Provisioning and configuring target environments as part of Release Pipeline in Azure DevOps

Provisioning and configuring target environments as part of Release Pipeline in Azure DevOps

Provisioning and configuring target environments as part of a release pipeline in Azure DevOps involves several steps depending on the environment type (on-premises servers, IaaS, PaaS, FaaS, clusters) and the service connections required.

Here's a structured guide.

1. On-Premises Servers

Prerequisites

1. Install and configure a self-hosted Azure DevOps agent on the on-premises server.

2. Ensure network connectivity to Azure DevOps.

Steps

1. Create Service Connection: Use a service connection (e.g., SSH or Windows Machine File Copy) for deployment tasks.

2. Provisioning:

   • If provisioning new servers, use infrastructure automation tools like Ansible, Chef, or PowerShell DSC.

   • Add these scripts in Azure Pipelines or as part of a task group.

3. Configuration:

   • Use deployment tasks like "SSH", "Windows Machine File Copy", or "PowerShell on Target Machines".

   • Deploy application packages, update configurations, and restart services as required.

2. Infrastructure as a Service (IaaS)

Prerequisites

1. A cloud subscription (Azure, AWS, GCP).

2. Proper IAM roles or service principal access.

Steps

1. Create Service Connection: Configure service connections for the specific cloud provider (Azure Resource Manager, AWS, GCP).

2. Provisioning:

   • Use tools like Terraform, ARM Templates, or Azure CLI to create virtual machines.

   • Define these templates in a repository and integrate them into your pipeline.

3. Configuration:

   • Configure the machines using tools like Ansible, Chef, or custom scripts.

   • Use pipeline tasks to run configuration scripts.

3. Platform as a Service (PaaS)

Prerequisites

Access to the target PaaS resource (e.g., App Service, Database as a Service).

Steps

1. Create Service Connection: Configure a service connection for Azure Resource Manager or other PaaS management interfaces.

2. Provisioning:

   • Use Azure CLI, PowerShell, or ARM templates to create resources (e.g., web apps, databases).

   • Incorporate these scripts into your pipeline.

3. Configuration:

   • Use Azure App Service tasks for web apps.

   • Use database deployment tasks for DBs.

   • Set up configuration settings and deployment slots as needed.

4. Function as a Service (FaaS)

Prerequisites

Access to the target FaaS resource (e.g., Azure Functions, AWS Lambda).

Steps

1. Create Service Connection: Use Azure Resource Manager or other cloud-specific connections.

2. Provisioning:

   • Use templates (e.g., Azure ARM, SAM for AWS) to define the FaaS environment.

   • Deploy the function code using Azure Functions task or CLI.

3. Configuration: Configure triggers, bindings, and environment variables.

5. Clusters (e.g., Kubernetes)

Prerequisites

1. Access to the Kubernetes cluster.

2. kubectl configured or Helm chart repository prepared.

Steps

1. Create Service Connection: Use Kubernetes or Helm service connection.

2. Provisioning:

   • Use Terraform or Kubernetes manifests to create namespaces and resources.

   • Include these steps in your pipeline.

3. Configuration: Use kubectl tasks or Helm tasks to deploy and configure resources.

6. Service Connections

General Steps

1. Go to Project Settings > Service Connections.

2. Add a New Service Connection:

   • Choose the appropriate type (Azure Resource Manager, Kubernetes, AWS, etc.).

   • Authenticate using the required credentials (Service Principal, Access Key, etc.).

3. Grant Access: Provide pipeline access to the service connection.

Pipeline Example

Here’s an example YAML snippet for a release pipeline that provisions and configures a Kubernetes cluster:

xxxxxxxxxx
23
1
stages:
2
- stage: Deploy
3
  jobs:
4
  - job: Provision
5
    steps:
6
   - task: Kubernetes@1
7
      inputs:
8
        connectionType: 'Azure Resource Manager'
9
        azureSubscriptionEndpoint: '<ServiceConnection>'
10
        resourceGroup: '<ResourceGroup>'
11
        clusterName: '<ClusterName>'
12
        command: 'apply'
13
        arguments: '-f deployment.yaml'
14
  - job: Configure
15
    steps:
16
   - task: HelmDeploy@0
17
      inputs:
18
        connectionType: 'Kubernetes Service Connection'
19
        kubernetesServiceEndpoint: '<ServiceConnection>'
20
        namespace: '<Namespace>'
21
        chartType: 'FilePath'
22
        chartPath: 'chart/'
23
        releaseName: 'myrelease'

Summary

By following this approach, you can streamline provisioning and configuration for different target environments as part of your Azure DevOps release pipeline.