DauQuangThanh

google-cloud

2
2
# Install this skill:
npx skills add DauQuangThanh/hanoi-rainbow --skill "google-cloud"

Install specific skill from multi-skill repository

# Description

Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".

# SKILL.md


name: google-cloud
description: Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".


Google Cloud Platform (GCP)

Core Capabilities

Provides expert guidance for Google Cloud Platform across all major services:

  1. Compute Services - Compute Engine (VMs), Cloud Run, Cloud Functions, App Engine
  2. Container & Kubernetes - Google Kubernetes Engine (GKE), Artifact Registry, Cloud Build
  3. Storage Services - Cloud Storage (buckets), Persistent Disk, Filestore
  4. Database Services - Cloud SQL, Cloud Spanner, Firestore, Bigtable, Memorystore
  5. Data & Analytics - BigQuery, Dataflow, Dataproc, Pub/Sub, Composer
  6. Networking - VPC, Cloud Load Balancing, Cloud CDN, Cloud Armor, Cloud Interconnect
  7. Security & IAM - Identity and Access Management, Secret Manager, Cloud KMS, Security Command Center
  8. Infrastructure as Code - Terraform Google provider, Deployment Manager, Config Connector

Key Principles

General Best Practices

  • Follow least privilege - Use IAM roles with minimal required permissions
  • Enable monitoring - Configure Cloud Monitoring and Logging for all services
  • Use managed services - Prefer GKE Autopilot, Cloud SQL, Cloud Run over self-managed
  • Implement IaC - Use Terraform or Deployment Manager for reproducible infrastructure
  • Tag resources - Apply labels for cost allocation and organization
  • Design for HA - Use regional resources and multi-zone deployments
  • Secure by default - Enable encryption, use private IPs, configure VPC Service Controls
  • Optimize costs - Use committed use discounts, autoscaling, and appropriate resource sizing

Architecture Patterns

  • Multi-tier applications: VPC + Cloud Load Balancer + GKE/Cloud Run + Cloud SQL
  • Data pipelines: Pub/Sub → Dataflow → BigQuery with Cloud Storage staging
  • Serverless APIs: Cloud Run + Cloud SQL + Secret Manager + Cloud Armor
  • Hybrid connectivity: VPN or Cloud Interconnect + Shared VPC + Private Google Access

When to Use What

  • Compute Engine: Full VM control, Windows workloads, lift-and-shift migrations
  • GKE: Containerized applications, microservices, Kubernetes workloads
  • Cloud Run: Stateless HTTP services, event-driven processing, auto-scaling needs
  • Cloud Functions: Event handlers, webhooks, simple integrations
  • Cloud SQL: Relational databases with minimal management
  • Cloud Spanner: Global distributed SQL, strong consistency across regions
  • BigQuery: Data warehouse, analytics, large-scale SQL queries
  • Firestore: Document database, real-time sync, mobile/web apps

Detailed References

Load reference files based on specific needs:

  • Compute Services: See compute-services.md for:
  • Compute Engine machine types and selection guide
  • Managed instance groups and autoscaling
  • Custom images and startup scripts
  • Preemptible VMs and spot instances

  • Container Orchestration: See container-orchestration.md for:

  • GKE cluster setup and configuration
  • Autopilot vs Standard mode comparison
  • Node pool management and scaling
  • Workload identity and service accounts
  • GKE Ingress and Gateway API

  • Storage Solutions: See storage-solutions.md for:

  • Cloud Storage bucket configuration
  • Storage class selection and lifecycle policies
  • Persistent disk types and performance
  • Filestore for shared file systems

  • Database Services: See database-services.md for:

  • Cloud SQL instance configuration
  • Cloud Spanner for global databases
  • Firestore data modeling
  • Bigtable for large-scale NoSQL
  • Memorystore for Redis/Memcached

  • Data & Analytics: See data-analytics.md for:

  • BigQuery table design and optimization
  • Dataflow streaming and batch pipelines
  • Pub/Sub messaging patterns
  • Cloud Composer (Airflow) workflows
  • Data governance and security

  • Networking Architecture: See networking-architecture.md for:

  • VPC design patterns and subnet planning
  • Cloud Load Balancing configuration
  • Cloud CDN and Cloud Armor setup
  • VPN and Cloud Interconnect
  • Shared VPC and peering

  • Serverless Computing: See serverless-computing.md for:

  • Cloud Functions deployment and triggers
  • Cloud Run service configuration
  • App Engine standard and flexible
  • Event-driven architectures
  • Cold start optimization

  • Security & IAM: See security-iam.md for:

  • IAM roles and service accounts
  • Organization policies and constraints
  • VPC Service Controls
  • Secret Manager integration
  • Cloud KMS encryption
  • Security Command Center alerts

  • Infrastructure as Code: See infrastructure-as-code.md for:

  • Terraform Google provider patterns
  • Deployment Manager templates
  • Config Connector for GKE
  • CI/CD with Cloud Build
  • State management best practices

  • Migration to GCP: See migration-to-gcp.md for:

  • Migration planning and assessment
  • Migrate for Compute Engine (Velostrata)
  • Database migration service
  • Storage transfer service
  • Cutover strategies and validation

  • Monitoring & Logging: See monitoring-logging.md for:

  • Cloud Monitoring setup and metrics
  • Cloud Logging configuration
  • Log-based alerts and metrics
  • Cloud Trace for distributed tracing
  • Cloud Profiler for performance
  • Dashboards and SLO monitoring

  • CI/CD Pipeline: See cicd-pipeline.md for:

  • Cloud Build configuration
  • Artifact Registry for containers
  • Deployment to GKE, Cloud Run, App Engine
  • Binary Authorization for security
  • Integration with GitHub, GitLab

  • Cost Management: See cost-management.md for:

  • Billing reports and cost allocation
  • Budget alerts and quotas
  • Committed use discounts planning
  • Resource optimization strategies
  • Cost anomaly detection

  • Multi-Region Architecture: See multi-region-architecture.md for:

  • Global load balancing patterns
  • Multi-region database replication
  • Cross-region data transfer
  • Disaster recovery strategies
  • Regional failover setup

  • Hybrid & Multi-Cloud: See hybrid-multi-cloud.md for:

  • Anthos for hybrid Kubernetes
  • Cloud Interconnect and VPN
  • Multi-cloud networking patterns
  • Workload migration strategies
  • Identity federation

  • GCP CLI & Tools: See gcp-cli-tools.md for:

  • gcloud CLI installation and configuration
  • Common gcloud commands
  • Cloud Shell usage
  • gsutil for Cloud Storage
  • bq for BigQuery operations
  • kubectl for GKE management

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.