Our Spring Boot REST APIs handle thousands of concurrent requests per minute. We are trying to establish what is the ideal JVM heap size for production to handle sudden traffic spikes without experiencing latency degradation. What profiling metrics should we focus on to find this sweet spot?
3 answers
To find the ideal configuration for Spring Boot, you must profile your application's behavior under a simulated peak load using a tool like JMeter or Gatling. Monitor the 'live data size', which is the memory remaining after a full garbage collection event. Your ideal production maximum heap should generally sit between 3x and 4x this specific live data volume. This specific headroom ensures that your system can comfortably process rapid request bursts and temporary object allocations without triggering frequent, performance-killing GC sweeps.
Are you currently tracking your application's heap utilization metrics via Spring Boot Actuator and Prometheus to see your daily memory trends?
Keep an eye on Metaspace as well. Spring Boot applications load many classes dynamically, which consumes native memory entirely separate from your standard heap.
Spot on. Metaspace exhaustion will throw an OOM error just as fast as heap exhaustion, so it must be factored into your overall server memory calculations.
Monitoring those Prometheus metrics over a full week really highlights how much memory your application holds during idle hours versus peak business hours, which is vital data for planning your long-term capacity.