---

CRITICAL: DEPLOYMENT SAFETY GUARDRAILS

BEFORE any deployment, validate:

• All tests passing (unit, integration, E2E, load)
• Security scan completed (SAST, DAST, dependency audit)
• Infrastructure capacity verified (CPU, memory, disk, network)
• Database migrations tested on production-like data volume
• Rollback procedure documented with time estimates

NEVER:

• Deploy without comprehensive monitoring (metrics, logs, traces)
• Skip load testing for high-traffic services
• Deploy breaking changes without backward compatibility
• Ignore security vulnerabilities in production dependencies
• Deploy without incident response plan

ALWAYS:

• Validate deployment checklist before proceeding
• Use feature flags for risky changes (gradual rollout)
• Monitor error rates, latency p99, and saturation metrics
• Document deployment in runbook with troubleshooting steps
• Retain deployment artifacts for forensic analysis

Evidence-Based Techniques for Deployment:

• Chain-of-Thought: Trace deployment flow (code -> artifact -> registry -> cluster -> pods)
• Program-of-Thought: Model deployment as state machine (pre-deploy -> deploy -> post-deploy -> verify)
• Reflection: After deployment, analyze what worked vs assumptions
• Retrieval-Augmented: Query past incidents for similar deployment patterns

name: cloud-platforms description: Multi-cloud deployment and infrastructure management across AWS, GCP, and Azure. Use when deploying applications to cloud platforms, implementing serverless architectures, or managing cloud infrastructure as code. Supports containers, serverless, and traditional compute. tier: gold version: 2.0.0 last_updated: 2025-11-02 category: operations tags:

• operations
• deployment
• infrastructure author: ruv

---

Cloud Platforms - Multi-Cloud Infrastructure ⭐ GOLD TIER

Comprehensive cloud deployment and management for AWS, Google Cloud, and Azure platforms with production-ready automation scripts, infrastructure templates, and multi-cloud testing.

Tier: Gold Version: 2.0.0 Files: 20 Scripts: 4 automation tools Templates: 4 IaC configurations Tests: 3 comprehensive suites

When to Use This Skill

Use when deploying applications to cloud platforms, implementing serverless architectures (Lambda, Cloud Functions), managing containerized workloads (ECS, GKE, AKS), or provisioning cloud infrastructure with Terraform/CloudFormation.

Supported Platforms

AWS (Amazon Web Services)

• Compute: EC2, Lambda, ECS, Fargate, Batch
• Storage: S3, EBS, EFS, Glacier
• Database: RDS, DynamoDB, Aurora, Redshift
• Networking: VPC, Route 53, CloudFront, API Gateway
• IaC: CloudFormation, AWS CDK

Google Cloud Platform

• Compute: Compute Engine, Cloud Functions, GKE, Cloud Run
• Storage: Cloud Storage, Persistent Disk, Filestore
• Database: Cloud SQL, Firestore, BigQuery, Spanner
• Networking: VPC, Cloud CDN, Cloud Load Balancing
• IaC: Deployment Manager, Terraform

Microsoft Azure

• Compute: VMs, Azure Functions, AKS, Container Instances
• Storage: Blob Storage, Disk Storage, Azure Files
• Database: SQL Database, Cosmos DB, Synapse Analytics
• Networking: Virtual Network, Traffic Manager, Front Door
• IaC: ARM Templates, Bicep, Terraform

Process

1. Define requirements

   • Determine workload type (compute, storage, database)
   • Assess scaling needs
   • Identify compliance requirements
   • Estimate costs

2. Select platform and services

   • Choose cloud provider (AWS/GCP/Azure)
   • Pick appropriate services for workload
   • Design for high availability
   • Plan disaster recovery

3. Provision infrastructure

   • Use Infrastructure as Code (Terraform, CloudFormation)
   • Implement security best practices
   • Configure networking and access
   • Set up monitoring and logging

4. Deploy applications

   • Containerize with Docker
   • Use CI/CD pipelines
   • Implement blue-green or canary deployments
   • Configure auto-scaling

5. Monitor and optimize

   • Track resource utilization
   • Optimize costs (right-sizing, spot instances)
   • Review security posture
   • Implement performance improvements

Best Practices

• Multi-region: Deploy across regions for high availability
• Infrastructure as Code: Never provision manually
• Cost Optimization: Use reserved instances, spot instances
• Security: Least privilege IAM, encryption at rest/transit
• Monitoring: CloudWatch, Stackdriver, Azure Monitor

🚀 Automation Tools (Gold Tier)

Deployment Scripts

Located in resources/scripts/:

1. deploy_aws.py (14 KB)

   • AWS Lambda, ECS Fargate, CloudFormation, EC2 deployment
   • Usage: python deploy_aws.py lambda --name func --zip code.zip --handler index.handler

2. deploy_k8s.sh (8.3 KB)

   • Kubernetes kubectl, Helm chart deployment
   • Usage: ./deploy_k8s.sh helm myapp ./charts/app production values.yaml

3. terraform_apply.py (13 KB)

   • Terraform automation with validation, planning, state management
   • Usage: python terraform_apply.py apply --var-file prod.tfvars

4. gcp_deploy.sh (10 KB)

   • GCP Cloud Run, Cloud Functions, GKE, Compute Engine deployment
   • Usage: ./gcp_deploy.sh cloud-run myservice gcr.io/project/image us-central1

Infrastructure Templates

Located in resources/templates/:

1. aws-infra.tf (14 KB)

   • Complete AWS VPC, ALB, ECS Fargate, RDS setup
   • 30+ Terraform resources for production deployment

2. k8s-deployment.yaml (7.2 KB)

   • Production Kubernetes manifest with HPA, Ingress, PDB
   • 10 K8s resources with health checks and monitoring

3. gcp-config.json (8.9 KB)

   • Comprehensive GCP configuration for Cloud Run, GKE, Cloud SQL
   • 9 major configuration sections

4. docker-compose.yaml (7.5 KB)

   • Full local development stack (11 services)
   • Web, DB, cache, monitoring, worker, scheduler

Test Suites

Located in tests/:

1. test-1-aws-deployment.md (9 KB)

   • 4 scenarios: Lambda, ECS, Terraform, CloudFormation
   • Complete testing procedures with validation

2. test-2-k8s-cluster.md (12 KB)

   • 5 scenarios: Local cluster, Helm, ConfigMaps, rolling updates, GKE
   • Performance and load testing included

3. test-3-multi-cloud.md (19 KB)

   • 5 scenarios: Parallel deploy, DB replication, GeoDNS, cost analysis, DR
   • Multi-cloud best practices and failover testing

Quick Start Examples

Deploy to AWS with Terraform

cd resources/templates
cp aws-infra.tf main.tf
echo 'project_name = "myapp"
environment = "prod"
container_image = "nginx:latest"' > terraform.tfvars

python ../scripts/terraform_apply.py init
python ../scripts/terraform_apply.py apply --var-file terraform.tfvars

Deploy to Kubernetes

# Using kubectl
./resources/scripts/deploy_k8s.sh kubectl resources/templates/k8s-deployment.yaml production

# Using Helm
./resources/scripts/deploy_k8s.sh helm myapp ./charts/myapp production values.yaml

Deploy to GCP

# Cloud Run
./resources/scripts/gcp_deploy.sh cloud-run myservice gcr.io/project/image us-central1

# GKE cluster
./resources/scripts/gcp_deploy.sh create-gke mycluster us-central1-a e2-medium 3 true

Multi-Cloud Support

• AWS: Lambda, ECS Fargate, EC2, RDS, S3, CloudFormation
• GCP: Cloud Run, Cloud Functions, GKE, Cloud SQL, GCR
• Kubernetes: GKE, EKS, AKS, Kind, Minikube
• Infrastructure: Terraform, Docker Compose

Testing

Run comprehensive test suites:

# AWS deployment tests
cd tests
bash test-1-aws-deployment.md

# Kubernetes cluster tests
bash test-2-k8s-cluster.md

# Multi-cloud tests
bash test-3-multi-cloud.md

Documentation

See ENHANCEMENT-SUMMARY.md for complete Gold tier enhancement details including:

• All 11 new files created
• Usage examples for each script
• Performance metrics
• Cost estimates
• Troubleshooting guide