Creating a CI/CD pipeline with Azure Pipelines and Google Kubernetes Engine

Last reviewed 2022-11-29 UTC

---

This tutorial shows how to use Azure Pipelines, Google Kubernetes Engine (GKE), and Google Container Registry to create a continuous integration/continuous deployment (CI/CD) pipeline for an ASP.NET MVC web application. For the purpose of this tutorial, you can select between two example applications:

• An ASP.NET Core web application that uses .NET 6.0 and runs on Linux
• An ASP.NET MVC web application that uses .NET Framework 4 and runs on Windows

The CI/CD pipeline uses two separate GKE clusters, one for development and one for production, as the following diagram shows.

At the beginning of the pipeline, developers commit changes to the example codebase. This action triggers the pipeline to create a release and to deploy it to the development cluster. A release manager can then promote the release so that it's deployed into the production cluster.

This tutorial is intended for developers and DevOps engineers. It assumes that you have basic knowledge of Microsoft .NET, Azure Pipelines, and GKE. The tutorial also requires you to have administrative access to an Azure DevOps account.

Objectives

• Connect Google Container Registry to Azure Pipelines for publishing Docker images.
• Prepare a .NET sample app for deployment into GKE.
• Authenticate securely against GKE without having to use legacy authentication.
• Use Azure Pipelines release management to orchestrate GKE deployments.

Costs

In this document, you use the following billable components of Google Cloud:

• GKE
• Cloud Load Balancing
• Cloud Storage (for Container Registry)

To generate a cost estimate based on your projected usage, use the pricing calculator. New Google Cloud users might be eligible for a free trial.

When you finish the tasks that are described in this document, you can avoid continued billing by deleting the resources that you created. For more information, see Clean up.

Check the Azure DevOps pricing page for any fees that might apply to using Azure DevOps.

Before you begin

It's usually advisable to use separate projects for development and production workloads so that Identity and Access Management (IAM) roles and permissions can be granted individually. For the sake of simplicity, this tutorial uses a single project for both GKE clusters, one for development and one for production.

1. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

2. Make sure that billing is enabled for your Google Cloud project.

3. Make sure you have an Azure DevOps account and have administrator access to it. If you don't yet have an Azure DevOps account, you can sign up on the Azure DevOps home page.

Note: You can either use a command-line Git client or Visual Studio to follow this tutorial. If you use Visual Studio, make sure that it's connected to your Azure DevOps account.

Creating an Azure DevOps project

You use Azure DevOps to manage the source code, run builds and tests, and orchestrate the deployment to GKE. To begin, you create a project in your Azure DevOps account.

1. Go to the Azure DevOps home page (https://dev.azure.com/YOUR_AZURE_DEVOPS_ACCOUNT_NAME).
2. Click New Project.
3. Enter a project name, such as CloudDemo.
4. Set Visibility to Private, and then click Create.
5. After you create the project, in the menu on the left, click Repos.
6. Click Import to fork the dotnet-docs-samples repository from GitHub, and then set the following values:
   • Repository type: Git
   • Clone URL: https://github.com/GoogleCloudPlatform/dotnet-docs-samples.git

7. Click Import.

   When the import process is done, you see the source code of the dotnet-docs-samples repository.

Connecting Azure Pipelines to Google Container Registry

Before you can set up continuous integration for the CloudDemo app, you must connect Azure Pipelines to Container Registry. This connection allows Azure Pipelines to publish container images to Container Registry.

Set up a service account for publishing images

Create a Google Cloud service account in your project:

1. Open the Google Cloud console.

2. In the Google Cloud console, activate Cloud Shell.

   Activate Cloud Shell

3. To save time typing your project ID and Compute Engine zone options, set default configuration values by running the following commands:

   gcloud config set project PROJECT_ID
   gcloud config set compute/zone us-central1-a
   

   Replace PROJECT_ID with the project ID of your project.

