Deploying Cloud Run Services

Introduction and Goal

In the previous lessons, you've learned about Google Cloud Run as a serverless platform and how to configure service resources like CPU, memory, and scaling parameters. You've also deployed basic Cloud Run services in earlier practices to get hands-on experience with the fundamentals. However, those initial deployments focused on learning the basics — now it's time to take your deployment skills to the next level with production-ready configurations. This is where Cloud Run service deployment with enterprise-grade components comes into play. A production Cloud Run service goes beyond basic deployment to include proper image management, logging infrastructure, and operational visibility — all essential for real-world applications. In this lesson, you'll deploy a production-ready Cloud Run service that pulls a container image from Google Artifact Registry, exposes your web application to the internet, and automatically ships application logs to Cloud Logging for monitoring and debugging. This represents a realistic scenario in which you're deploying a custom web application that needs secure image storage, network connectivity, and centralized logging — moving beyond the simple deployments you've done previously. Your main goal is to deploy a Cloud Run service using the gcloud command-line tool that incorporates these three critical components: Artifact Registry integration for private container images, automatic HTTPS endpoint creation for network access, and Cloud Logging integration for operational visibility. By the end of this lesson, you'll have a running Cloud Run service that's accessible via a public URL and understand how to manage its complete lifecycle in a production context.

Preparing for Deployment

Before deploying your Cloud Run service, you need to know the full path to your container image in Artifact Registry . This path follows a specific format and includes your Google Cloud project ID, the region, the repository name, and the image name with its tag. The standard format for an Artifact Registry image URI is: REGION-docker.pkg.dev/PROJECT_ID/REPOSITORY/IMAGE_NAME:TAG For this lesson, we will use the following values: Service Name : my-web-app Region : us-central1 Image URI : us-central1-docker.pkg.dev/YOUR_PROJECT_ID/my-apps/my-web-app:latest You will need to replace YOUR_PROJECT_ID with your actual Google Cloud project ID in the commands that follow. You can find your project ID in the Google Cloud Console or by running gcloud config get-value project .

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Inspecting the Full Service Configuration

Run this command to view your service details in a human-readable YAML format:

Shell

gcloud run services describe my-web-app \
  --region=us-central1 \
  --format=yaml

gcloud run services describe my-web-app \
  --region=us-central1 \
  --format=yaml

The --format=yaml flag outputs the service configuration in YAML, which is easier to read than the default JSON output. You'll see detailed information including:

YAML

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: my-web-app
  namespace: '123456789012'
spec:
  template:
    metadata:
      name: my-web-app-00001-abc
    spec:
      containerConcurrency: 80
      containers:
      - image: us-central1-docker.pkg.dev/your-project-id/my-apps/my-web-app:latest
        ports:
        - containerPort: 3000
        resources:
          limits:
            cpu: '1'
            memory: 512Mi
      serviceAccountName: 123456789012-compute@developer.gserviceaccount.com
status:
  url: https://my-web-app-abc123-uc.a.run.app
  conditions:
  - type: Ready
    status: 'True'

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: my-web-app
  namespace: '123456789012'
spec:
  template:
    metadata:
      name: my-web-app-00001-abc
    spec:
      containerConcurrency: 80
      containers:
      - image: us-central1-docker.pkg.dev/your-project-id/my-apps/my-web-app:latest
        ports:
        - containerPort: 3000
        resources:
          limits:
            cpu: '1'
            memory: 512Mi
      serviceAccountName: 123456789012-compute@developer.gserviceaccount.com
status:
  url: https://my-web-app-abc123-uc.a.run.app
  conditions:
  - type: Ready
    status: 'True'

This output shows you the complete service configuration, including some values that Cloud Run set automatically. Key sections to note:

spec.template.spec.containers: Shows your container configuration, including the image URI, port, and resource limits you specified during deployment.
spec.template.spec.containerConcurrency: Indicates how many concurrent requests a single container instance can handle. Cloud Run sets this to 80 by default, meaning each instance can process up to 80 requests simultaneously.
status.url: Your service's public HTTPS endpoint.
status.conditions: Shows the health status of your service. When type: Ready has status: 'True', your service is successfully deployed and serving traffic.

Introduction and Goal

Preparing for Deployment

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Deploying a Cloud Run Service with Full Configuration

Running the Deployment Command

Verifying the Deployment

Viewing Service Details

Inspecting the Full Service Configuration

Retrieving Specific Service Details

Viewing Service Logs

Updating a Service and Managing Revisions

Listing and Describing Revisions

Rolling Back to a Previous Revision

Deleting a Cloud Run Service

Summary and What's Next