Cloud Run for containerized services in GCP - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

How does Cloud Run handle incoming requests?

Cloud Run automatically scales container instances based on incoming requests. What happens when there are no requests?

A Cloud Run keeps at least one container instance running at all times.

B Cloud Run shuts down the service completely until manually restarted.

C Cloud Run queues requests until a container instance becomes available.

D Cloud Run scales down to zero container instances to save resources.

💡 Hint

Think about how serverless services save costs when idle.

Cloud Run scales down to zero instances when there are no requests, saving resources and cost. It automatically starts instances when new requests arrive.

❓ Configuration

intermediate

Which Cloud Run configuration sets the maximum number of container instances?

You want to limit the maximum number of container instances Cloud Run can create for your service. Which configuration option do you set?

A min-instances

B max-instances

C concurrency

D memory-limit

💡 Hint

Look for the setting that controls the upper limit of instances.

The max-instances setting limits how many container instances Cloud Run can create, controlling scaling upper bound.

❓ Architecture

advanced

What is the best architecture to securely connect Cloud Run to a private Cloud SQL instance?

You have a Cloud Run service that needs to connect to a Cloud SQL database that is not publicly accessible. Which architecture ensures secure connectivity?

A Configure Cloud Run to use a Serverless VPC Connector and connect via private IP.

B Use Cloud SQL Proxy sidecar container inside Cloud Run service.

C Expose Cloud SQL with a public IP and restrict access by IP whitelist.

D Connect directly using Cloud SQL public IP without additional security.

💡 Hint

Think about private network connectivity options for serverless.

Using a Serverless VPC Connector allows Cloud Run to connect privately to Cloud SQL via private IP, avoiding public exposure and improving security.

❓ security

advanced

How to restrict Cloud Run service access to only authenticated users?

You want your Cloud Run service to only allow requests from users who have signed in with Google accounts. Which setting enforces this?

A Enable IAM-based authentication and remove 'allUsers' from invoker role.

B Use a firewall rule to block all external traffic.

C Set the service to allow unauthenticated invocations.

D Deploy the service in a private subnet.

💡 Hint

Think about Cloud Run's integration with IAM permissions.

Removing 'allUsers' from the Cloud Run invoker role and enabling IAM authentication restricts access to authenticated users only.

✅ Best Practice

expert

What is the recommended concurrency setting for a Cloud Run service handling CPU-intensive tasks?

Your Cloud Run service runs CPU-heavy computations. Which concurrency setting optimizes performance and resource usage?

A Set concurrency to 0 to disable concurrency and allow unlimited requests.

B Set concurrency to 80 (default) to maximize instance utilization.

C Set concurrency to 1 to dedicate one request per container instance.

D Set concurrency to 10 to balance between throughput and CPU usage.

💡 Hint

Consider how concurrency affects CPU-bound workloads.

For CPU-intensive tasks, setting concurrency to 1 ensures each container handles one request at a time, preventing CPU contention and improving performance.

Practice

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

easy

A. It needs you to configure load balancers yourself.

B. It automatically scales your app based on traffic without managing servers.

C. It only works with virtual machines, not containers.

D. It requires you to manage virtual machines manually.

Solution

1. Step 1: Understand Cloud Run's serverless nature

   Cloud Run runs containers without requiring you to manage servers or infrastructure.

2. Step 2: Recognize automatic scaling feature

   Cloud Run automatically adjusts the number of container instances based on incoming traffic.

3. Final Answer:

   It automatically scales your app based on traffic without managing servers. -> Option B

4. Quick Check:

   Serverless + auto-scale = D [OK]

Hint: Cloud Run = serverless + auto scaling [OK]

Common Mistakes:

• Thinking you must manage servers manually
• Confusing Cloud Run with VM services
• Assuming manual load balancer setup is needed

2. Which of the following is the correct command to deploy 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. kubectl run deploy --image=gcr.io/my-project/my-image

D. docker run deploy --image=gcr.io/my-project/my-image

Solution

1. Step 1: Identify the correct CLI tool for Cloud Run deployment

   The gcloud run deploy command is used to deploy container images to Cloud Run.

2. Step 2: Confirm the correct syntax

   The command includes the --image flag followed by the container image URL.

3. Final Answer:

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

4. Quick Check:

   Cloud Run deploy uses gcloud run deploy [OK]

Hint: Use 'gcloud run deploy' to deploy containers [OK]

Common Mistakes:

• Using compute or kubectl commands instead of gcloud run
• Confusing docker run with Cloud Run deployment
• Missing the --image flag

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

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

medium

A. The service will scale down to zero immediately.

B. Cloud Run will reject new requests once CPU limit is reached.

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

D. Cloud Run will automatically create more container instances to handle the traffic.

Solution

1. Step 1: Understand Cloud Run's scaling behavior

   Cloud Run automatically scales container instances based on incoming traffic demand.

2. Step 2: Recognize resource limits do not prevent scaling

   Resource limits set max CPU/memory per instance but do not stop Cloud Run from adding instances.

3. Final Answer:

   Cloud Run will automatically create more container instances to handle the traffic. -> Option D

4. Quick Check:

   Auto scaling = more instances with traffic [OK]

Hint: Cloud Run auto scales instances, resource limits per instance [OK]

Common Mistakes:

• Thinking resource limits block scaling
• Assuming manual scaling is required
• Confusing scale down with scale up

4. You deployed a container to Cloud Run but get an error: Container failed to start. What is a common cause to check first?

medium

A. The container image does not expose the port Cloud Run expects.

B. You forgot to create a virtual machine instance.

C. Cloud Run requires a YAML file to deploy containers.

D. The container image must be in Docker Hub only.

Solution

1. Step 1: Understand Cloud Run port requirements

   Cloud Run expects the container to listen on port 8080 by default or the port set in the PORT environment variable.

2. Step 2: Check container image configuration

   If the container does not expose or listen on the expected port, it will fail to start properly.

3. Final Answer:

   The container image does not expose the port Cloud Run expects. -> Option A

4. Quick Check:

   Port mismatch causes start failure [OK]

Hint: Check container listens on port 8080 [OK]

Common Mistakes:

• Assuming VM instances are needed
• Thinking YAML is mandatory for deployment
• Believing container must be on Docker Hub

5. You want to deploy a containerized web app on Cloud Run that must handle sudden traffic spikes and also keep costs low when idle. Which setup is best?

hard

A. Deploy on Compute Engine with fixed VM instances.

B. Deploy on Cloud Run with minimum instances set to 5 to handle spikes.

C. Deploy on Cloud Run with autoscaling enabled and minimum instances set to zero.

D. Deploy on Cloud Run with manual scaling to 3 instances.

Solution

1. Step 1: Understand Cloud Run autoscaling and cost model

   Cloud Run automatically scales instances up and down based on traffic, and setting minimum instances to zero means no cost when idle.

2. Step 2: Compare options for cost and scalability

   Setting minimum instances above zero incurs cost even when idle; Compute Engine fixed VMs do not scale automatically; manual scaling requires more management.

3. Final Answer:

   Deploy on Cloud Run with autoscaling enabled and minimum instances set to zero. -> Option C

4. Quick Check:

   Auto scale + zero min instances = cost efficient [OK]

Hint: Zero min instances saves cost, autoscale handles spikes [OK]

Common Mistakes:

• Setting minimum instances above zero increases cost
• Using fixed VMs lacks automatic scaling
• Manual scaling requires extra management