# Cloud Run Canary Deployments - GSP1078

## Overview

Many organizations use robust release pipelines to move code into production. Cloud Run provides unique traffic management capabilities that let you implement advanced release management techniques with little effort.

In this lab you implement a deployment pipeline for Cloud Run. This pipeline executes a progression of code from developer branches to production with automated canary testing and percentage based traffic management.

This lab is for developers and DevOps engineers who are responsible for creating and managing CI/CD pipelines to Cloud Run.

## Objectives

In this lab, you learn how to:

*   Create a Cloud Run service.
    
*   Enable a developer branch.
    
*   Implement a canary testing.
    
*   Safely rollout revisions to production.
    

### Prerequisites

This lab assumes that you have a basic understanding of Git, Cloud Run, and CI/CD pipeline concepts.

In addition, you must have a personal GitHub account that you'll clone a repo into.

### 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 are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials 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 (recommended) or private browser window to run this lab. This prevents 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:** Use only the student account for this lab. If you use a different Google Cloud account, you may incur charges to that 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 dialog opens for you to select your payment method. On the left is the Lab Details pane 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-03-1e31e8d5db90@qwiklabs.net
    ```
    
    You can also find the Username in the Lab Details pane.
    
4.  Click **Next**.
    
5.  Copy the **Password** below and paste it into the **Welcome** dialog.
    
    ```apache
    VZOCcAo2sLT1
    ```
    
    You can also find the Password in the Lab Details pane.
    
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 access Google Cloud products and services, click the **Navigation menu** or type the service or product name in the **Search** field.

![Navigation menu icon and Search field](https://cdn.qwiklabs.com/9Fk8NYFp3quE9mF%2FilWF6%2FlXY9OUBi3UWtb2Ne4uXNU%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** at the top of the Google Cloud console.
    
2.  Click through the following windows:
    
    *   Continue through the Cloud Shell information window.
        
    *   Authorize Cloud Shell to use your credentials to make Google Cloud API calls.
        

When you are connected, you are already authenticated, and the project is set to your **Project\_ID**, `qwiklabs-gcp-02-7b1a2214d5f8`. 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-02-7b1a2214d5f8
```

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

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

```apache
gcloud auth list
```

4.  Click **Authorize**.
    

**Output:**

```apache
ACTIVE: *
ACCOUNT: student-03-1e31e8d5db90@qwiklabs.net

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

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

```apache
gcloud config list project
```

**Output:**

```apache
[core]
project = qwiklabs-gcp-02-7b1a2214d5f8
```

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

## Task 1. Prepare your environment

1.  In Cloud Shell, run the following code to create environment variables to use in this lab:
    

```apache
export PROJECT_ID=$(gcloud config get-value project)
export PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format='value(projectNumber)')
export REGION=us-west1
gcloud config set compute/region $REGION
```

In the next step, you enable the following APIs:

*   Cloud Resource Manager
    
*   GKE
    
*   Cloud Build
    
*   Container Registry
    
*   Cloud Run
    
*   Secret Manager
    

2.  Run the following code to enable the APIs:
    

```apache
gcloud services enable \
cloudresourcemanager.googleapis.com \
container.googleapis.com \
cloudbuild.googleapis.com \
containerregistry.googleapis.com \
run.googleapis.com \
secretmanager.googleapis.com
```

3.  Grant the Secret Manager Admin role (roles/secretmanager.admin) to the Cloud Build Service Agent by running the following command:
    

```apache
gcloud projects add-iam-policy-binding $PROJECT_ID \
--member=serviceAccount:service-$PROJECT_NUMBER@gcp-sa-cloudbuild.iam.gserviceaccount.com \
--role=roles/secretmanager.admin
```

4.  Run the following commands to configure Git and GitHub in Cloud Shell.
    
    ```apache
    curl -sS https://webi.sh/gh | sh
    gh auth login
    gh api user -q ".login"
    GITHUB_USERNAME=$(gh api user -q ".login")
    git config --global user.name "${GITHUB_USERNAME}"
    git config --global user.email "${USER_EMAIL}"
    echo ${GITHUB_USERNAME}
    echo ${USER_EMAIL}
    ```
    

*   Press ENTER to accept the default options. The last default you accept is to **Login with a web browser**.
    
