Understanding JIT Compilation and Its Impact on Application Startup Performance

When a Java application starts, the first few requests can be noticeably slow because the JVM initially executes bytecode using an interpreter, which translates and runs code line‑by‑line, resulting in high response times and resource consumption.

The interpreter’s low efficiency led HotSpot to introduce Just‑In‑Time (JIT) compilation: the JVM monitors method execution frequencies, identifies "hot spots," and compiles those sections into optimized native machine code, caching the result for future calls.

Since JIT optimization only occurs after a method has been executed enough times to be considered hot, all requests before this point go through the slower interpreter path, causing higher CPU usage, load, and occasional time‑outs, especially under heavy traffic.

To mitigate the startup latency, two main approaches are recommended:

Improve JIT optimization efficiency, for example by using Alibaba’s Dragonwell JDK, which includes the JwarmUp feature that records previous compilation data and pre‑compiles classes on the next startup, bypassing the interpreter phase.

Reduce instantaneous request volume by gradually ramping up traffic (pre‑warming). By directing a small amount of traffic to the newly started instance, JIT can compile hot code before the full load arrives, smoothing performance.

In summary, the initial slowness is caused by interpreter execution before JIT has had a chance to compile hot code; employing JIT warm‑up techniques or traffic pre‑warming can significantly reduce this startup overhead.