4. Enable the Container Registry API in the project:

   gcloud services enable containerregistry.googleapis.com
   

5. Create a service account that Azure Pipelines uses to publish Docker images:

   gcloud iam service-accounts create azure-pipelines-publisher \
       --display-name="Azure Pipelines Publisher"
   

6. Grant the Storage Admin IAM role (roles/storage.admin) to the service account to allow Azure Pipelines to push to Container Registry:

   AZURE_PIPELINES_PUBLISHER=azure-pipelines-publisher@$GOOGLE_CLOUD_PROJECT.iam.gserviceaccount.com
   
   gcloud projects add-iam-policy-binding $GOOGLE_CLOUD_PROJECT \
       --member serviceAccount:$AZURE_PIPELINES_PUBLISHER \
       --role roles/storage.admin
   

7. Generate a service account key:

   gcloud iam service-accounts keys create azure-pipelines-publisher.json \
       --iam-account $AZURE_PIPELINES_PUBLISHER
   
   tr -d '\n' < azure-pipelines-publisher.json > azure-pipelines-publisher-oneline.json
   

8. View the content of the service account key file:

   echo $(<azure-pipelines-publisher-oneline.json)
   

   You need the service account key in one of the following steps.

Create a service connection for Google Container Registry

In Azure Pipelines, create a new service connection for Container Registry:

1. In the Azure DevOps menu, select Project settings, and then select Pipelines > Service connections.
2. Click Create service connection.
3. From the list, select Docker Registry, and then click Next.
4. In the dialog, enter values for the following fields:
   • Registry type: Others
   • Docker Registry: https://gcr.io/PROJECT_ID, replacing PROJECT_ID with the name of your project (for example, https://gcr.io/azure-pipelines-test-project-12345).
   • Docker ID: _json_key
   • Password: Paste the content of azure-pipelines-publisher-oneline.json.
   • Service connection name: gcr-tutorial
5. Click Save to create the connection.

Building continuously

You can now use Azure Pipelines to set up continuous integration. For each commit that's pushed to the Git repository, Azure Pipelines builds the code and packages the build artifacts into a Docker container. The container is then published to Container Registry.

The repository already contains the following Dockerfile:

.NET/Linux

#
# Copyright 2020 Google LLC
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# 
#   http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

FROM mcr.microsoft.com/dotnet/aspnet:6.0
EXPOSE 8080

#------------------------------------------------------------------------------
# Copy publishing artifacts.
#------------------------------------------------------------------------------

WORKDIR /app
COPY CloudDemo.MvcCore/bin/Release/net6.0/publish/ /app/

ENV ASPNETCORE_URLS=http://0.0.0.0:8080

#------------------------------------------------------------------------------
# Run application in Kestrel.
#------------------------------------------------------------------------------

ENTRYPOINT ["dotnet", "CloudDemo.MvcCore.dll"]

.NET Framework/Windows

#
# Copyright 2020 Google LLC
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# 
#   http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

FROM mcr.microsoft.com/windows/servercore/iis:windowsservercore-ltsc2019
EXPOSE 80
SHELL ["powershell", "-command"]

#------------------------------------------------------------------------------
# Add LogMonitor so that IIS and Windows logs are emitted to STDOUT and can be 
# picked up by Docker/Kubernetes.
#
# See https://github.com/microsoft/windows-container-tools/wiki/Authoring-a-Config-File
# for details.
#------------------------------------------------------------------------------

ADD https://github.com/microsoft/windows-container-tools/releases/download/v1.1/LogMonitor.exe LogMonitor/
ADD LogMonitorConfig.json LogMonitor/

#------------------------------------------------------------------------------
# Copy publishing artifacts to webroot.
#------------------------------------------------------------------------------

ADD CloudDemo.Mvc/bin/Release/PublishOutput/ c:/inetpub/wwwroot/

#------------------------------------------------------------------------------
# Configure IIS using the helper functions from deployment.ps1.
#------------------------------------------------------------------------------

ADD deployment.ps1 /
RUN . /deployment.ps1; \
	Install-Iis; \
	Register-WebApplication -AppName "CloudDemo"; \
	Remove-Item /deployment.ps1

#------------------------------------------------------------------------------
# Run IIS, wrapped by LogMonitor.
#------------------------------------------------------------------------------

ENTRYPOINT ["C:\\LogMonitor\\LogMonitor.exe", "C:\\ServiceMonitor.exe", "w3svc"]

You now create a new pipeline that uses YAML syntax:

1. Using Visual Studio or a command-line git client, clone your new Git repository and check out the main branch.
2. In the root of the repository, create a file named azure-pipelines.yml.