*   Copy the one-time code, and then click the URL provided in the output that takes you to GitHub.
    
*   In GitHub, follow the prompts to connect this project to your GitHub account. This involves signing into your GitHub account, entering the one-time code when prompted, then authorizing the connection to GitHub CLI.
    

5.  Back in Cloud Shell, run the following command to create an empty repository named `cloudrun-progression` in GitHub Repositories:
    

```apache
gh repo create cloudrun-progression --private
```

6.  Clone and prepare the sample repository:
    

```apache
git clone https://github.com/GoogleCloudPlatform/training-data-analyst
```

7.  Use the following command to copy the sample code into your `cloudrun-progression` directory:
    

```apache
mkdir cloudrun-progression
cp -r /home/$USER/training-data-analyst/self-paced-labs/cloud-run/canary/*  cloudrun-progression
cd cloudrun-progression
```

8.  Click **Open Editor** to open Cloud Shell Editor. For the following files, set `REGION` in the `Default Values` section to `us-west1`:
    

*   `branch-cloudbuild.yaml`
    
*   `master-cloudbuild.yaml`
    
*   `tag-cloudbuild.yaml`
    

**Note :** Optionally you can use any code editor, this lab provides instructions for Cloud Shell Editor.

9.  Click **Open Terminal** to return to the Cloud Shell terminal window and run the commands below. These commands replace the placeholder values in the sample repository with your `PROJECT_ID` and `PROJECT_NUMBER`:
    

```apache
sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" branch-trigger.json-tmpl > branch-trigger.json
sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" master-trigger.json-tmpl > master-trigger.json
sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" tag-trigger.json-tmpl > tag-trigger.json
```

10.  Make your first commit with the sample code added to your **cloudrun-progression** directory, and push the changes to the master branch:
     

```apache
git init
git config credential.helper gcloud.sh
git remote add gcp https://github.com/${GITHUB_USERNAME}/cloudrun-progression
git branch -m master
git add . && git commit -m "initial commit"
git push gcp master
```

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

Preparing your environment

## Task 2. Create your Cloud Run service

In this section, you build and deploy the initial production application that you use throughout this lab.

1.  In Cloud Shell, build and deploy the application, which includes a service that requires authentication.
    

```apache
gcloud builds submit --tag gcr.io/$PROJECT_ID/hello-cloudrun
gcloud run deploy hello-cloudrun \
--image gcr.io/$PROJECT_ID/hello-cloudrun \
--platform managed \
--region $REGION \
--tag=prod -q
```

The output looks similar to the following:

```apache
Deploying container to Cloud Run service [hello-cloudrun] in project [sdw-mvp6] region us-west1
✓ Deploying new service... Done.
✓ Creating Revision...
✓ Routing traffic...
Done.
Service [hello-cloudrun] revision [hello-cloudrun-00001-tar] has been deployed and is serving 100 percent of traffic.
Service URL: https://hello-cloudrun-apwaaxltma-uc.a.run.app
The revision can be reached directly at https://prod---hello-cloudrun-apwaaxltma-uc.a.run.app
```

The output includes the service URL and a unique URL for the revision. Your values will differ slightly from what's indicated here.

