gcp-cloud-architect
Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. Covers Cloud Run, GKE, Cloud Functions, Cloud SQL, BigQuery, and cost optimization.
Profile →npx skills add alirezarezvani/claude-skills --skill gcp-cloud-architect --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# GCP Cloud Architect Design scalable, cost-effective Google Cloud architectures for startups and enterprises with infrastructure-as-code templates. --- ## Workflow ### Step 1: Gather Requirements Collect application specifications: ``` - Application type (web app, mobile backend, data pipeline, SaaS) - Expected users and requests per second - Budget constraints (monthly spend limit) - Team size and GCP experience level - Compliance requirements (GDPR, HIPAA, SOC 2) - Availability requirements (SLA, RPO/RTO) ``` ### Step 2: Design Architecture Run the architecture designer to get pattern recommendations: ```bash python scripts/architecture_designer.py --input requirements.json ``` **Example output:** ```json { "recommended_pattern": "serverless_web", "service_stack": ["Cloud Storage", "Cloud CDN", "Cloud Run", "Firestore", "Identity Platform"], "estimated_monthly_cost_usd": 30, "pros": ["Low ops overhead", "Pay-per-use", "Auto-scaling", "No cold starts on Cloud Run min instances"], "cons": ["Vendor lock-in", "Regional limitations", "Eventual consistency with Firestore"] } ``` Select from recommended patterns: - **Serverless Web**: Cloud Storage + Cloud CDN + Cloud Run + Firestore -
- Workflow
- Step 1: Gather Requirements
- Step 2: Design Architecture
- Step 3: Estimate Cost
- Step 4: Generate IaC
- Step 5: Configure CI/CD
- Step 6: Security Review
- Tools
- architecturedesigner.py
- costoptimizer.py
- deploymentmanager.py
- Quick Start
- Web App on Cloud Run (< $100/month)
- Microservices on GKE ($500-2000/month)
python scripts/architecture_designer.py --input requirements.json python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000 python scripts/deployment_manager.py --app-name my-app --pattern serverless_web --region us-central1 Deploy Cloud Run service gcloud run deploy my-app-api \ Create Firestore database gcloud firestore databases create --location=us-central1 Connect repo and create trigger gcloud builds triggers create github \ Review IAM bindings
What does the gcp-cloud-architect skill do?
Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. Covers Cloud Run, GKE, Cloud Functions, Cloud SQL, BigQuery, and cost optimization.
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill gcp-cloud-architect --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.