Gcp Cloud Run
Gcp Cloud Run is an code AI skill with a core value of Specialized skill for building production-ready serverless applications on GCP. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-dri...
Quick Facts
mkdir -p ./skills/gcp-cloud-run && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/gcp-cloud-run/SKILL.md -o ./skills/gcp-cloud-run/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# GCP Cloud Run
Patterns
Cloud Run Service Pattern
Containerized web service on Cloud Run
**When to use**: ['Web applications and APIs', 'Need any runtime or library', 'Complex services with multiple endpoints', 'Stateless containerized workloads']
# Dockerfile - Multi-stage build for smaller image
FROM node:20-slim AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
FROM node:20-slim
WORKDIR /app
# Copy only production dependencies
COPY --from=builder /app/node_modules ./node_modules
COPY src ./src
COPY package.json ./
# Cloud Run uses PORT env variable
ENV PORT=8080
EXPOSE 8080
# Run as non-root user
USER node
CMD ["node", "src/index.js"]
// src/index.js
const express = require('express');
const app = express();
app.use(express.json());
// Health check endpoint
app.get('/health', (req, res) => {
res.status(200).send('OK');
});
// API routes
app.get('/api/items/:id', async (req, res) => {
try {
const item = await getItem(req.params.id);
res.json(item);
} catch (error) {
console.error('Error:', error);
res.status(500).json({ error: 'Internal server error' });
}
});
// Graceful shutdown
process.on('SIGTERM', () => {
console.log('SIGTERM received, shutting down gracefully');
server.close(() => {
console.log('Server closed');
process.exit(0);
});
});
const PORT = process.env.PORT || 8080;
const server = app.listen(PORT, () => {
console.log(`Server listening on port ${PORT}`);
});
# cloudbuild.yaml
steps:
# Build the container image
- name: 'gcr.io/cloud-builders/docker'
args: ['build', '-t', 'gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA', '.']
# Push the container image
- name: 'gcr.io/cloud-builders/docker'
args: ['push', 'gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA']
# Deploy to Cloud Run
- name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'
entrypoint: gcloud
args:
- 'run'
- 'deploy'
- 'my-service'
- '--image=gcr.io/$PROJECT_ID/my-service:$COMMIT_SHA'
- '--region=us-central1'
- '--platform=managed'
- '--allow-unauthenticated'
- '--memory=512Mi'
- '--cpu=1'
- '--min-instances=1'
- '--max-instances=100'
### Cloud Run Functions Pattern
Event-driven functions (formerly Cloud Functions)
**When to use**: ['Simple event handlers', 'Pub/Sub message processing', 'Cloud Storage triggers', 'HTTP webhooks']
// HTTP Function
// index.js
const functions = require('@google-cloud/functions-framework');
functions.http('helloHttp', (req, res) => {
const name = req.query.name || req.body.name || 'World';
res.send(`Hello, ${name}!`);
});// Pub/Sub Function
const functions = require('@google-cloud/functions-framework');
functions.cloudEvent('processPubSub', (cloudEvent) => {
// Decode Pub/Sub message
const message = cloudEvent.data.message;
const data = message.data
? JSON.parse(Buffer.from(message.data, 'base64').toString())
: {};
console.log('Received message:', data);
// Process message
processMessage(data);
});// Cloud Storage Function
const functions = require('@google-cloud/functions-framework');
functions.cloudEvent('processStorageEvent', async (cloudEvent) => {
const file = cloudEvent.data;
console.log(`Event: ${cloudEvent.type}`);
console.log(`Bucket: ${file.bucket}`);
console.log(`File: ${file.name}`);
if (cloudEvent.type === 'google.cloud.storage.object.v1.finalized') {
await processUploadedFile(file.bucket, file.name);
}
});# Deploy HTTP function
gcloud functions deploy hello-http \
--gen2 \
--runtime nodejs20 \
--trigger-http \
--allow-unauthenticated \
--region us-central1
# Deploy Pub/Sub function
gcloud functions deploy process-messages \
--gen2 \
--runtime nodejs20 \
--trigger-topic my-topic \
--region us-central1
# Deploy Cloud Storage funct🎯 Best For
- UI designers
- Product designers
- Claude users
- Software engineers
- Development teams
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Gcp Cloud Run to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
Is Gcp Cloud Run compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Gcp Cloud Run?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Gcp Cloud Run?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/gcp-cloud-run/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.