After the deployment completes, you can view the newly deployed service:

2.  In the Google Cloud console, in the **Navigation menu** (), click **Cloud Run**.
    
3.  Click **hello-cloudrun** from the **Services** list to open the **Service details** page.
    
4.  Click the **Revisions** tab to view the **hello-cloudrun** status.
    
5.  To view the authenticated service response, return to Cloud Shell and run the following commands:
    

```apache
PROD_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.url")
echo $PROD_URL
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $PROD_URL
```

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

Create the CloudRun service and view the authenticated service response

## Task 3. Enable dynamic developer deployments

In this section, you provide developers with a unique URL for development branches in your GitHub account. Each branch is represented by a URL identified by the branch name. Commits to the branch trigger a deployment, and the updates are accessible at that same URL.

1.  In Cloud Shell, enter the following command to initiate a connection to your GitHub repository:
    

```apache
gcloud builds connections create github cloud-build-connection --project=$PROJECT_ID  --region=$REGION 

gcloud builds connections describe cloud-build-connection --region=$REGION
```

2.  In the output, copy (do not click) the **actionUri** URL.
    

Be sure that you are copying the URL in the **actionUri** field in a new tab. If you click, you may not be directed to the correct location.

```apache
etag: yKV297keFBHzs1UcgMsbYJlEYvYdIkfFLJMYZfOADu8
githubConfig: {}
installationState:
  actionUri: https://accounts.google.com/AccountChooser?continue=https%3A%2F%2Fconsole.cloud.google.com%2Fm%2Fgcb%2Fgithub%2Flocations%2Fus-east4%2Foauth_v2%3Fconnection_name%3Dprojects%252F921646058273%252Flocations%252Fus-east4%252Fconnections%252Fcloud-build-connection
  message: Please log in to https://github.com using a robot account and then follow
    this link to authorize Cloud Build to access that account. After authorization,
    your GitHub authorization token will be stored in Cloud Secret Manager.
  stage: PENDING_USER_OAUTH
name: projects/qwiklabs-gcp-00-40e7d6bb49bb/locations/us-east4/connections/cloud-build-connection
reconciling: false
updateTime: '2024-12-12T08:52:48.505263316Z'
```

3.  Click **Continue**. Install the Cloud Build GitHub App in your GitHub account.
    
4.  Choose **Only select repositories**, and then click **Select repositories** and select the `cloudrun-progression` repository.
    
5.  Click **Save**.
    
6.  In Cloud Shell, enter the following command to create a Cloud Build repository:
    

```apache
gcloud builds repositories create cloudrun-progression \
     --remote-uri="https://github.com/${GITHUB_USERNAME}/cloudrun-progression.git" \
     --connection="cloud-build-connection" --region=$REGION
```

### Set up the trigger

1.  In Cloud Shell, run the following command to set up the trigger:
    

```apache
gcloud builds triggers create github --name="branch" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='branch-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com \
   --region=$REGION \
   --branch-pattern='[^(?!.*master)].*'
```

2.  To review the trigger, select **Cloud Build** from the Google Cloud console menu and select **Triggers**.
    
3.  In Cloud Shell, create a new branch:
    

```apache
git checkout -b new-feature-1
```

4.  Click **Open Editor** to open the sample application code in Cloud Shell Editor:
    
5.  In the sample application (**~/cloudrun-progression/app.py**), in line 24, change `v1.0` to `v1.1`:
    

```apache
@app.route('/')
def hello_world():
return 'Hello World v1.1'
```

6.  Click **Open Terminal** to return to your Cloud Shell terminal.
    
7.  In Cloud Shell, commit the change and push it to the remote repository:
    

```apache
git add . && git commit -m "updated" && git push gcp new-feature-1
```

8.  To review the build in progress, go back to the **Cloud Build** page and view the current build running on your new branch.
    
9.  When the build completes, review the revision:
    

*   The **Cloud Run** page should still be open in the console. Otherwise, in the **Navigation menu** click **Cloud Run**.
    
*   Choose the **hello-cloudrun service**.
    
*   Select the **Revisions** tab.
    

