Cloud costs can spiral out of control for fast-growing startups. When one of our SaaS clients came to us spending over $15,000/month on AWS, we knew there was room for optimization.
///The Audit
We started with a comprehensive audit of their AWS infrastructure:
- ▸EC2 instances running at 10-15% average CPU utilization
- ▸RDS databases over-provisioned by 3x
- ▸S3 storage with no lifecycle policies
- ▸Lambda functions with excessive memory allocation
///Optimization Strategy
1. Right-Sizing Compute
We analyzed CloudWatch metrics over 30 days and downsized instances where utilization was consistently low. Moving from m5.xlarge to m5.large saved 50% on compute alone.
2. Reserved Instances and Savings Plans
For predictable workloads, we purchased 1-year reserved instances. Combined with Savings Plans for flexible compute, this reduced on-demand costs by 35%.
3. Serverless Migration
We migrated scheduled jobs and event-driven workflows to AWS Lambda. No idle compute costs — you only pay for what you use.
4. Storage Optimization
Implementing S3 Intelligent-Tiering and lifecycle policies automatically moved infrequently accessed data to cheaper storage classes.
///Results
After three months of optimization:
- ▸45% reduction in monthly cloud spend
- ▸99.95% uptime maintained throughout
- ▸Improved performance due to right-sized resources
The cheapest infrastructure is the infrastructure you do not need. Always measure before you optimize.