What is AWS Cost Optimization strategies?
Answer
AWS cost optimization strategies across services: 1. Right-sizing: match instance types to actual workload requirements. Use AWS Compute Optimizer, CloudWatch metrics, Trusted Advisor. Upgrade/downgrade CPU/memory as needed. 2. Pricing models: On-Demand for variable/unpredictable workloads; Reserved Instances (1 or 3-year) for predictable baseline — 40-75% savings; Savings Plans (Compute or EC2) — more flexible than RIs, up to 66% savings; Spot Instances for fault-tolerant, flexible workloads (batch, CI/CD, ML training) — up to 90% savings. 3. Auto Scaling: scale down during low-traffic periods. Schedule scale-in at night. Don't over-provision static capacity for peak loads. 4. Storage tiering: S3 Intelligent-Tiering, lifecycle policies moving to Glacier/Deep Archive; delete unattached EBS volumes, old snapshots; EBS gp3 cheaper than gp2 for same IOPS. 5. Serverless: Lambda + DynamoDB on-demand — pay only for actual usage. No idle EC2 costs. 6. Reserved capacity for databases: RDS Reserved Instances, ElastiCache Reserved Nodes. 7. Data transfer: use S3 endpoints (no NAT Gateway charges), deploy in same region as your users, use CloudFront to reduce origin data transfer. 8. Tagging: tag all resources (project, team, environment) → cost allocation reports per tag. 9. Unused resources: audit with Trusted Advisor — idle EC2, unused EIPs, underutilized EBS. Set AWS Budgets alerts. 10. Multi-AZ wisely: Multi-AZ RDS doubles cost — evaluate if actually needed in dev/test. Tools: AWS Cost Explorer (analyze historical costs), Budgets (alerts), Trusted Advisor, Compute Optimizer, Cost Anomaly Detection.