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

Connect to a GitHub repository, set up the branch trigger and update the sample application

10.  In Cloud Shell, get the unique URL for this branch:
     

```apache
BRANCH_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.traffic[] | select (.tag==\"new-feature-1\")|.url")
echo $BRANCH_URL
```

11.  Access the authenticated URL:
     

```apache
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $BRANCH_URL
```

The updated response output looks like the following:

```apache
Hello World v1.1
```

Task 4. Automate canary testing

When code is released to production, it's common to release a small subset of live traffic before migrating all traffic to the new code base.

In this section, you implement a trigger that activates by a code commit to the main branch. The trigger deploys the code to a unique canary URL and routes 10% of the live traffic to it.

1.  In Cloud Shell, set up the branch trigger:
    

```apache
gcloud builds triggers create github --name="master" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='master-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com  \
   --region=$REGION \
   --branch-pattern='master'
```

2.  To review the new trigger, go to the **Cloud Build > Triggers** page.
    
3.  In Cloud Shell, merge the branch to the main line and push to the remote repository:
    

```apache
git checkout master
git merge new-feature-1
git push gcp master
```

4.  To review the build in progress, go back to the **Cloud Build** page and view the current build.
    
5.  After the build completes, to review the new revision, go to **Cloud Run**, choose the **hello-cloudrun service** , and select the **Revisions** page. Note that 90% of the traffic is routed to prod, 10% to canary, and 0% to the branch revisions.
    

![Revisions page showing percentage of traffic on each revision](https://cdn.qwiklabs.com/ofBtRhde8X03IPSk4EP5LmHY9IUSvMEDgknkkq2SIG4%3D align="left")

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

Create the master trigger and build a new revision

6.  Review the key lines of `master-cloudbuild.yaml` that implement the logic for the canary deploy.
    

Lines 39-44 deploy the new revision and use the tag flag to route traffic from the unique canary URL:

```apache
gcloud run deploy ${_SERVICE_NAME} \
--platform managed \
--region ${_REGION} \
--image gcr.io/${PROJECT_ID}/${_SERVICE_NAME} \
--tag=canary \
--no-traffic
```

Line 61 adds a static tag to the revision that notes the Git short Secure Hash Algorithm (SHA) of the deployment:

**Note:** The SHA is a unique identifier for each commit. The SHA ensures the integrity of data by generating a unique, fixed-size string from the content of the commit.

```apache
gcloud beta run services update-traffic ${_SERVICE_NAME} --update-tags=sha-$SHORT_SHA=$${CANARY} --platform managed --region ${_REGION}
```

Line 62 updates the traffic to route 90% to production and 10% to canary:

```apache
gcloud run services update-traffic ${_SERVICE_NAME} --to-revisions=$${PROD}=90,$${CANARY}=10 --platform managed --region ${_REGION}
```

7.  In Cloud Shell, get the unique URL for the canary revision:
    

```apache
CANARY_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.traffic[] | select (.tag==\"canary\")|.url")
echo $CANARY_URL
```

8.  Review the canary endpoint directly:
    

```apache
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $CANARY_URL
```

9.  To see percentage-based responses, make a series of requests:
    

```apache
LIVE_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.url")
for i in {0..20};do
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $LIVE_URL; echo \n
done
```

## Task 5. Release to production

After you validate the canary deployment with a small subset of traffic, release the deployment to the remainder of the live traffic.

In this section, you set up a trigger that is activated when you create a tag in the repository. The trigger migrates 100% of traffic to the already deployed revision based on the commit SHA of the tag. Using the commit SHA ensures the revision validated with canary traffic is the revision utilized for the remainder of production traffic.

1.  In Cloud Shell, set up the tag trigger:
    

```apache
gcloud builds triggers create github --name="tag" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='tag-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com  \
   --region=$REGION \
   --tag-pattern='.*'
```

2.  To review the new trigger, go to the console title bar, enter **Cloud Build Trigger** in the **Search** field, and then click **Triggers** in the search results.
    
