Software Development

How do you configure a Spring Boot API to prevent crashes under extreme traffic load?

BR Asked by Brenda Foster · 12-04-2025
0 upvotes 14,604 views 0 comments
The question

Our enterprise app is facing heavy latency spikes during flash sales. We use , but the default embedded Tomcat configurations are failing to scale. What are the best thread pool tuning metrics and JVM garbage collection flags we can use to handle over 50,000 concurrent requests safely?

3 answers

0
PO
Answered on 14-04-2025

To keep your system stable, focus heavily on database connection pool configuration and embedded server scaling. By default, Tomcat limits maximum worker threads, which leads to starvation under high concurrent loads. Update your configuration to increase max threads while tuning your HikariCP pool size. Don't leave your database connections at default levels; calculate your maximum pool capacity based on your core CPU count. Additionally, apply response compression to save network bandwidth and dramatically reduce JSON payload serialization overhead across your microservices network.

0
AU
Answered on 18-04-2025

Have you looked closely at your database query performance during these specific flash sales? In many cases, thread starvation happens because threads are stuck waiting for a connection from the pool due to unindexed database columns or unoptimized SQL joins rather than Tomcat itself.

BR 19-04-2025

Austin, you hit the nail on the head. We analyzed our slow query logs and discovered that a single unindexed foreign key lookup was keeping database connections open for over two seconds. This caused a massive pile-up in our HikariCP pool, which rapidly starved our Tomcat worker threads and brought down the entire REST application layout under traffic.

0
HE
Answered on 22-04-2025

Try implementing Spring Boot 3 virtual threads if you run on JDK 21. It replaces standard thread-per-request blocking behavior, allowing millions of concurrent tasks to execute smoothly.

ME 25-04-2025

Completely agree with Heather on this one. Switching to virtual threads via basic configuration attributes dropped our microservice resource usage by almost sixty percent during heavy load. It completely changes how backend engineering handles blocking IO operations.

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