3. Copy the following code into the file:

   .NET/Linux

   resources:
   - repo: self
     fetchDepth: 1
   pool:
     vmImage: ubuntu-20.04
   trigger:
   - main
   variables:
     TargetFramework: 'net6.0'
     BuildConfiguration: 'Release'
     DockerImageName: 'PROJECT_ID/clouddemo'
   steps:
   - task: DotNetCoreCLI@2
     displayName: Publish
     inputs:
       projects: 'applications/clouddemo/netcore/CloudDemo.MvcCore.sln'
       publishWebProjects: false
       command: publish
       arguments: '--configuration $(BuildConfiguration) --framework=$(TargetFramework)'
       zipAfterPublish: false
       modifyOutputPath: false
   - task: CmdLine@1
     displayName: 'Lock image version in deployment.yaml'
     inputs:
       filename: /bin/bash
       arguments: '-c "awk ''{gsub(\"CLOUDDEMO_IMAGE\", \"gcr.io/$(DockerImageName):$(Build.BuildId)\", $0); print}'' applications/clouddemo/netcore/deployment.yaml > $(build.artifactstagingdirectory)/deployment.yaml"'
   - task: PublishBuildArtifacts@1
     displayName: 'Publish Artifact'
     inputs:
       PathtoPublish: '$(build.artifactstagingdirectory)'
   - task: Docker@2
     displayName: 'Login to Container Registry'
     inputs:
       command: login
       containerRegistry: 'gcr-tutorial'
   - task: Docker@2
     displayName: 'Build and push image'
     inputs:
       Dockerfile: 'applications/clouddemo/netcore/Dockerfile'
       command: buildAndPush
       repository: '$(DockerImageName)'
   

   .NET Framework/Windows

   resources:
   - repo: self
     fetchDepth: 1
   pool:
     vmImage: windows-2019     # Matches WINDOWS_LTSC in GKE
     demands:
     - msbuild
     - visualstudio
   trigger:
   - master
   variables:
     Solution: 'applications/clouddemo/net4/CloudDemo.Mvc.sln'
     BuildPlatform: 'Any CPU'
     BuildConfiguration: 'Release'
     DockerImageName: 'PROJECT_ID/clouddemo'
   steps:
   - task: NuGetCommand@2
     displayName: 'NuGet restore'
     inputs:
       restoreSolution: '$(Solution)'
   - task: VSBuild@1
     displayName: 'Build solution'
     inputs:
       solution: '$(Solution)'
       msbuildArgs: '/p:DeployOnBuild=true /p:PublishProfile=FolderProfile'
       platform: '$(BuildPlatform)'
       configuration: '$(BuildConfiguration)'
   - task: PowerShell@2
     displayName: 'Lock image version in deployment.yaml'
     inputs:
       targetType: 'inline'
       script: '(Get-Content applications\clouddemo\net4\deployment.yaml) -replace "CLOUDDEMO_IMAGE","gcr.io/$(DockerImageName):$(Build.BuildId)" | Out-File -Encoding ASCII $(build.artifactstagingdirectory)\deployment.yaml'
   - task: PublishBuildArtifacts@1
     displayName: 'Publish Artifact'
     inputs:
       PathtoPublish: '$(build.artifactstagingdirectory)'
   - task: Docker@2
     displayName: 'Login to Container Registry'
     inputs:
       command: login
       containerRegistry: 'gcr-tutorial'
   - task: Docker@2
     displayName: 'Build and push image'
     inputs:
       Dockerfile: 'applications/clouddemo/net4/Dockerfile'
       command: buildAndPush
       repository: '$(DockerImageName)'
   
   

   Replace PROJECT_ID with the name of your project, and then save the file.

