Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
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Design and operate GCP: architectures with Terraform IaC, Cloud Run, BigQuery pipelines, cost optimization and Cloud Build CI/CD, plus day-2 operations for IAM and Secret Manager, Cloud Run, functions, Cloud SQL, Compute Engine, networking and audit logs.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Design scalable, cost-effective Google Cloud architectures for startups and enterprises with infrastructure-as-code templates.
Collect application specifications:
Select from recommended patterns:
See references/architecture_patterns.md for detailed pattern specifications with service stacks, Terraform configs, and cost estimates.
Validation checkpoint: Confirm the recommended pattern matches the team's operational maturity and compliance requirements before proceeding.
python scripts/cost_optimizer.py --resources current_setup.json --monthly-spend 2000
Output includes monthly cost breakdown, right-sizing recommendations, committed use discount opportunities, and sustained use discount analysis. Use the GCP Pricing Calculator for detailed estimates.
python scripts/deployment_manager.py --app-name my-app --pattern serverless_web --region us-central1
Generates production-ready Terraform HCL and gcloud CLI scripts. See references/architecture_patterns.md for full template examples including Cloud CDN, Identity Platform, IAM, and Cloud Monitoring.
Set up automated deployment with Cloud Build or GitHub Actions. See references/best_practices.md for cloudbuild.yaml templates and trigger configuration.
Verify security configuration:
Recommends GCP services based on workload requirements.
python scripts/architecture_designer.py --input requirements.json --output design.json
Analyzes GCP resources for cost savings: idle removal, right-sizing, committed use discounts, storage transitions.
python scripts/cost_optimizer.py --resources inventory.json --monthly-spend 5000
Generates gcloud CLI scripts and Terraform configurations.
python scripts/deployment_manager.py --app-name my-app --pattern serverless_web --region us-central1
| Scenario | Architecture | Estimated Cost |
|---|---|---|
| Web App on Cloud Run (<1k users) | Cloud Run + Firestore + Identity Platform + Cloud CDN | $15-40/mo |
| Microservices SaaS (50k users) | GKE Autopilot + Cloud SQL + Memorystore + Cloud Build | $500-2000/mo |
| Serverless Data Pipeline | Pub/Sub + Dataflow + BigQuery + Looker | Variable |
| ML Platform | Vertex AI + Cloud Storage + BigQuery + Cloud Functions | Variable |
| Anti-Pattern | Better Approach |
|---|---|
| Using default VPC for production | Custom VPC with private subnets |
| Over-provisioning GKE node pools | GKE Autopilot or cluster autoscaler |
| Storing secrets in env vars | Secret Manager with Workload Identity |
| Single-region deployment for SaaS | Multi-region with Cloud Load Balancing |
| BigQuery on-demand for heavy workloads | BigQuery slots (flat-rate) for consistency |
| Cloud Functions for long tasks (>60s) | Cloud Run for longer-running tasks |
Once it runs, read only the file for the service at hand. Engine-level database work is in /database-ops, backups in /backup-strategy, rollback with revisions in /rollback-strategy, incidents in /incident-response.
| Area | Reference | Covers |
|---|---|---|
| IAM and secrets | references/ops-iam-secrets.md | One service account per service, GitHub through Workload Identity Federation, Secret Manager access and rotation, auditing |
| Cloud Run | references/ops-cloud-run.md | Concurrency, min/max instances, billing mode, probes, ingress and VPC egress, deploys, debugging |
| Cloud Run functions | references/ops-cloud-functions.md | Deploys, Eventarc triggers and idempotency, retries and dead letters, scheduled calls, debugging |
| Cloud SQL | references/ops-cloud-sql.md | Private IP and the Auth Proxy, IAM auth, HA, maintenance, restores, alerts |
| Compute Engine | references/ops-compute.md | Regional MIGs with autohealing, OS Login and IAP SSH, snapshots, debugging |
| Networking | references/ops-networking.md | Custom VPC, firewall by service account, Cloud NAT, private access, load balancer with Cloud Armor, Connectivity Tests |
| Audit logs | references/ops-audit-logs.md | Log types and defaults, Data Access logs, sinks, investigation queries, alerts |
| Document | Contents |
|---|---|
references/architecture_patterns.md | 6 patterns with Terraform configs, gcloud scripts, cost estimates |
references/service_selection.md | Decision matrices for compute, database, storage, messaging |
references/best_practices.md | Naming, labels, IAM, networking, monitoring, DR |
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Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
中文简介正在准备中。当前显示原文说明。
Web/mobile accessibility decision guide: WCAG 2.2 AA, ARIA, keyboard nav, focus management, contrast, testing. Use for: a11y, accessibility, wcag, aria, screen reader, keyboard, contrast.
中文简介正在准备中。当前显示原文说明。
Generate, iterate, and scale ad creative for paid advertising across Google, Meta, LinkedIn, and X. Covers platform specs, creative frameworks, and quality validation.
中文简介正在准备中。当前显示原文说明。
Musica interactiva para juegos: layering vertical, re-secuenciacion horizontal, stingers, reglas de transicion con sync points, y mapeo de estados de gameplay a musica. Usar para: musica adaptativa, sistema de musica dinamica, transiciones musicales, combat music.
中文简介正在准备中。当前显示原文说明。
Design multi-agent systems, create agent architectures, define communication patterns, and build autonomous agent workflows with structured evaluation frameworks.
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Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, response formats, and quality loops.
中文简介正在准备中。当前显示原文说明。