Nearly $40K AWS Cloud Cost Reduction in Just 6 Weeks

The organization offers innovative and compliant scalable solutions that help healthcare providers improve cash flow while enhancing patient outcomes and creating lasting peace of mind.

The Problem Statement

Rising AWS costs were straining operational budgets with only a limited portion of infrastructure available for optimization. With critical production workloads and RDS excluded, only $10–$11K of infrastructure could be optimized to achieve the $3K savings target. The challenge demanded aggressive, precise optimization without impacting reliability, performance, or service continuity.

Challenges

Limited Optimization Scope

Only $10–11K of infrastructure was eligible, restricting cost-saving opportunities significantly.

Excluded Critical Services

Production databases and essential workloads were completely outside the optimization scope.

Aggressive Savings Target

Required $3K reduction meant 27–30% optimization from the limited eligible spend.

Tight Delivery Timeline

Expected completion within 6–7 weeks, leaving no margin for experimentation.

Minimal Team Support

Development resources available only for validations, restricting collaborative optimization efforts.

Complex Workload Mix

Diverse services like EC2, ElastiCache, and CloudWatch required tailored cost strategies.

Reliability at Stake

Savings had to be delivered without impacting uptime, performance, or user experience.

Sustainable Governance Need

Required long-term automation to avoid recurring manual cost management overhead.

Solutions

Instance Rightsizing

Analyzed utilization patterns and resized compute resources to align with actual workload needs.

Spot Instance Adoption

Leveraged cost-efficient Spot capacity with intelligent fallback to ensure workload continuity.

Architecture Migration

Shifted workloads from Intel to AMD and ARM instances for significant cost-performance gains.

Workload Scheduling

Automated shutdown of non-production environments during off-hours, reducing unnecessary compute consumption.

Resource Decommissioning

Identified and eliminated unused services, bundles, and infrastructure across multiple AWS environments.

Storage and Image Cleanup

Applied retention policies, compressed container images, and pruned unused snapshots for savings.

Monitoring Optimization

Consolidated metrics, alarms, and dashboards while enforcing log retention policies across environments.

Automation Framework

Built Python-based scripts enabling predictive optimization, anomaly detection, and near-zero manual intervention.

Outcomes

Cost Savings Delivered

Surpassed the $3,000 monthly target, achieving $3,200 and $38,400 annual savings, enhancing financial efficiency and operational sustainability.

Delivery Speed

Completed project in 3 weeks, 57% faster than the planned 6–7 week schedule.

Automation Success

Implemented 95% automation with Python scripts, drastically minimizing recurring manual intervention needs.

Service Continuity

Maintained 100% uptime throughout optimization, ensuring zero disruption to critical business operations.

Optimization Efficiency

Reduced eligible infrastructure costs by 30.9%, outperforming typical industry cost optimization benchmarks.

Future Potential

Identified additional $500 monthly savings opportunities for upcoming optimization and efficiency phases.

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