4. Commit your changes and push them to Azure Pipelines.

   Visual Studio

   1. Open Team Explorer and click the Home icon.
   2. Click Changes.
   3. Enter a commit message like Add pipeline definition.
   4. Click Commit All and Push.

   Command line

   1. Stage all modified files:

      git add -A
      

   2. Commit the changes to the local repository:

      git commit -m "Add pipeline definition"
      

   3. Push the changes to Azure DevOps:

      git push
      

5. In the Azure DevOps menu, select Pipelines and then click Create Pipeline.

6. Select Azure Repos Git.

7. Select your repository.

8. On the Review your pipeline YAML page, click Run.

   A new build is triggered. It might take about 6 minutes for the build to complete.

9. To verify that the image has been published to Container Registry, switch to your project in the Google Cloud console, select Container Registry > Images, and then click clouddemo.

   A single image and the tag of this image are displayed. The tag corresponds to the numeric ID of the build that was run in Azure Pipelines.

Deploying continuously

With Azure Pipelines automatically building your code and publishing Docker images for each commit, you can now turn your attention to deployment.

Unlike some other continuous integration systems, Azure Pipelines distinguishes between building and deploying, and it provides a specialized set of tools labeled Release Management for all deployment-related tasks.

Azure Pipelines Release Management is built around these concepts:

• A release refers to a set of artifacts that make up a specific version of your app and that are usually the result of a build process.
• Deployment refers to the process of taking a release and deploying it into a specific environment.
• A deployment performs a set of tasks, which can be grouped in jobs.
• Stages let you segment your pipeline and can be used to orchestrate deployments to multiple environments—for example, development and testing environments.

The primary artifact that the CloudDemo build process produces is the Docker image. However, because the Docker image is published to Container Registry, the image is outside the scope of Azure Pipelines. The image therefore doesn't serve well as the definition of a release.

To deploy to Kubernetes, you also need a manifest, which resembles a bill of materials. The manifest not only defines the resources that Kubernetes is supposed to create and manage, but also specifies the exact version of the Docker image to use. The Kubernetes manifest is well suited to serve as the artifact that defines the release in Azure Pipelines Release Management.

Configure the Kubernetes deployment

To run the CloudDemo in Kubernetes, you need the following resources:

• A Deployment that defines a single pod that runs the Docker image produced by the build.
• A NodePort service that makes the pod accessible to a load balancer.
• An Ingress that exposes the application to the public internet by using a Cloud HTTP(S) load balancer.

The repository already contains the following Kubernetes manifest that defines these resources:

.NET/Linux

#
# Copyright 2020 Google LLC
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# 
#   http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

apiVersion: v1
kind: Service
metadata:
  name: clouddemo-netcore
spec:
  ports:
  - port: 80
    targetPort: 8080
    protocol: TCP
    name: http
  selector:
    app: clouddemo-netcore
  type: NodePort

---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: clouddemo-netcore
spec:
  defaultBackend:
    service:
      name: clouddemo-netcore
      port:
        number: 80

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: clouddemo-netcore
spec:
  replicas: 2
  selector:
    matchLabels:
      app: clouddemo-netcore
  template:
    metadata:
      labels:
        app: clouddemo-netcore
    spec:
      containers:
      - name: clouddemo-netcore
        image: CLOUDDEMO_IMAGE
        ports:
          - containerPort: 8080
        livenessProbe:      # Used by deployment controller
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 5
        readinessProbe:     # Used by Ingress/GCLB
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 3
          periodSeconds: 5
        resources:
          limits:
            memory: 1024Mi
          requests:
            memory: 256Mi

.NET Framework/Windows

#
# Copyright 2020 Google LLC
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# 
#   http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

apiVersion: v1
kind: Service
metadata:
  name: clouddemo-net4
  annotations:
    cloud.google.com/neg: '{"ingress": false}' # Disable NEG

spec:
  ports:
  - port: 80
    targetPort: 80
    protocol: TCP
    name: http
  selector:
    app: clouddemo-net4
  type: NodePort

