Cloud Run service concept in GCP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to deploy a Cloud Run service with the correct command.

GCP

gcloud run deploy my-service --image [1] --region us-central1

Drag options to blanks, or click blank then click option'

Amy-service

Bgcr.io/my-project/my-image

Cus-central1

Dmy-image

Attempts:

3 left

💡 Hint

Common Mistakes

Using the service name instead of the image URL.

Using only the image name without the registry path.

The --image flag requires the full container image URL, such as gcr.io/my-project/my-image.

2fill in blank

medium

Complete the code to specify the platform when deploying a Cloud Run service.

GCP

gcloud run deploy my-service --image gcr.io/my-project/my-image --platform [1]

Drag options to blanks, or click blank then click option'

Agke

Bapp-engine

Cmanaged

Dkubernetes

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'gke' when intending to deploy to the managed platform.

Using unrelated platforms like 'app-engine'.

The --platform managed flag tells Cloud Run to use the fully managed environment.

3fill in blank

hard

Fix the error in the command to allow unauthenticated access to the Cloud Run service.

GCP

gcloud run deploy my-service --image gcr.io/my-project/my-image --allow-[1]

Drag options to blanks, or click blank then click option'

Aprivate

Bauthenticated

Cpublic

Dunauthenticated

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'authenticated' which restricts access to logged-in users.

Using 'public' or 'private' which are not valid flag values.

The correct flag is --allow-unauthenticated to let anyone access the service without login.

4fill in blank

hard

Fill both blanks to create a Cloud Run service with 2 CPU cores and 512Mi memory.

GCP

gcloud run deploy my-service --image gcr.io/my-project/my-image --cpu [1] --memory [2]

Drag options to blanks, or click blank then click option'

A2

B1

C512Mi

D256Mi

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping CPU and memory values.

Using incorrect memory units like 'MB' instead of 'Mi'.

Use --cpu 2 for 2 CPU cores and --memory 512Mi for 512 MiB memory.

5fill in blank

hard

Fill all three blanks to set environment variables and concurrency for a Cloud Run service.

GCP

gcloud run deploy my-service --image gcr.io/my-project/my-image --set-env-vars [1]=prod,[2]=us-central1 --concurrency [3]

Drag options to blanks, or click blank then click option'

AENVIRONMENT

BREGION

C80

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase or incorrect environment variable names.

Setting concurrency to a very low or invalid number.

Set environment variables ENVIRONMENT=prod and REGION=us-central1, and concurrency to 80.

Practice

1. What is the main benefit of using Cloud Run for your applications?

easy

A. You must manually scale your application.

B. You don't need to manage servers or infrastructure.

C. It only runs applications written in Python.

D. You need to configure virtual machines yourself.

Solution

1. Step 1: Understand Cloud Run's server management

   Cloud Run automatically manages the servers, so you don't have to.

2. Step 2: Compare other options

   Manual scaling and VM configuration are not needed with Cloud Run.

3. Final Answer:

   You don't need to manage servers or infrastructure. -> Option B

4. Quick Check:

   Serverless = No server management [OK]

Hint: Cloud Run means no server setup needed [OK]

Common Mistakes:

• Thinking you must manage servers manually
• Believing Cloud Run only supports one language
• Confusing Cloud Run with VM services

2. Which gcloud command correctly deploys a container image to Cloud Run?

easy

A. gcloud run deploy --image gcr.io/my-project/my-image

B. gcloud compute instances create --image gcr.io/my-project/my-image

C. gcloud app deploy --image gcr.io/my-project/my-image

D. gcloud container clusters create --image gcr.io/my-project/my-image

Solution

1. Step 1: Identify the correct service for deploying containers

   Cloud Run uses gcloud run deploy to deploy container images.

2. Step 2: Eliminate other commands

   compute instances is for VMs, app deploy is for App Engine, and container clusters create is for Kubernetes clusters.

3. Final Answer:

   gcloud run deploy --image gcr.io/my-project/my-image -> Option A

4. Quick Check:

   Cloud Run deploy = gcloud run deploy [OK]

Hint: Use 'gcloud run deploy' for Cloud Run containers [OK]

Common Mistakes:

• Using compute or app commands instead of run
• Confusing Kubernetes cluster commands with Cloud Run
• Missing the --image flag

3. Given this Cloud Run service configuration snippet, what happens when traffic increases?

apiVersion: serving.knative.dev/v1
kind: Service
metadata:
  name: hello-service
spec:
  template:
    spec:
      containers:
      - image: gcr.io/my-project/hello-image
        resources:
          limits:
            cpu: 1
            memory: 512Mi

medium

A. Cloud Run automatically creates more instances to handle the traffic.

B. The service crashes because CPU is limited to 1.

C. You must manually add more instances in the config.

D. Traffic is rejected when CPU limit is reached.

Solution

1. Step 1: Understand Cloud Run scaling behavior

   Cloud Run automatically scales container instances based on incoming traffic.

2. Step 2: Analyze resource limits

   CPU and memory limits set max per instance but do not prevent scaling.

3. Final Answer:

   Cloud Run automatically creates more instances to handle the traffic. -> Option A

4. Quick Check:

   Auto scaling = more instances on traffic rise [OK]

Hint: Cloud Run scales instances automatically with traffic [OK]

Common Mistakes:

• Thinking CPU limit stops scaling
• Believing manual scaling is required
• Assuming traffic is rejected on resource limits

4. You deployed a Cloud Run service but get an error: Container failed to start. What is a likely cause?

medium

A. The container image is too large to deploy.

B. You forgot to set the CPU limit in the deployment.

C. The container image does not have a listening port configured.

D. Cloud Run requires a VM instance to be created first.

Solution

1. Step 1: Check container requirements for Cloud Run

   Cloud Run requires the container to listen on a port for incoming requests.

2. Step 2: Evaluate other options

   CPU limits are optional, Cloud Run is serverless (no VM setup), and image size usually causes warnings, not start failure.

3. Final Answer:

   The container image does not have a listening port configured. -> Option C

4. Quick Check:

   Listening port missing = start failure [OK]

Hint: Containers must listen on a port for Cloud Run [OK]

Common Mistakes:

• Assuming VM setup is needed
• Blaming CPU limits for start failure
• Thinking image size causes start errors

5. You want to deploy a Cloud Run service that scales down to zero when idle but also supports up to 10 concurrent requests per instance. Which configuration is correct?

hard

A. Set --concurrency=1 and --min-instances=10 to scale down to zero.

B. Set --min-instances=1 and --concurrency=10 to scale to zero.

C. Set --max-instances=10 and --concurrency=1 to allow 10 concurrent requests.

D. Set --concurrency=10 and deploy normally; Cloud Run scales to zero automatically.

Solution

1. Step 1: Understand concurrency and scaling in Cloud Run

   Concurrency controls how many requests one instance handles; setting it to 10 allows 10 requests per instance.

2. Step 2: Understand scaling to zero behavior

   Cloud Run automatically scales down to zero when idle unless --min-instances is set above zero.

3. Final Answer:

   Set --concurrency=10 and deploy normally; Cloud Run scales to zero automatically. -> Option D

4. Quick Check:

   Concurrency 10 + no min-instances = scale to zero [OK]

Hint: No min-instances means auto scale to zero [OK]

Common Mistakes:

• Setting min-instances prevents scaling to zero
• Confusing max-instances with concurrency
• Assuming concurrency 1 means 10 requests