GSP1079

Overview

Google Cloud Deploy is a managed service that automates delivery of your applications to a series of target environments in a defined promotion sequence. When you want to deploy your updated application, you create a release, whose lifecycle is managed by a delivery pipeline.

In this lab, you will create a delivery pipeline using Google Cloud Deploy. You will then create a release for a basic application and promote the application through a series of Google Kubernetes Engine (GKE) targets.

The sample application is a simple web app that listens to a port, provides an HTTP response code and adds a log entry. This lab is derived from a tutorial published by Google: https://cloud.google.com/deploy/docs/tutorials.

Objectives

In this lab, you learn how to perform the following tasks:

• Deploy a container image to Google Cloud Artifact Registry using Skaffold
• Create a Google Cloud Deploy delivery pipeline
• Create a release for the delivery pipeline
• Promote the application through the targets in the delivery pipeline

Setup

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.

This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

• Access to a standard internet browser (Chrome browser recommended).

Note: Use an Incognito or private browser window to run this lab. This prevents any conflicts between your personal account and the Student account, which may cause extra charges incurred to your personal account.

• Time to complete the lab---remember, once you start, you cannot pause a lab.

Note: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your account.

How to start your lab and sign in to the Google Cloud console

1. Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:

   • The Open Google Cloud console button
   • Time remaining
   • The temporary credentials that you must use for this lab
   • Other information, if needed, to step through this lab

2. Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).

   The lab spins up resources, and then opens another tab that shows the Sign in page.

   Tip: Arrange the tabs in separate windows, side-by-side.

   Note: If you see the Choose an account dialog, click Use Another Account.

3. If necessary, copy the Username below and paste it into the Sign in dialog.

   {{{user_0.username | "Username"}}}

   You can also find the Username in the Lab Details panel.

4. Click Next.

5. Copy the Password below and paste it into the Welcome dialog.

   {{{user_0.password | "Password"}}}

   You can also find the Password in the Lab Details panel.

6. Click Next.

   Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

7. Click through the subsequent pages:

   • Accept the terms and conditions.
   • Do not add recovery options or two-factor authentication (because this is a temporary account).
   • Do not sign up for free trials.

After a few moments, the Google Cloud console opens in this tab.

Note: To view a menu with a list of Google Cloud products and services, click the Navigation menu at the top-left.

Activate Cloud Shell

Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.

1. Click Activate Cloud Shell at the top of the Google Cloud console.

When you are connected, you are already authenticated, and the project is set to your Project_ID, . The output contains a line that declares the Project_ID for this session:

Your Cloud Platform project in this session is set to {{{project_0.project_id | "PROJECT_ID"}}}

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

2. (Optional) You can list the active account name with this command:

gcloud auth list

3. Click Authorize.

Output:

ACTIVE: * ACCOUNT: {{{user_0.username | "ACCOUNT"}}} To set the active account, run: $ gcloud config set account `ACCOUNT`

4. (Optional) You can list the project ID with this command:

gcloud config list project

Output:

[core] project = {{{project_0.project_id | "PROJECT_ID"}}} Note: For full documentation of gcloud, in Google Cloud, refer to the gcloud CLI overview guide.

Task 1. Set variables

• Declare the environment variables that will be used by various commands:

export PROJECT_ID=$(gcloud config get-value project) export REGION={{{ project_0.default_region | "" }}} gcloud config set compute/region $REGION

Task 2. Create three GKE clusters

In this task you will create the three GKE clusters that will be targets for the delivery pipeline.

Three GKE clusters will be created, denoting the three targets for the delivery pipeline:

• test
• staging
• prod

1. Enable the Google Kubernetes Engine API:

gcloud services enable \ container.googleapis.com \ clouddeploy.googleapis.com

2. Create the three GKE clusters:

gcloud container clusters create test --node-locations={{{project_0.default_zone|""}}} --num-nodes=1 --async gcloud container clusters create staging --node-locations={{{project_0.default_zone|""}}} --num-nodes=1 --async gcloud container clusters create prod --node-locations={{{project_0.default_zone|""}}} --num-nodes=1 --async

3. Check the status of the three clusters:

gcloud container clusters list --format="csv(name,status)"

Output

name,status prod,PROVISIONING staging,PROVISIONING test,RUNNING

Creating the clusters can take a few minutes. You don't need to wait for the clusters to be ready. Continue the lab.

Click Check my progress to verify the objective. Create three GKE clusters

Task 3. Prepare the web application container image

In this task you'll create a repository in Artifact Registry to hold the web application's container images.

1. Enable the Artifact Registry API:

gcloud services enable artifactregistry.googleapis.com

2. Create the web-app repository for holding container images:

gcloud artifacts repositories create web-app \ --description="Image registry for tutorial web app" \ --repository-format=docker \ --location=$REGION

Click Check my progress to verify the objective. Create the web-app repository

Task 4. Build and deploy the container images to the Artifact Registry

In this task you will clone the git repository containing the web application and deploy the application's container images to Artifact Registry.