---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: clouddemo-net4
spec:
  defaultBackend:
    service:
      name: clouddemo-net4
      port:
        number: 80

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: clouddemo-net4
spec:
  replicas: 2
  selector:
    matchLabels:
      app: clouddemo-net4
  template:
    metadata:
      labels:
        app: clouddemo-net4
    spec:
      nodeSelector:
        kubernetes.io/os: windows
      containers:
      - name: clouddemo-net4
        image: CLOUDDEMO_IMAGE
        ports:
          - containerPort: 80
        livenessProbe:      # Used by deployment controller
          httpGet:
            path: /health
            port: 80
          initialDelaySeconds: 120
          periodSeconds: 5
        readinessProbe:     # Used by Ingress/GCLB
          httpGet:
            path: /health
            port: 80
          initialDelaySeconds: 10
          periodSeconds: 5
        resources:
          limits:
            memory: 1024Mi
          requests:
            memory: 256Mi

Set up the development and production environments

Before returning to Azure Pipelines Release Management, you need to create the GKE clusters.

Create GKE clusters

1. Return to your Cloud Shell instance.

2. Enable the GKE API for your project:

   gcloud services enable container.googleapis.com

3. Create the development cluster by using the following command. Note that it might take a few minutes to complete:

   .NET/Linux

   gcloud container clusters create azure-pipelines-cicd-dev --enable-ip-alias
   

   .NET Framework/Windows

   gcloud container clusters create azure-pipelines-cicd-dev --enable-ip-alias
   
   gcloud container node-pools create azure-pipelines-cicd-dev-win \
       --cluster=azure-pipelines-cicd-dev \
       --image-type=WINDOWS_LTSC \
       --no-enable-autoupgrade \
       --machine-type=n1-standard-2
   

4. Create the production cluster by using the following command. Note that it might take a few minutes to complete:

   .NET/Linux

   gcloud container clusters create azure-pipelines-cicd-prod --enable-ip-alias
   

   .NET Framework/Windows

   gcloud container clusters create azure-pipelines-cicd-prod --enable-ip-alias
   
   gcloud container node-pools create azure-pipelines-cicd-prod-win \
       --cluster=azure-pipelines-cicd-prod \
       --image-type=WINDOWS_LTSC \
       --no-enable-autoupgrade \
       --machine-type=n1-standard-2
   

Connect Azure Pipelines to the development cluster

Just as you can use Azure Pipelines to connect to an external Docker registry like Container Registry, Azure Pipelines supports integrating external Kubernetes clusters.

It is possible to authenticate to Container Registry using a Google Cloud service account, but using Google Cloud service accounts is not supported by Azure Pipelines for authenticating with GKE. Instead, you have to use a Kubernetes service account.

To connect Azure Pipelines to your development cluster, you therefore have to create a Kubernetes service account first.

1. In Cloud Shell, connect to the development cluster:

   gcloud container clusters get-credentials azure-pipelines-cicd-dev

2. Create a Kubernetes service account for Azure Pipelines:

   kubectl create serviceaccount azure-pipelines-deploy

3. Create a Kubernetes secret containing a token credential for Azure Pipelines:

   kubectl create secret generic azure-pipelines-deploy-token --type=kubernetes.io/service-account-token --dry-run -o yaml \
     | kubectl annotate --local -o yaml -f - kubernetes.io/service-account.name=azure-pipelines-deploy \
     | kubectl apply -f -
   

4. Assign the cluster-admin role to the service account by creating a cluster role binding:

   kubectl create clusterrolebinding azure-pipelines-deploy --clusterrole=cluster-admin --serviceaccount=default:azure-pipelines-deploy

5. Determine the IP address of the cluster:

   gcloud container clusters describe azure-pipelines-cicd-dev --format=value\(endpoint\)
   

   You will need this address in a moment.

