Infrastructure Cost Optimization
Analyzed and optimized cloud infrastructure spending for an e-commerce company, implementing right-sizing, reserved instances, and automated scheduling to achieve $200K+ annual savings.
💸 The Problem: Runaway Cloud Costs
An e-commerce company was experiencing rapidly growing AWS bills — increasing 40% year-over-year — with no visibility into what was driving the spend. Teams were over-provisioning "just in case" and nobody owned cost optimization.
🔍 Cost Analysis Approach
I conducted a comprehensive cost analysis using AWS Cost Explorer, billing data exports, and custom Python scripts to identify optimization opportunities:
⚙️ Optimization Strategies Implemented
- Analyzed CloudWatch metrics for CPU, memory, network
- Identified 60% of instances running at <20% utilization
- Downsized from m5.2xlarge to m5.large where applicable
- Moved memory-light workloads to T3 burstable
- Analyzed 12-month usage patterns
- Purchased 1-year partial upfront RIs for stable workloads
- Used Savings Plans for flexible compute
- Achieved 70% coverage on EC2 spend
- Built Lambda functions to stop dev/staging at night
- Weekend shutdowns for non-production
- Tag-based opt-in/opt-out mechanism
- Slack notifications before shutdown
- Deleted 2TB of orphaned EBS volumes
- Removed unused Elastic IPs ($3.65/month each)
- Cleaned up old snapshots (>90 days)
- Terminated zombie resources
🤖 Cost Automation Architecture
To maintain savings long-term, I built automated cost governance:
Lambda functions triggered by CloudWatch Events to start/stop tagged resources on schedule.
AWS Cost Anomaly Detection with Slack alerts for unexpected spend spikes.
Automated cost breakdown emails to stakeholders every Monday.
AWS Config rules enforce mandatory tags; non-compliant resources flagged.
📊 Cost Visibility Dashboard
Built a centralized cost visibility solution enabling teams to understand and own their spend:
🏆 Results Achieved
Without impacting performance or availability
Every dollar attributed to a team/application
Automation prevents cost creep
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