Cloud Run for containerized services in GCP - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Cloud Run in Google Cloud Platform?

Cloud Run is a service that lets you run containerized applications without managing servers. It automatically scales your app based on traffic.

beginner

How does Cloud Run handle scaling for your containerized service?

Cloud Run automatically scales the number of container instances up or down depending on the number of incoming requests, even down to zero when idle.

beginner

What is required to deploy an application on Cloud Run?

You need a container image stored in a container registry, like Google Container Registry or Artifact Registry, and then you deploy it to Cloud Run.

intermediate

Can Cloud Run services be accessed publicly by default?

Yes, by default Cloud Run services are publicly accessible over HTTPS, but you can restrict access using authentication and IAM policies.

intermediate

What is the difference between Cloud Run and traditional VM hosting?

Cloud Run runs containers without managing servers or VMs, automatically scales, and charges only for actual usage, unlike traditional VM hosting where you manage servers and pay for uptime.

What does Cloud Run automatically scale based on?

A Number of incoming requests

B CPU usage of your laptop

C Number of developers in your team

D Size of your container image

Cloud Run scales the number of container instances automatically based on the number of incoming requests.

Which of these is needed before deploying to Cloud Run?

A A virtual machine instance

B A physical server

C A container image in a registry

D A database connection

You must have your application packaged as a container image stored in a container registry before deploying to Cloud Run.

By default, who can access a Cloud Run service?

A No one until you configure access

B Only the developer

C Only users inside your company

D Anyone on the internet

Cloud Run services are publicly accessible by default over HTTPS unless you configure access restrictions.

What happens to Cloud Run instances when there is no traffic?

A They keep running at full capacity

B They scale down to zero

C They crash

D They switch to a backup server

Cloud Run scales down container instances to zero when there is no traffic, saving costs.

Which billing model does Cloud Run use?

A Pay only for the time your containers handle requests

B Pay a fixed monthly fee

C Pay per number of developers

D Pay for server uptime regardless of usage

Cloud Run charges you only for the time your containers are processing requests, not for idle time.

Explain how Cloud Run manages scaling for containerized services.

Think about how Cloud Run adjusts resources depending on traffic.

Describe the steps needed to deploy an application on Cloud Run.

Focus on what you need before and during deployment.

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