gcp-cloud-run – DevOps & Infrastructure skill for AI agents

GCP Cloud Run

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-driven architecture with Pub/Sub.

<!-- Modified 2026-10-23: scoped deployment and reliability limits. -->

Deployment prerequisites

Examples are incomplete integration sketches: application helpers, IAM roles, queues, regions and health/startup probes must be supplied. Select an authorized project/service and budget, private ingress/auth by default, versioned Artifact Registry image and rollback revision. Historical nodejs20/GCR examples require supported-runtime and registry migration checks. Bound max instances and aggregate DB connections; minimum instances and boosts incur costs. A 2xx response must follow completed or durably enqueued work, with idempotency for retries. psutil host-memory readings may not reflect the container cgroup limit; use Cloud Monitoring/container metrics.

Detailed Guide

Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.

Calculate memory including /tmp usage

# cloudbuild.yaml
steps:
  - name: 'gcr.io/cloud-builders/gcloud'
    args:
      - 'run'
      - 'deploy'
      - 'my-service'
      - '--memory=1Gi'  # Include /tmp overhead
      - '--image=gcr.io/$PROJECT_ID/my-service'

Monitor memory usage

import psutil
import logging

def log_memory():
    memory = psutil.virtual_memory()
    logging.info(f"Memory: {memory.percent}% used, "
                f"{memory.available / 1024 / 1024:.0f}MB available")

Concurrency=1 Causes Scaling Bottlenecks

Severity: HIGH

Situation: Setting concurrency to 1 for request isolation

Symptoms:

Auto-scaling creates many container instances.

High latency during traffic spikes.

Increased cold starts.

Higher costs from more instances.

Why this breaks:

Setting concurrency to 1 means each container handles only one

request at a time. During traffic spikes:

• 100 simultaneous in-flight requests may need up to 100 instances, subject to capacity, queuing and limits
• Each instance has cold start overhead
• More instances = higher costs
• Scaling takes time, requests queue up

This should only be used when:

• Processing is truly single-threaded
• Memory-heavy per-request processing
• Using thread-unsafe libraries

Recommended fix: Load-test a concurrency matching handler thread safety, peak memory, latency and downstream connection limits; concurrency 1 can be appropriate.

When to Use

Use this skill when the request clearly matches the capabilities and patterns described above.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.