Cloud Run service concept in GCP - Step-by-Step Execution

Process Flow - Cloud Run service concept

Write containerized app

↓

Push container image to registry

↓

Create Cloud Run service

↓

Cloud Run deploys container

↓

Service receives HTTP request

↓

Container handles request and responds

↓

Scale up/down based on traffic

↓

End

This flow shows how a containerized app is deployed to Cloud Run, which runs it on demand and scales automatically.

Execution Sample

GCP

gcloud run deploy my-service --image gcr.io/my-project/my-image --platform managed

Deploys a container image as a Cloud Run service that runs and scales automatically.

Process Table

Step	Action	Input/Condition	Result/Output
1	Write containerized app	App code + Dockerfile	Container image ready
2	Push container image	Container image	Image stored in registry
3	Deploy Cloud Run service	Image URL	Service created and running
4	Send HTTP request	Request arrives at service URL	Request routed to container
5	Container handles request	Request data	Response sent back
6	Scale based on traffic	Number of requests	Containers scale up/down
7	No requests	Idle state	Containers scale to zero
8	Stop	No more requests	Service waits for next request

💡 Execution stops when no requests are received and containers scale to zero, waiting for new requests.

Status Tracker

Variable	Start	After Step 2	After Step 3	After Step 6	Final
Container Image	Not built	Built and pushed	Used by Cloud Run	Used for scaling	Stored in registry
Cloud Run Service	Not created	Not created	Created and running	Scaling containers	Waiting for requests
Containers Running	0	0	1 (initial)	Varies with traffic	0 (idle)

Key Moments - 3 Insights

Why does Cloud Run scale containers to zero when idle?

Cloud Run scales to zero to save resources and cost when no requests are received, as shown in execution_table step 7.

How does Cloud Run know which container image to run?

The container image URL provided during deployment (step 3) tells Cloud Run which image to use.

What happens when a new request arrives and no containers are running?

Cloud Run automatically starts a container to handle the request, scaling from zero as in step 4 and 5.

Visual Quiz - 3 Questions

Look at the execution_table, at which step does Cloud Run create the service?

A Step 2

B Step 3

C Step 5

D Step 7

💡 Hint

Check the 'Action' column for 'Deploy Cloud Run service' in execution_table.

According to variable_tracker, what is the number of running containers after step 6?

A Varies with traffic

B 1 (initial)

C 0

D Not created

💡 Hint

Look at the 'Containers Running' row under 'After Step 6' in variable_tracker.

If no requests come in, what does Cloud Run do according to the execution_table?

A Deletes the service

B Keeps containers running

C Scales containers to zero

D Returns error

💡 Hint

See step 7 in execution_table about scaling behavior when idle.

Concept Snapshot

Cloud Run runs containerized apps on demand.
Deploy by pushing container image and creating a service.
Service handles HTTP requests and scales automatically.
Scales to zero when idle to save cost.
Simple command: gcloud run deploy --image IMAGE_URL

Full Transcript

Cloud Run lets you run your containerized app without managing servers. First, you write your app and package it into a container image. Then you push this image to a container registry. Next, you deploy the image to Cloud Run, which creates a service. When someone sends an HTTP request to the service URL, Cloud Run starts a container to handle it. If many requests come, Cloud Run automatically adds more containers. When no requests come, it scales down to zero containers to save resources. This process is simple and automatic, making it easy to run apps in the cloud.

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