AWS Cost Optimization

Overview

Tasked with reducing a growing AWS infrastructure bill without compromising performance or reliability, this project delivered a 46% cost reduction through systematic analysis, automation, and ongoing governance.

The Problem

Infrastructure costs had grown significantly over several years of rapid scaling. The team lacked visibility into waste — idle resources, over-provisioned instances, and unattached storage were accumulating costs silently. There was no automated process for identifying or acting on optimization opportunities.

The Solution

I built a Python/Boto3 automation suite covering EC2 right-sizing recommendations from Cost Explorer, EBS volume lifecycle policies for snapshot cleanup and orphan removal, S3 intelligent tiering and lifecycle rules, Route53 health-check-driven traffic optimization, Lambda scheduling for non-production environment shutdowns, and a CloudWatch reporting dashboard with executive-ready cost breakdowns.

The Results

Total infrastructure spend dropped by 46% over 3 months. Performance benchmarks remained stable or improved post-optimization. The automation suite now runs continuously, generating weekly cost reports and alerting on budget anomalies. Zero manual intervention required for routine optimization.

Key Takeaways

• →Cost optimization is most effective when paired with continuous automation — one-time analyses degrade quickly
• →Right-sizing EC2 instances is the single highest-impact lever, but lifecycle policies compound gains over time
• →Executive reporting cadence accelerates buy-in and makes cost governance a shared responsibility
• →Never optimize in isolation — validate performance benchmarks before and after every significant change

Tools & Technologies