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Azure Data Processing Application CI/CD Pipes in Part 1: Container Instance Deployment

Automating the process of creating and deploying resources in Azure and other cloud platforms can prove beneficial, as it decreases the need for manual labor. However, it's often necessary to modify these resources due to changes in requirements, which can lead to substantial effort in...

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Azure Data Processing Application CI/CD Pipelines: Initial Setup with Container Instances (Part 1)
Azure Data Processing Application CI/CD Pipelines: Initial Setup with Container Instances (Part 1)

Azure Data Processing Application CI/CD Pipes in Part 1: Container Instance Deployment

In this article, we'll guide you through the process of automating a Continuous Integration/Continuous Deployment (CI/CD) pipeline to deploy an Azure Container Registry (ACR), build and push a Docker image, create an Azure Container Instance (ACI), and enable managed identity access to Azure Key Vault. We'll be using GitHub Actions and Azure CLI.

Setting up Your Azure Resources

Before you begin, you'll need an Azure account and the Azure CLI installed on your local system or through the Cloud Shell in the Azure portal. To start, you'll need to:

  1. Clone the repository containing your application code.
  2. Create Azure resources like a resource group, a storage account with a blob container, and a key vault using the Azure Portal.

Writing the GitHub Actions Workflow

Next, you'll write a YAML GitHub Actions workflow that runs the Azure CLI commands sequentially or in individual jobs, using the official action for authentication.

Key steps include:

  • Authenticate with Azure in GitHub Actions using action (which supports service principal or OIDC).
  • Use to create the container registry.
  • Use or Docker CLI to build and push your image.
  • Use to create the container instance with managed identity enabled ().
  • Use to grant the container identity access to secrets in Key Vault.

Here's an example outline of a GitHub Actions workflow:

```yaml name: Deploy Containerized App

on: push: branches: [main]

jobs: deploy: runs-on: ubuntu-latest steps: - name: Checkout code uses: actions/checkout@v3

```

Additional Details

  • You must create a user-assigned managed identity or use the system-assigned one created on container creation; get its object ID to assign Key Vault access policy.
  • Store sensitive data such as Azure service principal credentials in GitHub repository secrets (e.g., ) for secure login.
  • Use Azure CLI extensions if necessary (like ) based on the service used.
  • For more advanced scaling or runner automation, Azure Container Apps can be configured as GitHub Actions runners to optimize costs and scaling dynamically[1].
  • You can find detailed examples of building, pushing Docker images, and deploying to Azure via GitHub Actions in Microsoft’s docs and community tutorials[5][3].
  • For enabling managed identity access to Key Vault, is key to grant permissions to the container’s identity.

This approach automates the entire workflow in a CI/CD pipeline triggered by GitHub pushes, enabling seamless container deployment and secure secret management in Azure. The pipeline runs when changes are pushed to the 'main' branch due to a branch trigger set up in the workflow. In the Logs pane, you may see the script running in the console.

For further learning about GitHub Actions and Bicep, refer to the provided resources from the MS Learn platform. You can also use Azure Storage Explorer to make it easier to upload files and verify the application's correct functioning. After the script completes, a new file should be present in the blob container's 'output' folder. To start the container instance, go to the Azure portal and click on it.

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