The Hidden Cost of a Log Line : Sync/Async Flush and everything in Between
log.info("user logged in") looks free. It isn't. Behind that one line is a chain of decisions — buffer or not, flush or not, block or drop, same thread or another — and each one trades latency , throughput , and durability against the others. This post walks the whole chain, from the method call down to the bytes hitting the disk platter. If you've ever wondered why your p99 latency has a mysterious spike, why logs vanish after a crash, or what "async logging" actually buys you, this is for you. First, the map: facade vs. implementation Java logging is a two-layer cake, and mixing up the layers is the #1 source of confusion. The facade is the API your code calls. The implementation is what actually writes the bytes. your code │ log.info(...) ▼ ┌───────────────────────────────┐ │ Facade: SLF4J (or Log4j2 API)│ ← the interface you compile against └──────────────┬────────────────┘ │ bound at runtime ┌───────────┼────────────┬──────────────┐ ▼ ▼ ▼ ▼ Logback Log4j2 Core java.util.logging ... (the engine that buffers, formats, and flushes) SLF4J — the de-facto standard facade. Your app should log against this. Logback — the reference SLF4J implementation. Solid, widely deployed. Log4j2 — the performance-focused implementation, famous for its lock-free async loggers. java.util.logging (JUL) — built into the JDK, rarely chosen on purpose. Why the split? So you can swap engines without touching a single log. call. Everything interesting in this post — the buffering, the flushing, the async magic — happens in the implementation layer. The anatomy of a single log call Before we talk flushing, let's see what one log.info(...) actually does. There are five stages: 1. Level check → is INFO enabled for this logger? (cheap, often the fastest bail-out) 2. Build LogEvent → capture message, timestamp, thread, MDC context, maybe a stack trace 3. Filter → run any configured filters 4. Layout / encode → turn the event into bytes ("2026-07-28 12:00:01 INFO ...") 5. Append → write those by