gcp-cloud-run
Automates the deployment of containerized HTTP applications to Google Cloud Run.
Install
mkdir -p .claude/skills/gcp-cloud-run && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/239" && unzip -o skill.zip -d .claude/skills/gcp-cloud-run && rm skill.zipInstalls to .claude/skills/gcp-cloud-run
Activation
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Deploy containerized applications on Google Cloud Run with automatic scaling, traffic management, and service mesh integration. Use for container-based serverless computing.Key capabilities
- →Deploy containerized applications to serverless environments
- →Manage traffic splitting and revisions
- →Configure IAM policies for service access
- →Set environment variables and resource limits
- →Integrate with Cloud Logging and Cloud Armor
How it works
The skill automates the deployment of stateless containers to Google Cloud Run, managing infrastructure scaling and traffic routing via gcloud CLI commands.
Inputs & outputs
When to use gcp-cloud-run
- →Deploy microservices or APIs
- →Run batch processing jobs
- →Host web backends
- →Manage background workers
About this skill
GCP Cloud Run
Table of Contents
Overview
Google Cloud Run enables deployment of containerized applications at scale without managing infrastructure. Run stateless HTTP containers with automatic scaling from zero to thousands of instances, paying only for compute time consumed.
When to Use
- Microservices and APIs
- Web applications and backends
- Batch processing jobs
- Long-running background workers
- CI/CD pipeline integration
- Data processing pipelines
- WebSocket applications
- Multi-language services
Quick Start
Minimal working example:
# Build container image
gcloud builds submit --tag gcr.io/MY_PROJECT_ID/my-app:latest
# Deploy to Cloud Run
gcloud run deploy my-app \
--image gcr.io/MY_PROJECT_ID/my-app:latest \
--platform managed \
--region us-central1 \
--memory 512Mi \
--cpu 1 \
--timeout 3600 \
--max-instances 100 \
--min-instances 1 \
--no-allow-unauthenticated \
--set-env-vars NODE_ENV=production,DATABASE_URL=postgresql://...
# Allow public access
gcloud run services add-iam-policy-binding my-app \
--platform managed \
--region us-central1 \
--member=allUsers \
--role=roles/run.invoker
# Get service URL
gcloud run services describe my-app \
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Cloud Run Deployment with gcloud CLI | Cloud Run Deployment with gcloud CLI |
| Containerized Application (Node.js) | Containerized Application (Node.js) |
| Terraform Cloud Run Configuration | Terraform Cloud Run Configuration |
| Docker Build and Push | Docker Build and Push |
Best Practices
✅ DO
- Use container health checks
- Set appropriate CPU and memory
- Implement graceful shutdown
- Use service accounts with least privilege
- Monitor with Cloud Logging
- Enable Cloud Armor for protection
- Use revision management for blue-green deployments
- Implement startup and liveness probes
❌ DON'T
- Store secrets in code
- Use default service account
- Create stateful applications
- Ignore health checks
- Deploy without testing
- Use excessive resource limits
- Store files in container filesystem
When not to use it
- →When the application requires a stateful filesystem
- →When managing long-running processes exceeding timeout limits
Prerequisites
Limitations
- →Cannot store persistent state in the container filesystem
- →Requires adherence to stateless architectural patterns
How it compares
It automates the entire deployment lifecycle including IAM binding and resource allocation, replacing manual console configuration.
Compared to similar skills
gcp-cloud-run side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| gcp-cloud-run (this skill) | 5 | 5mo | Review | Intermediate |
| deployment-engineer | 4 | 4mo | No flags | Advanced |
| build-release | 1 | 5mo | Review | Intermediate |
| publish-mock-server | 1 | 6mo | Review | Beginner |
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