AWS Cost Optimization

Evaluate current AWS costs and produce actionable optimization suggestions across compute, storage, networking, and managed services.

Do not use this skill when

• •The task targets Azure, GCP, or a non-AWS provider
• •The task is about general application performance without a cost dimension

Instructions

1. •Identify the AWS services in scope (EC2, S3, RDS, Lambda, etc.).
2. •Apply the Cost Optimization Framework top-to-bottom: Visibility → Right-Sizing → Pricing → Architecture.
3. •For each service, check the Service-Specific Quick Reference below.
4. •Generate a prioritized list of suggestions with estimated savings.
5. •For Terraform/CLI/boto3 implementation details, open references/implementation-playbook.md.

Cost Optimization Framework

1. Visibility — Know What You Spend

2. Right-Sizing — Stop Over-Provisioning

Use AWS Compute Optimizer and Trusted Advisor for automated right-sizing recommendations.

3. Pricing Models — Pay Less Per Unit

Decision heuristic:

1. •Steady 24/7 → Savings Plan or RI
2. •Batch / stateless → Spot with On-Demand fallback
3. •Unknown workload → start On-Demand, analyze with Cost Explorer, then commit

4. Architecture — Spend Smarter

Service-Specific Quick Reference

EC2

• •Use Graviton (c7g, m7g, r7g) for 20-40 % cost reduction.
• •Mix Spot + On-Demand via Capacity-Optimized allocation in ASGs.
• •Enable auto-scaling with target tracking (CPU 60-70 %).
• •Schedule dev/staging instances off-hours with Instance Scheduler.

S3

Implement S3 Intelligent-Tiering when access patterns are unpredictable. Use S3 Lifecycle rules for deterministic transitions (see playbook).

RDS / Aurora

• •Use Aurora Serverless v2 for variable traffic.
• •Enable RDS Reserved Instances for production.
• •Use Aurora I/O-Optimized if I/O costs > 25 % of total DB cost.

Lambda

• •Right-size memory with AWS Lambda Power Tuning.
• •Use Graviton2 (arm64 architecture) for ~34 % cost reduction.
• •Enable Provisioned Concurrency only when cold-start SLA < 100 ms.
• •Prefer Step Functions over chained Lambdas to avoid idle billing.

ECS / EKS

• •Use Fargate Spot for fault-tolerant tasks (up to 70 % savings).
• •Use Compute Savings Plans for steady Fargate workloads.
• •For EKS: enable Karpenter for intelligent node provisioning.
• •Right-size task/pod CPU and memory with Container Insights.

Data Transfer

Tagging Strategy (Mandatory)

Every AWS resource MUST have these tags:

Enforce via AWS Organizations Tag Policies and SCP deny rules.

Cost Evaluation Workflow

When asked to evaluate costs, follow this sequence:

1. •Inventory: List services, instance types, storage volumes, and data flows.
2. •Tag audit: Check for missing cost-allocation tags.
3. •Utilization check: Review CloudWatch metrics (CPU, memory, IOPS, network).
4. •Pricing check: Compare current pricing model vs optimal (RI/SP/Spot).
5. •Architecture review: Identify unnecessary data transfer, missing caching, idle resources.
6. •Report: Produce a table of findings with:
   • •Resource / Service
   • •Current monthly cost (estimated or from Cost Explorer)
   • •Suggested action
   • •Estimated savings (% and $)
   • •Effort (low / medium / high)
   • •Risk (low / medium / high)

Tools

• •AWS Cost Explorer — Spend trends, forecasting, RI/SP recommendations
• •AWS Compute Optimizer — EC2, EBS, Lambda right-sizing
• •AWS Trusted Advisor — Idle resources, under-utilized instances
• •AWS Cost Anomaly Detection — ML-based spend anomaly alerts
• •AWS Budgets — Threshold alerts and auto-actions
• •Kubecost — Kubernetes cost allocation (EKS)

Implementation Details

For Terraform, AWS CLI, and boto3 code examples, see implementation-playbook.md.

Related Skills

• •aws-serverless — Serverless architecture patterns (Lambda, API Gateway, DynamoDB)
• •production-dockerfile — Containerization best practices