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