Azure DevOps RealTime Project

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Advance AzureDevOps Pipeline Stages and Deployment

In some companies, a dedicated release team handles new code versions. For example, if the current stable version is 23.0.0, they create a release candidate version 23.0.0.0-RC1. If additional changes are needed, they may release RC2 or RC3. Once testing is complete, it becomes the stable version 23.0.0.0. If a bug is found after release, a hotfix version is issued.

Continuous Delivery:

• After successful integration testing, the application is automatically deployed to lower environments like development or staging.

Continuous Deployment:

• If everything works well in the previous stages, the application is deployed to higher environments like production. Many organizations prefer manual approval before production deployment.

So, we will Set up an Azure DevOps pipeline by creating a virtual machine (VM) as a self-hosted agent Configure the VM with necessary tools and integrate it with Azure DevOps.

Conclusion:

• In the next session, we will cover infrastructure pipelines using Terraform.

• We will also discuss SAST (Static Application Security Testing) and DAST in more detail.
  
  Stage 1: Adding SonarQube Integration

  • Set up SonarQube in Azure DevOps using service connections.

  • Add a SonarQube stage in the pipeline and configure it with necessary tokens.

  Stage 2: Building and Uploading Artifacts to JFrog

  • Create a secure file for storing sensitive information like credentials.

  • Build the project using Maven and store the artifacts in JFrog.

  Stage 3: Copying Artifacts to Azure Blob Storage

  1. Create an Azure Storage Account.

  2. Add a container named artifacts.

  3. Create a service principal in Azure and use it for authentication.

  4. Add storage account keys as pipeline variables.

  Stage 4: Pushing Docker Images to ACR and Docker Hub

  1. Create an Azure Container Registry (ACR).

  2. Set up service connections for ACR and Docker Hub.

  3. Push the built Docker image to both registries.

  Stage 5: Deploying to Azure Container Instance (ACI)

  • Use the pipeline to deploy the Docker image to ACI.

  Stage 6: Setting Up Staging and Production Environments

  1. Create two Ubuntu servers on AWS (one for staging and one for production).

  2. Configure DNS records using Route 53.

  3. Register the servers as deployment targets in Azure DevOps.

  Stage 7: Final Deployment and Testing

  • Deploy the application to staging and production.

  • Perform DAST (Dynamic Application Security Testing) using tools like ZAP.

  • Verify the deployment by accessing the application via the configured URLs.

  Stage 8: Handling Errors and Debugging

  • Show how to debug issues by checking logs and error messages.

  • Modify the Dockerfile to use the correct Java version if needed.