Spring Boot Performance Tuning Guide (Production Ready)

A Spring Boot app works fast locally…
but slows down under real traffic.

Performance tuning is about identifying bottlenecks and optimizing CPU, memory, database, and threads in Spring Boot applications.

This guide covers practical production optimizations.


📌 Typical Performance Problems

  • High response time

  • High CPU usage

  • Memory spikes

  • Slow database queries

  • Thread starvation


🖼️ Performance Bottlenecks Overview


1️⃣ JVM Memory Tuning

Default JVM settings are not optimized for production.

Recommended JVM options

-Xms2g
-Xmx2g
-XX:+UseG1GC
-XX:MaxGCPauseMillis=200

Why

Prevents frequent garbage collection and memory resizing.


🖼️ GC Behavior


2️⃣ Thread Pool Optimization

Tomcat default threads = 200 (not always correct)

Configure

server.tomcat.threads.max=100
server.tomcat.accept-count=50

Too many threads → context switching overhead.


3️⃣ Database Performance

Most performance issues come from database.

Enable connection pooling

Spring Boot uses HikariCP (good default)

Tune it:

spring.datasource.hikari.maximum-pool-size=20
spring.datasource.hikari.minimum-idle=5
spring.datasource.hikari.idle-timeout=30000

🖼️ DB Connection Pool


4️⃣ Cache Frequently Used Data

Use caching to reduce DB load.

@Cacheable("products")
public Product getProduct(Long id) {
return repository.findById(id);
}

Enable:

@EnableCaching

5️⃣ Async Processing

Avoid blocking APIs.

@Async
public void sendEmail(){
mailService.send();
}

🖼️ Async vs Blocking


6️⃣ Optimize Logging

Logging can slow production.

Set production level:

logging.level.root=INFO

Avoid DEBUG in production.


7️⃣ Reduce JSON Serialization Cost

Use DTOs instead of entities.

Bad:

Returning full entity graph

Good:

Return minimal response object


8️⃣ Enable HTTP Compression

server.compression.enabled=true
server.compression.mime-types=application/json

Reduces network latency.


Monitoring Tools

  • Actuator /metrics

  • Prometheus

  • Grafana

  • JProfiler


Best Practices Checklist

✔ Tune JVM heap
✔ Optimize DB queries
✔ Limit threads
✔ Use caching
✔ Async processing
✔ Monitor continuously


📚 Recommended Reading


🎯 Conclusion

Performance tuning is not one setting.

It’s a combination of:

JVM + DB + Threads + Network + Code

Small optimizations together create big performance gains.


💼 Professional Support Available

If you are facing issues in real projects related to enterprise backend development or workflow automation, I provide paid consulting, production debugging, project support, and focused trainings.

Technologies covered include Java, Spring Boot, PL/SQL, CMS, Azure, and workflow automation (jBPM, Camunda BPM, RHPAM).


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