What is AWS Cost Optimization strategies?
Why Interviewers Ask This
Candidates at the intermediate level are expected to not only know this concept but explain the trade-offs involved. Interviewers use this question to see if you can reason about design decisions, not just recall facts.
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.
Pro Tip
Demonstrate both theoretical understanding and practical experience. Say what it is, then give an example of how you actually used it in a AWS / Cloud Computing codebase.