6. In the Azure DevOps menu, select Project settings and then select Pipelines > Service connections.

7. Click New service connection.

8. Select Kubernetes and click Next.

9. Configure the following settings.

   Note: To get some of these values, you must run kubectl commands in Cloud Shell and then copy the values into the Azure page.
   • Authentication method: Service account.
   • Server URL: https://PRIMARY_IP. Replace PRIMARY_IP with the IP address that you determined earlier.
   • Secret: The Kubernetes Secret that you created earlier. To get the Secret, run the following command, copy the Secret, and then copy the Secret into the Azure page.

     kubectl get secret azure-pipelines-deploy-token -o yaml

   • Service connection name: azure-pipelines-cicd-dev.

10. Click Save.

Connect Azure Pipelines to the production cluster

To connect Azure Pipelines to your production cluster, you can follow the same approach.

1. In Cloud Shell, connect to the production cluster:

   gcloud container clusters get-credentials azure-pipelines-cicd-prod

2. Create a Kubernetes service account for Azure Pipelines:

   kubectl create serviceaccount azure-pipelines-deploy

3. Assign the cluster-admin role to the service account by creating a cluster role binding:

   kubectl create clusterrolebinding azure-pipelines-deploy --clusterrole=cluster-admin --serviceaccount=default:azure-pipelines-deploy

4. Determine the IP address of the cluster:

   gcloud container clusters describe azure-pipelines-cicd-prod --format=value\(endpoint\)
   

   You will need this address in a moment.

5. In the Azure DevOps menu, select Project settings and then select Pipelines > Service connections.

6. Click New service connection.

7. Select Kubernetes and click Next.

8. Configure the following settings:

   Note: To get some of these values, you must run kubectl commands in Cloud Shell and then copy the values into the Azure page.
   • Authentication method: Service account.
   • Server URL: https://PRIMARY_IP. Replace PRIMARY_IP with the IP address that you determined earlier.
   • Secret: Run the following command in Cloud Shell and copy the output:

     kubectl get secret $(kubectl get serviceaccounts azure-pipelines-deploy -o custom-columns=":secrets[0].name") -o yaml

   • Service connection name: azure-pipelines-cicd-prod.

9. Click Save.

Configure the release pipeline

After you set up the GKE infrastructure, you return to Azure Pipelines to automate the deployment, which includes the following:

• Deploying to the development environment.
• Requesting manual approval before initiating a deployment to the production environment.
• Deploying to the production environment.

Create a release definition

As a first step, create a new release definition.

1. In the Azure DevOps menu, select Pipelines > Releases.
2. Click New pipeline.
3. From the list of templates, select Empty job.
4. When you're prompted for a name for the stage, enter Development.
5. At the top of the screen, name the release CloudDemo-KubernetesEngine.
6. In the pipeline diagram, next to Artifacts, click Add.

7. Select Build and add the following settings:

   • Source type: Build
   • Source (build pipeline): Select the build definition (there should be only one option)
   • Default version: Latest
   • Source Alias: manifest

8. Click Add.

9. On the Artifact box, click Continuous deployment trigger (the lightning bolt icon) to add a deployment trigger.

10. Under Continuous deployment trigger, set the switch to Enabled.

11. Click Save.

12. Enter a comment if you want, and then confirm by clicking OK.

    The pipeline displays similar to the following.

    

Deploy to the development cluster

With the release definition created, you can now configure the deployment to the GKE development cluster.

1. In the menu, switch to the Tasks tab.

2. Click Agent job and configure the following settings:

   • Agent pool: Azure Pipelines
   • Agent specification: ubuntu-18.04

3. Next to Agent job, click Add a task to agent job to add a step to the phase.

4. Select the Deploy to Kubernetes task and click Add.

5. Click the newly added task and configure the following settings:

   • Display name: Deploy
   • Action: deploy
   • Kubernetes service connection: azure-pipelines-cicd-dev
   • Namespace: default
   • Strategy: None
   • Manifests: manifest/drop/deployment.yaml

6. Click Save.

7. Enter a comment if you want, and then confirm by clicking OK.

Deploy to the production cluster

Finally, you configure the deployment to the GKE production cluster.