Prepare the application configuration

1. Clone the repository for the lab into your home directory:

cd ~/ git clone https://github.com/GoogleCloudPlatform/cloud-deploy-tutorials.git cd cloud-deploy-tutorials git checkout c3cae80 --quiet cd tutorials/base

2. Create the skaffold.yaml configuration:

envsubst < clouddeploy-config/skaffold.yaml.template > web/skaffold.yaml cat web/skaffold.yaml

The web directory now contains the skaffold.yaml configuration file, which provides instructions for Skaffold to build a container image for your application. This configuration describes the following items.

The build section configures:

• The two container images that will be built (artifacts)
• The Google Cloud Build project used to build the images

The deploy section configures the Kubernetes manifests needed in deploying the workload to a cluster.

The portForward configuration is used to define the Kubernetes service for the deployment.

Output

apiVersion: skaffold/v2beta7 kind: Config build: artifacts: - image: leeroy-web context: leeroy-web - image: leeroy-app context: leeroy-app googleCloudBuild: projectId: {{project-id}} deploy: kubectl: manifests: - leeroy-web/kubernetes/* - leeroy-app/kubernetes/* portForward: - resourceType: deployment resourceName: leeroy-web port: 8080 localPort: 9000 Note: To view the files, use vi, emacs, nano or the Cloud Shell Code Editor by clicking on the Open Editor icon in Cloud Shell.

Build the web application

The skaffold tool will handle submission of the codebase to Cloud Build.

1. Enable the Cloud Build API:

gcloud services enable cloudbuild.googleapis.com

2. Run the skaffold command to build the application and deploy the container image to the Artifact Registry repository previously created:

cd web skaffold build --interactive=false \ --default-repo $REGION-docker.pkg.dev/$PROJECT_ID/web-app \ --file-output artifacts.json cd ..

3. Once the skaffold build has completed, check for the container images in Artifact Registry:

gcloud artifacts docker images list \ $REGION-docker.pkg.dev/$PROJECT_ID/web-app \ --include-tags \ --format yaml

The --format yaml parameter returns the output as YAML for readability. The output should look like this:

Output

--- createTime: '2022-01-14T02:07:54.995807Z' package: us-central1-docker.pkg.dev/{{project-id}}/web-app/leeroy-app tags: '9181623' updateTime: '2022-01-14T02:07:54.995807Z' version: sha256:6af6a0a72d13dd6597c0fc0191f697e2da2c3892d1bf8e87a3df8d96612e1495 --- createTime: '2022-01-14T02:07:53.629263Z' package: us-central1-docker.pkg.dev/{{project-id}}/web-app/leeroy-web tags: '9181623' updateTime: '2022-01-14T02:07:53.629263Z' version: sha256:a0179673d1876f205875b223557c83162e56e91c5e3313f5e99465a224adb6c9

By default, Skaffold sets the tag for an image to its related git tag if one is available. Similar information can be found in the artifacts.json file that was created by the skaffold command.

Skaffold generates the web/artifacts.json file with details of the deployed images:

cat web/artifacts.json | jq

Output

{ "builds": [ { "imageName": "leeroy-web", "tag": "us-central1-docker.pkg.dev/{{project-id}}/web-app/leeroy-web:9181623@sha256:a0179673d1876f205875b223557c83162e56e91c5e3313f5e99465a224adb6c9" }, { "imageName": "leeroy-app", "tag": "us-central1-docker.pkg.dev/{{project-id}}/web-app/leeroy-app:9181623@sha256:6af6a0a72d13dd6597c0fc0191f697e2da2c3892d1bf8e87a3df8d96612e1495" } ]

Click Check my progress to verify the objective. Build and deploy the container images to the Artifact Registry

Task 5. Create the delivery pipeline

In this task you will set up the delivery pipeline.

1. Enable the Google Cloud Deploy API:

gcloud services enable clouddeploy.googleapis.com

2. Create the delivery-pipeline resource using the delivery-pipeline.yaml file:

gcloud config set deploy/region $REGION cp clouddeploy-config/delivery-pipeline.yaml.template clouddeploy-config/delivery-pipeline.yaml gcloud beta deploy apply --file=clouddeploy-config/delivery-pipeline.yaml

3. Verify the delivery pipeline was created:

gcloud beta deploy delivery-pipelines describe web-app

The delivery pipeline will appear similar to the following output:

Output

Unable to get target test Unable to get target staging Unable to get target prod Delivery Pipeline: createTime: '2021-08-16T14:03:18.294884547Z' description: web-app delivery pipeline etag: 2539eacd7f5c256d name: projects/{{project-id}}/locations/us-central1/deliveryPipelines/web-app serialPipeline: stages: - targetId: test - targetId: staging - targetId: prod uid: eb0601aa03ac4b088d74c6a5f13f36ae updateTime: '2021-08-16T14:03:18.680753520Z' Targets: []

Notice the first three lines of the output. The delivery pipeline currently references three target environments that haven't been created yet. In the next task you will create those targets.

