How One Spring Boot Optimization Saved Our Startup $30,000 a Year

Author(s): FutureLens Originally published on Towards AI. How One Spring Boot Optimization Saved Our Startup $30,000 a Year Our AWS bill was $7,400 last month. The month before, $6,900. The month before that, $6,200. The line was going in one direction. Our runway wasn’t. “Image created by ChatGPT”After observing steadily rising AWS costs without user growth, the author traces the issue to Spring Boot defaults and production inefficiencies: tuning HikariCP connection pooling to reduce CPU, then uncovering a costly session-validation query repeatedly executed on every authenticated request and eliminating it with Redis caching. They further cut serialization overhead by caching the products endpoint response, add missing PostgreSQL composite indexes to prevent expensive sequential scans, and finally rightsizes ECS Fargate tasks based on real utilization; overall CPU drops sharply, database load decreases, and monthly cloud spend falls from roughly $7,400 to about $3,130—saving an estimated $30,000–$35,000 annually. Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI