cloud

## What I do - Design cloud architectures - Choose appropriate cloud services - Optimize cloud costs - Ensure cloud security - Implement cloud-native patterns ## When to use me When building cloud-native applications, migrating to cloud, or designing scalable systems. ## Cloud Service Models ### IaaS (Infrastructure as a Service) - Virtual machines - Networking - Storage - Examples: AWS EC2, GCP Compute Engine, Azure VMs - Pros: Full control, flexibility - Cons: Management overhead ### PaaS (Platform as a Service) - Runtime environments - Databases - Message queues - Examples: Heroku, Cloud Run, App Service - Pros: Less management - Cons: Less control ### SaaS (Software as a Service) - Complete applications - Examples: Salesforce, Office 365, Slack - Pros: No management - Cons: Least customization ## Cloud Concepts ### Compute - Virtual machines - Containers (ECS, EKS, AKS, GKE) - Serverless (Lambda, Cloud Functions, Azure Functions) - Container instances ### Storage - Object storage (S3, GCS, Blob) - Block storage (EBS, PD, Managed Disks) - File storage (EFS, Filestore) - Archive storage (Glacier, Archive) ### Networking - VPCs and subnets - Load balancers - CDN - DNS - VPN/Direct Connect - Private endpoints ### Databases - RDBMS (RDS, Cloud SQL, Azure SQL) - NoSQL (DynamoDB, Cosmos DB, MongoDB Atlas) - Caching (ElastiCache, Memorystore) - Data warehousing (Redshift, BigQuery, Synapse) ### Security - Identity management (IAM) - Security groups - Encryption at rest/transit - Key management (KMS) - Firewall rules - Compliance certifications ### Cost Optimization - Right-sizing resources - Reserved instances - Spot/preemptible instances - Savings plans - Cost monitoring - Auto-scaling ## Cloud-Native Patterns - Microservices - Containerization - Orchestration - Service mesh - Observability - CI/CD automation - Infrastructure as Code