List of AWS Fixes

🔧 Easy Fixes (Automated, No Downtime)

These optimizations are straightforward to implement and carry minimal risk:

• Eliminate Idle Resources: Identify and remove unused EBS volumes, AMIs, Elastic IPs, and ELBs to cut unnecessary costs.
• Right-Size EC2 Instances: Utilize AWS Compute Optimizer to adjust instance sizes or migrate to Graviton processors for better performance at lower costs.
• Implement Intelligent Storage Tiering: Enable S3 Intelligent-Tiering and switch EBS volumes to gp3 to optimize storage expenses based on access patterns.
• Schedule Non-Production Environments: Automatically shut down development, testing, and staging instances during off-hours to save up to 65% on non-critical workloads.
• Optimize Database Costs: Adjust configurations for DynamoDB and RDS, such as enabling infrequent access modes or using Single-AZ deployments for non-critical databases.
• Clean Up ML Resources: Remove idle SageMaker endpoints, models, and notebooks to prevent unnecessary charges.
• Leverage Reserved Instances & Savings Plans: Apply appropriate discount programs for services like RDS, EC2, and EMR to achieve significant savings over on-demand pricing.
• Fine-Tune Compute Efficiency: Optimize Lambda memory allocations and right-size EC2 GPU usage to maximize performance-to-cost ratios.
• Optimize Data Transfer: Implement S3 and DynamoDB gateway endpoints to reduce data transfer fees and enhance security.

⚙️ Medium Fixes (Resource Rationalization)

These optimizations require a moderate level of intervention and may involve some manual oversight:

• Modernize EC2 Instances: Transition from Intel-based instances to the latest AMD processors, offering a 20–30% improvement in price/performance.
• Adjust RDS Configurations: Enable auto-scaling and optimize storage settings to reduce costs without compromising performance.

🧠 Advanced Fixes (Strategic Overhaul)

These are more complex optimizations that may involve significant changes and potential downtime:

• Delete Idle SageMaker Models: Manually identify and remove unused SageMaker models to eliminate unnecessary expenses.
• Implement Best Practices for Long-Term Management: Enhance telemetry and monitoring capabilities to establish a foundation for ongoing optimizations.

🔄 Continuous Optimization Process

SmartCloud AWS Fixer operates on a continuous cycle of identifying and implementing optimizations:

• Find: SmartCloud AWS Fixer's AI-powered scanning engine analyzes your AWS environment to identify cost-saving opportunities.
• Fix: Utilizing AWS Systems Manager Automation Runbooks, SmartCloud AWS Fixer applies the identified optimizations securely and efficiently.
• Save: By continuously applying these optimizations, SmartCloud AWS Fixer helps achieve 15–60% savings per AWS service.