3.  Return to Cloud Shell to create a new tag and push the update to the remote repository:
    

```apache
git tag 1.1
git push gcp 1.1
```

4.  To review the build in progress, return to the console with the **Cloud Build** page open, and click **History** in the left pane.
    
5.  After the build is complete, still in the console, click the **hello-cloudrun service** and select the **Revisions** tab. The revision should now indicate the prod tag and be serving 100% of live traffic.
    

![Revisions page showing percentage of traffic on each revision](https://cdn.qwiklabs.com/wxg0Z4wZdd4XN9QI3JD5ju7NimPSrL7h1GSmKLlI%2B2s%3D align="left")

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

Create the tag trigger and view the updated revision

6.  In Cloud Shell, to see percentage-based responses, make a series of requests:
    

```apache
LIVE_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.url")
for i in {0..20};do
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $LIVE_URL; echo \n
done
```

7.  Review the key lines of `tag-cloudbuild.yaml` that implement the production deployment logic.
    

Line 37 updates the canary revision adding the prod tag. The deployed revision is now tagged for both prod and canary:

```apache
gcloud beta run services update-traffic ${_SERVICE_NAME} --update-tags=prod=$${CANARY} --platform managed --region ${_REGION}
```

Line 39 updates the traffic for the base service URL to route 100% of traffic to the revision tagged as prod:

```apache
gcloud run services update-traffic ${_SERVICE_NAME} --to-revisions=$${NEW_PROD}=100 --platform managed --region ${_REGION}
```

## Task 6. GitHub cleanup

To keep your GitHub account organized, remove the GitHub repo you created in this lab.

1.  In [GitHub.com](https://www.cloudskillsboost.google/games/6311/labs/GitHub.com), navigate to the `cloudrun-progression` repo.
    
2.  In the title bar, click **Settings**, then scroll down to the **Danger Zone** section.
    
3.  Click **Delete this repository**.
    
4.  Step through the prompts that confirm you have the correct repository and that you want to delete it.
    

**Warning:** Be sure you are deleting the correct repo, you cannot undo the deletion.

* * *

## Solution of Lab

### Quick

<iframe type="youtube" src="https://www.youtube.com/watch?v=_uxYHcCcQmI" data-node-type="hn-embed"></iframe>

```apache
curl -LO raw.githubusercontent.com/ePlus-DEV/storage/refs/heads/main/labs/GSP1078/lab.sh
source lab.sh
```

![](https://cdn.hashnode.com/uploads/covers/5f802df9bbabf10ec84d9fe8/ad01dc57-ca0c-4205-a756-1d71d33658b3.png align="center")

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1770785812582/b010ea3c-9a65-4b9c-a6e6-289406e0064a.png align="center")

**Script Alternative**

```apache
export PROJECT_ID=$(gcloud config get-value project)
export PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID --format='value(projectNumber)')
REGION=$(gcloud compute project-info describe \
  --format="value(commonInstanceMetadata.items[google-compute-default-region])")
gcloud config set compute/region $REGION


gcloud services enable \
cloudresourcemanager.googleapis.com \
container.googleapis.com \
cloudbuild.googleapis.com \
containerregistry.googleapis.com \
run.googleapis.com \
secretmanager.googleapis.com

sleep 60


gcloud projects add-iam-policy-binding $PROJECT_ID \
--member=serviceAccount:service-$PROJECT_NUMBER@gcp-sa-cloudbuild.iam.gserviceaccount.com \
--role=roles/secretmanager.admin


curl -sS https://webi.sh/gh | sh
gh auth login
gh api user -q ".login"
GITHUB_USERNAME=$(gh api user -q ".login")
git config --global user.name "${GITHUB_USERNAME}"
git config --global user.email "${USER_EMAIL}"
echo ${GITHUB_USERNAME}
echo ${USER_EMAIL}
```

*   Press **ENTER** to accept the default options. The last default you accept is to **Login with a web browser**.  
    Copy the one-time code, and then click the URL provided in the output that takes you to GitHub.  
    In GitHub, follow the prompts to connect this project to your GitHub account.  
    This involves:
    
