techwavedev 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
# 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']
```javascript
// 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 function
gcloud functions deploy process-uploads \
--gen2 \
--runtime nodejs20 \
--trigger-event-filters="type=google.cloud.storage.object.v1.finalized" \
--trigger-event-filters="bucket=my-bucket" \
--region us-central1
### Cold Start Optimization Pattern
Minimize cold start latency for Cloud Run
**When to use**: ['Latency-sensitive applications', 'User-facing APIs', 'High-traffic services']
```javascript
## 1. Enable Startup CPU Boost
```bash
gcloud run deploy my-service \
--cpu-boost \
--region us-central1
2. Set Minimum Instances
gcloud run deploy my-service \
--min-instances 1 \
--region us-central1
3. Optimize Container Image
# Use distroless for minimal image
FROM node:20-slim AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
FROM gcr.io/distroless/nodejs20-debian12
WORKDIR /app
COPY --from=builder /app/node_modules ./node_modules
COPY src ./src
CMD ["src/index.js"]
4. Lazy Initialize Heavy Dependencies
// Lazy load heavy libraries
let bigQueryClient = null;
function getBigQueryClient() {
if (!bigQueryClient) {
const { BigQuery } = require('@google-cloud/bigquery');
bigQueryClient = new BigQuery();
}
return bigQueryClient;
}
// Only initialize when needed
app.get('/api/analytics', async (req, res) => {
const client = getBigQueryClient();
const results = await client.query({...});
res.json(results);
});
5. Increase Memory (More CPU)
# Higher memory = more CPU during startup
gcloud run deploy my-service \
--memory 1Gi \
--cpu 2 \
--region us-central1
## Anti-Patterns
### ❌ CPU-Intensive Work Without Concurrency=1
**Why bad**: CPU is shared across concurrent requests. CPU-bound work
will starve other requests, causing timeouts.
### ❌ Writing Large Files to /tmp
**Why bad**: /tmp is an in-memory filesystem. Large files consume
your memory allocation and can cause OOM errors.
### ❌ Long-Running Background Tasks
**Why bad**: Cloud Run throttles CPU to near-zero when not handling
requests. Background tasks will be extremely slow or stall.
## ⚠️ Sharp Edges
| Issue | Severity | Solution |
|-------|----------|----------|
| Issue | high | ## Calculate memory including /tmp usage |
| Issue | high | ## Set appropriate concurrency |
| Issue | high | ## Enable CPU always allocated |
| Issue | medium | ## Configure connection pool with keep-alive |
| Issue | high | ## Enable startup CPU boost |
| Issue | medium | ## Explicitly set execution environment |
| Issue | medium | ## Set consistent timeouts |
## When to Use
This skill is applicable to execute the workflow or actions described in the overview.
---
<!-- AGI-INTEGRATION-START -->
## AGI Framework Integration
> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)
### Memory-First Protocol
Retrieve prior deployment configurations, rollback procedures, and incident post-mortems. Avoid re-discovering infrastructure patterns.
```bash
# Check for prior infrastructure context before starting
python3 execution/memory_manager.py auto --query "deployment configuration and patterns for Gcp Cloud Run"
Storing Results
After completing work, store infrastructure decisions for future sessions:
python3 execution/memory_manager.py store \
--content "Deployment pipeline: configured blue-green deployment with health checks on port 8080" \
--type technical --project <project> \
--tags gcp-cloud-run devops
Multi-Agent Collaboration
Broadcast deployment changes so frontend and backend agents update their configurations accordingly.
python3 execution/cross_agent_context.py store \
--agent "<your-agent>" \
--action "Deployed infrastructure changes — updated CI/CD pipeline with new health check endpoints" \
--project <project>
Playbook Integration
Use the ship-saas-mvp or full-stack-deploy playbook to sequence this skill with testing, documentation, and deployment verification.