Click Check my progress to verify the objective. Create the delivery pipeline

Task 6. Configure the deployment targets

Three delivery pipeline targets will be created - one for each of the GKE clusters.

Ensure that the clusters are ready

The three GKE clusters should now be running, but it's useful to verify this.

• Run the following to get the status of the clusters:

gcloud container clusters list --format="csv(name,status)"

All three clusters should be in the RUNNING state, as indicated in the output below. If they are not yet marked as RUNNING, retry the command above until their status has changed to RUNNING.

Output

name,status prod,RUNNING staging,RUNNING test,RUNNING

Once all the clusters have the "RUNNING" status continue the lab.

Create a context for each cluster

Use the commands below to get the credentials for each cluster and create an easy-to-use kubectl context for referencing the clusters later:

CONTEXTS=("test" "staging" "prod") for CONTEXT in ${CONTEXTS[@]} do gcloud container clusters get-credentials ${CONTEXT} --region ${REGION} kubectl config rename-context gke_${PROJECT_ID}_${REGION}_${CONTEXT} ${CONTEXT} done

Create a namespace in each cluster

Use the commands below to create a Kubernetes namespace (web-app) in each of the three clusters:

for CONTEXT in ${CONTEXTS[@]} do kubectl --context ${CONTEXT} apply -f kubernetes-config/web-app-namespace.yaml done

The application will be deployed to the (web-app) namespace.

Create the delivery pipeline targets

1. Submit a target definition for each of the targets:

for CONTEXT in ${CONTEXTS[@]} do envsubst < clouddeploy-config/target-$CONTEXT.yaml.template > clouddeploy-config/target-$CONTEXT.yaml gcloud beta deploy apply --file clouddeploy-config/target-$CONTEXT.yaml done

The targets are described in a yaml file. Each target configures the relevant cluster information for the target. The test and staging target configurations are mostly the same.

2. Display the details for the test Target:

cat clouddeploy-config/target-test.yaml

Output

apiVersion: deploy.cloud.google.com/v1beta1 kind: Target metadata: name: test description: test cluster gke: cluster: projects/{{project-id}}/locations/us-central1/clusters/test

The prod target is slightly different as it requires approval (see the requireApproval setting in the output) before a release can be promoted to the cluster.

3. Display the details for the prod Target:

cat clouddeploy-config/target-prod.yaml

Output

apiVersion: deploy.cloud.google.com/v1beta1 kind: Target metadata: name: prod description: prod cluster requireApproval: true gke: cluster: projects/{{project-id}}/locations/us-central1/clusters/prod

4. Verify the three targets (test, staging, prod) have been created:

gcloud beta deploy targets list

All Google Cloud Deploy targets for the delivery pipeline have now been created.

Click Check my progress to verify the objective. Configure the deployment targets

Task 7. Create a release

In this task you create a release of the application.

A Google Cloud Deploy release is a specific version of one or more container images associated with a specific delivery pipeline. Once a release is created, it can be promoted through multiple targets (the promotion sequence). Additionally, creating a release renders your application using skaffold and saves the output as a point-in-time reference that's used for the duration of that release.

Since this is the first release of your application, you'll name it web-app-001.

1. Run the following command to create the release:

gcloud beta deploy releases create web-app-001 \ --delivery-pipeline web-app \ --build-artifacts web/artifacts.json \ --source web/

The --build-artifacts parameter references the artifacts.json file created by skaffold earlier. The --source parameter references the application source directory where skaffold.yaml can be found.

When a release is created, it will also be automatically rolled out to the first target in the pipeline (unless approval is required, which will be covered in a later step of this lab).

2. To confirm the test target has your application deployed, run the following command:

gcloud beta deploy rollouts list \ --delivery-pipeline web-app \ --release web-app-001

Output

--- approvalState: DOES_NOT_NEED_APPROVAL createTime: '2021-08-16T14:05:21.961604Z' deployEndTime: '2021-08-16T14:06:35.278604Z' deployStartTime: '2021-08-16T14:06:22.420091744Z' deployingBuild: projects/{{project-id}}/locations/us-central1/builds/4815b788-ec5e-4185-9141-a5b57c71b001 enqueueTime: '2021-08-16T14:06:21.760830Z' etag: 5cb7b6c342b5f29b name: projects/{{project-id}}/locations/us-central1/deliveryPipelines/web-app/releases/web-app-001/rollouts/web-app-001-to-test-0001 state: SUCCESS targetId: test uid: cccd9525d3a0414fa60b2771036841d9

The first rollout of a release will take several minutes because Google Cloud Deploy renders the manifests for all targets when the release is created. The GKE cluster may also take a few minutes to provide the resources required by the deployment.