1. In the menu, switch to the Pipeline tab.
2. In the Stages box, select Add > New stage.
3. From the list of templates, select Empty job.
4. When you're prompted for a name for the stage, enter Production.
5. Click the lightning bolt icon of the newly created stage.

6. Configure the following settings:

   • Select trigger: After stage
   • Stages: Dev
   • Pre-deployment approvals: (enabled)
   • Approvers: Select your own user name.

   The pipeline now looks like this:

   

7. Switch to the Tasks tab.

8. Hold the mouse over the Tasks tab and select Tasks > Production.

9. Click Agent job and configure the following settings:

   • Agent pool: Azure Pipelines
   • Agent specification: ubuntu-18.04

10. Click Add a task to agent job to add a step to the phase.

11. Select the Deploy to Kubernetes task and click Add.

12. Click the newly added task and configure the following settings:

    • Display name: Deploy
    • Action: deploy
    • Kubernetes service connection: azure-pipelines-cicd-prod
    • Namespace: default
    • Strategy: None
    • Manifests: manifest/drop/deployment.yaml

13. Click Save.

14. Enter a comment if you want, and then confirm by clicking OK.

Run the pipeline

Now that you've configured the entire pipeline, you can test it by performing a source code change:

1. On your local computer, open the file Index.cshtml from the Git repository you cloned earlier:

   .NET/Linux

   The file is located in applications\clouddemo\netcore\CloudDemo.MvcCore\Views\Home\

   .NET Framework/Windows

   The file is located in applications\clouddemo\net4\CloudDemo.Mvc\Views\Home\

2. In line 26, change the value of ViewBag.Title from Home Page to This app runs on GKE.

3. Commit your changes, and then push them to Azure Pipelines.

   Visual Studio

   1. Open Team Explorer and click the Home icon.
   2. Click Changes.
   3. Enter a commit message like Change site title.
   4. Click Commit All and Push.

   Command line

   1. Stage all modified files:

      git add -A
      

   2. Commit the changes to the local repository:

      git commit -m "Change site title"
      

   3. Push the changes to Azure Pipelines:

      git push
      

4. In the Azure DevOps menu, select Pipelines. A build is triggered.

5. After the build is finished, select Pipelines > Releases. A release process is initiated.

6. Click Release-1 to open the details page, and wait for the status of the Development stage to switch to Succeeded.

7. In the Google Cloud console, select Kubernetes Engine > Services & Ingress > Ingress.

8. Locate the Ingress service for the azure-pipelines-cicd-dev cluster, and wait for its status to switch to Ok. This might take several minutes.

9. Open the link in the Frontends column of the same row. You might see an error at first because the load balancer takes a few minutes to become available. When it's ready, observe that the CloudDemo has been deployed and is using the custom title.

10. In Azure Pipelines, click the Approve button located under the Prod stage to promote the deployment to the production environment.

    If you don't see the button, you might need to first approve or reject a previous release.

11. Enter a comment if you want, and then confirm by clicking Approve.

12. Wait for the status of the Prod environment to switch to Succeeded. You might need to manually refresh the page in your browser.

13. In the Google Cloud console, refresh the Services & Ingress page.

14. Locate the Ingress service for the azure-pipelines-cicd-prod cluster and wait for its status to switch to Ok. This might take several minutes.

15. Open the link in the Frontends column of the same row. Again, you might see an error at first because the load balancer take a few minutes to become available. When it's ready, you see the CloudDemo app with the custom title again, this time running in the production cluster.

Clean up

To avoid incurring further costs after you complete this tutorial, delete the entities that you created.

Delete the Azure Pipelines project

To delete the Azure Pipelines project, see the Azure DevOps Services documentation. Deleting the Azure Pipelines project causes all source code changes to be lost.

Delete the Google Cloud development and projects

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

What's next

• Configure fine-grained access control for Container Registry.
• Learn how to deploy a highly available SQL Server group on Compute Engine.
• Read about .NET on Google Cloud Platform.
• Install Cloud Tools for Visual Studio.
• Explore reference architectures, diagrams, and best practices about Google Cloud. Take a look at our Cloud Architecture Center.