    *   Signing into your GitHub account
        
    *   Entering the one-time code when prompted
        
    *   Authorizing the connection to GitHub CLI
        

```apache

gh repo create cloudrun-progression --private 

git clone https://github.com/GoogleCloudPlatform/training-data-analyst

mkdir cloudrun-progression
cp -r /home/$USER/training-data-analyst/self-paced-labs/cloud-run/canary/*  cloudrun-progression
cd cloudrun-progression

sed -i "s/_REGION: us-central1/_REGION: $REGION/g" branch-cloudbuild.yaml
sed -i "s/_REGION: us-central1/_REGION: $REGION/g" master-cloudbuild.yaml
sed -i "s/_REGION: us-central1/_REGION: $REGION/g" tag-cloudbuild.yaml


sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" branch-trigger.json-tmpl > branch-trigger.json
sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" master-trigger.json-tmpl > master-trigger.json
sed -e "s/PROJECT/${PROJECT_ID}/g" -e "s/NUMBER/${PROJECT_NUMBER}/g" tag-trigger.json-tmpl > tag-trigger.json


git init
git config credential.helper gcloud.sh
git remote add gcp https://github.com/${GITHUB_USERNAME}/cloudrun-progression
git branch -m master
git add . && git commit -m "initial commit"
git push gcp master


gcloud builds submit --tag gcr.io/$PROJECT_ID/hello-cloudrun
gcloud run deploy hello-cloudrun \
--image gcr.io/$PROJECT_ID/hello-cloudrun \
--platform managed \
--region $REGION \
--tag=prod -q


PROD_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.url")
echo $PROD_URL
curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $PROD_URL


gcloud builds connections create github cloud-build-connection --project=$PROJECT_ID  --region=$REGION 

gcloud builds connections describe cloud-build-connection --region=$REGION
```

*   Click Continue. Install the Cloud Build GitHub App in your GitHub account.
    
*   Choose Only select repositories, and then click Select repositories and select the cloudrun-progression repository.
    

**For Better Understading Follow the Video**

```apache

gcloud builds repositories create cloudrun-progression \
     --remote-uri="https://github.com/${GITHUB_USERNAME}/cloudrun-progression.git" \
     --connection="cloud-build-connection" --region=$REGION


gcloud builds triggers create github --name="branch" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='branch-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com \
   --region=$REGION \
   --branch-pattern='[^(?!.*master)].*'


git checkout -b new-feature-1


sed -i "s/v1.0/v1.1/g" app.py

git add . && git commit -m "updated" && git push gcp new-feature-1

BRANCH_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.traffic[] | select (.tag==\"new-feature-1\")|.url")
echo $BRANCH_URL


gcloud builds triggers create github --name="master" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='master-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com  \
   --region=$REGION \
   --branch-pattern='master'


git checkout master
git merge new-feature-1
git push gcp master


CANARY_URL=$(gcloud run services describe hello-cloudrun --platform managed --region $REGION --format=json | jq --raw-output ".status.traffic[] | select (.tag==\"canary\")|.url")
echo $CANARY_URL

curl -H "Authorization: Bearer $(gcloud auth print-identity-token)" $CANARY_URL




gcloud builds triggers create github --name="tag" \
   --repository=projects/$PROJECT_ID/locations/$REGION/connections/cloud-build-connection/repositories/cloudrun-progression \
   --build-config='tag-cloudbuild.yaml' \
   --service-account=projects/$PROJECT_ID/serviceAccounts/$PROJECT_NUMBER-compute@developer.gserviceaccount.com  \
   --region=$REGION \
   --tag-pattern='.*'


git tag 1.1
git push gcp 1.1
```

* * *

### Manual

<iframe type="youtube" src="https://youtu.be/pxbOIKRnONY" data-node-type="hn-embed"></iframe>