If you do not see state: SUCCESS in the output from the previous command, please wait and periodically re-run the command until the rollout completes.

3. Confirm your application was deployed to the test GKE cluster by running the following commands:

kubectx test kubectl get all -n web-app

Output

NAME READY STATUS RESTARTS AGE pod/leeroy-app-5547cf9d9b-rgc2l 1/1 Running 0 3m27s pod/leeroy-web-6768b49c46-w7vt9 1/1 Running 0 3m27s NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE service/leeroy-app ClusterIP None <none> 50051/TCP 3m28s NAME READY UP-TO-DATE AVAILABLE AGE deployment.apps/leeroy-app 1/1 1 1 3m28s deployment.apps/leeroy-web 1/1 1 1 3m28s NAME DESIRED CURRENT READY AGE replicaset.apps/leeroy-app-5547cf9d9b 1 1 1 3m28s replicaset.apps/leeroy-web-6768b49c46 1 1 1 3m28s

Click Check my progress to verify the objective. Create a release

Task 8. Promote the application to staging

In this task you will promote the application from test and into the staging target.

1. Promote the application to the staging target:

gcloud beta deploy releases promote \ --delivery-pipeline web-app \ --release web-app-001

You will be prompted to continue before the promotion commences.

• Press ENTER to accept the default (Y = yes).

2. To confirm the staging Target has your application deployed, run the following command:

gcloud beta deploy rollouts list \ --delivery-pipeline web-app \ --release web-app-001

Review the output

Look for the section marked targetId: staging. As before, if you do not see state: SUCCEEDED in the output from the previous command, wait and periodically re-run the command until the rollout completes.

Output

--- approvalState: DOES_NOT_NEED_APPROVAL createTime: '2022-01-05T02:19:32.539468Z' deployEndTime: '2022-01-05T02:19:45.970949Z' deployStartTime: '2022-01-05T02:19:33.111948770Z' deployingBuild: projects/743805075658/locations/us-central1/builds/2316517c-3a2f-4cd3-80ad-6d133b653746 etag: 1109b802ff586df5 name: projects/{{project-id}}/locations/us-central1/deliveryPipelines/web-app/releases/web-app-001/rollouts/web-app-001-to-staging-0001 state: SUCCEEDED targetId: staging uid: 80a35a5f044844708d2050f8c556e07e

Click Check my progress to verify the objective. Promote the application to staging

Task 9. Promote the application to prod

In this task you will again promote the application but will also provide approval.

1. Promote the application to the prod target:

gcloud beta deploy releases promote \ --delivery-pipeline web-app \ --release web-app-001

You will be prompted to continue before the promotion commences.

• Press ENTER to accept the default (Y = yes).

2. To review the status of the prod target, run the following command:

gcloud beta deploy rollouts list \ --delivery-pipeline web-app \ --release web-app-001

In the output, note that the approvalState is NEEDS_APPROVAL and the state is PENDING_APPROVAL.

Output

--- approvalState: NEEDS_APPROVAL createTime: '2021-08-16T14:12:07.466989Z' etag: 6e9303e5a1b04084 name: projects/{{project-id}}/locations/us-central1/deliveryPipelines/web-app/releases/web-app-001/rollouts/web-app-001-to-prod-0001 state: PENDING_APPROVAL targetId: prod uid: a5c7d6007fee4d80904d49142581aaa7

3. Approve the rollout with the following:

gcloud beta deploy rollouts approve web-app-001-to-prod-0001 \ --delivery-pipeline web-app \ --release web-app-001

You will be prompted to approve the rollout before the promotion commences.

• Press ENTER to accept the default (Y = yes).

4. To confirm the prod target has your application deployed, run the following command:

gcloud beta deploy rollouts list \ --delivery-pipeline web-app \ --release web-app-001

As for previous rollouts, locate the entry for the target (targetId: prod) and check that the rollout has completed (state: SUCCEEDED). Periodically re-run the command until the rollout completes.

5. Use kubectl to check on the status of the deployed application:

kubectx prod kubectl get all -n web-app

Click Check my progress to verify the objective. Promote the application to prod

Congratulations!

Congratulations! In this lab, you learned how to create a delivery pipeline using Google Cloud Deploy. You created a release for a basic application and promoted the application through a series of Google Kubernetes Engine (GKE) targets. You first deployed the application to the test target, then promoted it to the staging target, and finally to the prod target. Now you can use Cloud Deploy to create continuous delivery pipelines!

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Manual Last Updated February 5, 2024

Lab Last Tested July 12, 2023

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