it's access, so after running this command, it will ask for the username and password for your VM. Set your credentials and press Enter, and done.

You can confirm by checking your mentioned Resource Group, it will show your Virtual Machine there.

You have successfully created an Azure Virtual Machine using PowerShell script.

Here's the full code:

Now you can connect/start your VM using RDP: Connecting to Windows Virtual Machine created on Azure using RDP

Docs on the commands used:

Hurray🥳
Enjoy using your VM now!

Aniket Kumar SinhaFollow

Cloud Consultant at Rapid Circle | Gold Microsoft Learn Student Ambassador | GDSC Lead'21

Connecting to Windows Virtual Machine created on Azure using RDP

Aniket Kumar Sinha — Thu, 21 Jul 2022 04:40:42 +0000

Let's see how we can start/connect to our Virtual Machine.

On the Virtual Machine page on Azure Portal, you can see this bar.

Here you have the option of Connect. So, you need to tap on the arrow with Connect and choose the RDP option from the dropdown menu.

Connect with RDP interface will open up, and now we need to download the RDP file using the Download RDP File button.

Now in your downloads folder, you can see a .rdp file with the name of your VM.

Just open that file.

Remote Desktop Connection interface will open up, and you need to tap on the Connect button to connect to your VM.

Windows Security interface will open up. But you need to tap on More choices option given below. And there you need to choose Use a different account option.

Now on the new interface, you need to add the username and password which you set while creating the VM. And then tap on OK button below.

If this kind of interface comes up, just tap Yes below.

Now you can see the Virtual Machine is opening up.

You can enlarge the VM and make it full screen and use it like your own system.

Yayy!
You have successfully connected to your Virtual Machine.

Enjoy your new system 🎉

Creating Virtual Machine on Azure Portal

Aniket Kumar Sinha — Wed, 29 Jun 2022 15:57:10 +0000

What is Virtual Machine?

Virtual machine is a virtual environment over your a system. Assume you have a Linux OS on your system, but you want to use Windows for some specific functionality, but you don't want to install it over your system. What you can do is, just create a VM (Virtual Machine) with Windows OS and use in whatever way you want virtually over your system.
So basically, a virtual machine (VM) is a virtual environment that functions as a virtual computer system with its own CPU, memory, network interface, and storage, created on a physical hardware system.

So, let's create a VM on Azure.

Move to the Azure Portal, and tap on the + icon with text Create a resource.

You will get similar interface show below. Choose the Virtual machine from the given option.

This interface will open up.

Let's now examine each option given.

Let the Subscription be as it is. And in Resource group, let's create a new one using the Create new option shown in blue below the input bar.

I am creating a Resource group named as VM_RG.

Now the question arise that, What is a Resource group?
So, a resource group is a container that holds related resources for an Azure solution. The resource group can include all the resources for the solution, or only those resources that you want to manage as a group.

The time to give our Virtual Machine a name.

In the Virtual machine name, I am giving the VM a name as VMonPortal.
Under Region, choose the region which is nearest to you. I am choose the region as Central India as it's nearest to me.
Keep the Availability option as No infrastructure redundance required.
Let the Security type remain as Standard.
Under Image choose the operating system which you want in your virtual machine. I am choosing Windows 11 Pro.
Leave the Azure Spot instance as unchecked.
Under Size, choose the size which suites your pocket. I am choosing the lowest one, i.e, Standard_D2s_v3.

Time to set the username and password of our VM.

You can see that there are some criteria related to the username and password, so choose the username and password accordingly.
And do remember this username and password, because this will help you to signin to your VM.

Leave the Inbound port rules section as it is.

Check mark the licensing confirmation.

Now your interface should look similar to this, with similar values.

Now tap on Next: Disks > button below.

Now this interface will open up which basically ask for the data disks you want in your VM.

I am keeping the OS disk type as Standard SSD, leaving the other items same.

If you want you add a data disk, but I am not adding any, leaving the other items as it is.

Now tap on the Next: Networking > tab below.

I am keeping all the items as it is, in the Networking tab.

Now directly tap on Review + Create button below.

The Review + create tab will open up with some information and costing of your VM.

Now just tap on the Create button below.

This will create the VM with the configurations you mentioned.
The creation process may take some time.

This kind of message can come up on your screen that the deployment is complete.

Now tap on Go to resource button.

The portal for the virtual machine will open up.

Awesome!!
We just now created our Virtual Machine on Azure Portal.

But wait!!!!
How to use the Virtual Machine now.

Let's see how we can start our Virtual Machine.

You can see this bar.

Here you have the option of Connect. So, you need to tap on the arrow with Connect and choose the RDP option from the dropdown menu.

Connect with RDP interface will open up, and now we need to download the RDP file using the Download RDP File button.

Now in your downloads folder, you can see a .rdp file with the name of your VM.

Just open that file.

Remote Desktop Connection interface will open up, and you need to tap on the Connect button to connect to your VM.

Windows Security interface will open up. But you need to tap on More choices option given below. And there you need to choose Use a different account option.

Now on the new interface, you need to add the username and password which you set while creating the VM. And then tap on OK button below.

If this kind of interface comes up, just tap Yes below.

