This article provides architectural patterns and best practices for cost-optimizing AWS workloads through compute optimization and strategic service selection.

• Cost optimization is continuous; requires identifying right tools and efficient designs
• AWS Budgets and Cost Anomaly Detection help govern cloud usage and prevent surprises
• Compute Optimizer, EC2 Spot Instances, Savings Plans optimize infrastructure costs
• Graviton processors deliver better price-performance for cloud workloads
• Lambda optimization covers performance-cost tradeoffs and idle time elimination
• ECS/Fargate: use spot instances and right-sized instance types for savings
• Karpenter auto-scales Kubernetes clusters with spot and Graviton instances
• AWS Well-Architected Labs provide hands-on cost optimization training

Cost optimization requires selecting appropriate hardware, leveraging pricing models like Savings Plans, and using AWS tools to continuously monitor and reduce expenses.