# Continuous Delivery with Google Cloud Deploy - 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](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.
    
    ```apache
    student-04-261b235aa684@qwiklabs.net
    ```
    
    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.
    
    ```apache
    luYbyzDyfhnD
    ```
    
    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.

![Navigation menu icon](https://cdn.qwiklabs.com/nUxFb6oRFr435O3t6V7WYJAjeDFcrFb16G9wHWp5BzU%3D align="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**
    
    ![Activate Cloud Shell icon](https://cdn.qwiklabs.com/ep8HmqYGdD%2FkUncAAYpV47OYoHwC8%2Bg0WK%2F8sidHquE%3D align="left")
    
    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**, `qwiklabs-gcp-02-20ee5447c766`. The output contains a line that declares the **Project\_ID** for this session:

```apache
Your Cloud Platform project in this session is set to qwiklabs-gcp-02-20ee5447c766
```

`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:
    

```apache
gcloud auth list
```

3.  Click **Authorize**.
    

**Output:**

```apache
ACTIVE: *
ACCOUNT: student-04-261b235aa684@qwiklabs.net

To set the active account, run:
    $ gcloud config set account `ACCOUNT`
```

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

```apache
gcloud config list project
```

**Output:**

```apache
[core]
project = qwiklabs-gcp-02-20ee5447c766
```

**Note:** For full documentation of `gcloud`, in Google Cloud, refer to [the gcloud CLI overview guide](https://cloud.google.com/sdk/gcloud).

## **Task 1. Set variables**

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

```apache
export PROJECT_ID=$(gcloud config get-value project)
export REGION=us-east4
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:
    

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

2.  Create the three GKE clusters:
    

```apache
gcloud container clusters create test --node-locations=us-east4-c --num-nodes=1  --async
gcloud container clusters create staging --node-locations=us-east4-c --num-nodes=1  --async
gcloud container clusters create prod --node-locations=us-east4-c --num-nodes=1  --async
```

3.  Check the status of the three clusters:
    

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

**Output**

```apache
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

**Check my progress**

## **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:
    

```apache
gcloud services enable artifactregistry.googleapis.com
```

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

```apache
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

**Check my progress**

## **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:
    

```apache
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:
    

```apache
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**

```apache
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:
    

```apache
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:
    

```apache
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:
    

```apache
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**

```apache
---
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:

```apache
cat web/artifacts.json | jq
```

**Output**

```json
{
    "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

**Check my progress**

## **Task 5. Create the delivery pipeline**

In this task you will set up the delivery pipeline.

1.  Enable the Google Cloud Deploy API:
    

```apache
gcloud services enable clouddeploy.googleapis.com
```

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

```apache
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:
    

```apache
gcloud beta deploy delivery-pipelines describe web-app
```

The delivery pipeline will appear similar to the following output:

**Output**

```apache
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

**Check my progress**

## **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:
    

```apache
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**

```apache
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:

```apache
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:

```apache
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:
    

```apache
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:
    

```apache
cat clouddeploy-config/target-test.yaml
```

**Output**

```apache
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:
    

```apache
cat clouddeploy-config/target-prod.yaml
```

**Output**

```apache
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:
    

```apache
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

**Check my progress**

## **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:
    

```apache
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:
    

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

**Output**

```apache
---
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:
    

```apache
kubectx test
kubectl get all -n web-app
```

**Output**

```apache
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

**Check my progress**

## **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:
    

```apache
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:
    

```apache
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**

```apache
---
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

**Check my progress**

## **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:
    

```apache
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:
    

```apache
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**

```apache
---
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:
    

```apache
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:
    

```apache
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:
    

```apache
kubectx prod
kubectl get all -n web-app
```

Click **Check my progress** to verify the objective.

* * *

## Solution of Lab

### Quick

%[https://youtu.be/ZR0c3wmDayk] 

```apache
curl -LO raw.githubusercontent.com/ePlus-DEV/storage/refs/heads/main/labs/GSP1079/lab.sh
source lab.sh
```

**Script Alternative**

```apache
curl -LO raw.githubusercontent.com/quiccklabs/Labs_solutions/master/Continuous%20Delivery%20with%20Google%20Cloud%20Deploy/quicklabgsp1079.sh
sudo chmod +x quicklabgsp1079.sh
./quicklabgsp1079.sh
```

* * *

### Other Solution

%[https://www.youtube.com/watch?v=G4L3Jsr9qAM] 

```plaintext
curl -LO raw.githubusercontent.com/ePlus-DEV/storage/refs/heads/main/labs/GSP1079/other.sh
source other.sh
```

**Script Alternative**

```plaintext
curl -LO raw.githubusercontent.com/imharshtiwari/2-Minutes-GCP-Lab-Solutions/main/Continuous%20Delivery%20with%20Google%20Cloud%20Deploy/gsp1079.sh

sudo chmod +x gsp1079.sh

./gsp1079.sh
```

### Manual

%[https://www.youtube.com/watch?v=ak3HQH8ltik]