Now you can see the Virtual Machine is opening up.

You can enlarge the VM and make it full screen and use it like your own system.

Yayy!
Now finally you have created your own Virtual Machine on Azure Portal and used it too.

Enjoy your new system 🎉

Updating React App deployed on Firebase

Aniket Kumar Sinha — Tue, 14 Jun 2022 17:32:47 +0000

Be sure that you've deployed your app on Firebase, if not done then follow this blog: How to deploy your React app on Firebase?

Make all the changes and save them in your React App.

Run the following commands in the terminal:

$ npm run build
$ firebase deploy

It's Done!
Your app is updated.

Happy Learning!

How to deploy your React app on Firebase?

Aniket Kumar Sinha — Tue, 14 Jun 2022 17:25:16 +0000

Assuming you have created an account on Firebase, let’s move forward to creating the project on the Firebase console to the deployment of your React app on Firebase.

Create Firebase Project
Sign in to Firebase and move to console through the button “Go to console” present at the top right corner of the website. The console panel will open up. Tap on the “Add project” tab there and create the project with any desired name. The project overview window will open up as shown below.

Tap on the web icon, just beside the android icon present there. Register your app there with a suitable name. Tick the setup of Firebase hosting setup there.

Just tap Next on the further proceedings and move to Git Bash to your project directory. Run command:

$ npm install -g firebase-tools

Then you need to log in to firebase through your bash.

$ firebase login

Allow the asked permission by running y or yes. It will open the sign-in window. Just sign in there with your account. Coming back to bash. Run command:

$ npm run build

Then run the command:

$ firebase init

Answer the questions as mentioned below.

? Are you ready to proceed? Yes
? Which Firebase CLI features do you want to set up for this folder? Press Space to select features, then Enter to confi
rm your choices. Hosting: Configure and deploy Firebase Hosting sites
? Please select an option: Use an existing project
? Select a default Firebase project for this directory: mylinks-71d4a (mylinks)
? What do you want to use as your public directory? build
? Configure as a single-page app (rewrite all urls to /index.html)? Yes
? Set up automatic builds and deploys with GitHub? No
? File build/index.html already exists. Overwrite? No

These questions will be asked to you and you need to answer as given above. In the question “Select a default Firebase project for this directory”, choose the project which you created for the web app.

The next step is to deploy your app to firebase.

$ firebase deploy

Hola! Your React app is deployed to Firebase. You can get its link either from the Git Bash itself. It will show up there as “Hosting URL” ending with “.web.app” or in the project on Firebase, go to Hosting tab, there too you will find your app URL.

Now the question arises, how to update your already deployed app?
Follow the following steps:

Make and save changes in your react app.
Run the following commans:

$ npm run build
$ firebase deploy

This will update your deployed app.

Happy Learning!

How to get Microsoft Azure Fundamentals Certified?

Aniket Kumar Sinha — Fri, 02 Jul 2021 04:47:48 +0000

I recently passed the Microsoft Azure Fundamentals Certification Examination(AZ 900). It was an awesome learning journey and I learned a lot about Azure and Cloud Computing. This article is related to the same. What is Microsoft Certified: Azure Fundamentals examination and how to prepare for it.

What is Cloud Computing?
Cloud computing is the delivery of computing services — including servers, storage, databases, networking, software, analytics, and intelligence — over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. You typically pay only for cloud services you use, helping lower your operating costs, run your infrastructure more efficiently and scale as your business needs change.

What is Azure?
Azure is a cloud computing platform with an ever-expanding set of services to help you build solutions to meet your business goals. The Azure cloud platform is more than 200 products and cloud services designed to help you bring new solutions to life — to solve today’s challenges and create the future. Build, run and manage applications across multiple clouds, on-premises and at the edge, with the tools and frameworks of your choice.
To become Microsoft certified in Azure Fundamentals, you need to pass the AZ-900 Examination.

The AZ-900 is the exam needed to get the Azure Fundamentals certification. The exam is intended for candidates who are just beginning to work with cloud-based solutions and services or are new to Azure.

How to prepare for AZ 900 Examination?
Microsoft Learn is an amazing platform to learn about Microsoft technologies. For Azure too, you should visit Microsoft Learn. I am mentioning the important links related to this Certification and also links to the learning paths which you need to prepare for this examination:

You can practice through practice tests like Mindhub’s AZ-900: Microsoft Azure Fundamentals Microsoft Official Practice Test and Whizlabs’ Microsoft Azure Exam AZ-900 Certification Practice Tests.

What is the question pattern and marks distribution of the AZ 900 examination?
According to the most updated terms and conditions, the following is the exam skill outline and question distribution:

Describe cloud concepts (20–25%)
Describe core Azure services (15–20%)
Describe core solutions and management tools on Azure (10–15%)
Describe general security and network security features (10–15%)
Describe identity, governance, privacy, and compliance features (20–25%)
Describe Azure cost management and Service Level Agreements (10–15%)

The questions are mainly theory based and are majorly MCQ based with around 40–60 questions which are to be answered in 60 minutes.

So, this is it. If you are done with above mentioned stuff, you are good to go for the AZ-900 examination.

All the best!