[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_28":-5,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_47":48,"_49":50,"_51":52,"_53":54,"_55":56,"_57":58},"routes/_store+/_readers+/email_author.$slug/route",{"_9":10,"_11":-5},"book",{"_12":13,"_14":15,"_16":17,"_18":19,"_20":21,"_22":23},"currentUser","id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNzgxNjY","title","Spring Boot 4 Performance in Practice","state","published","contactAuthorMethod","email","aboutText","

Most performance books teach you what the knobs do. This one teaches you which knobs to turn, and proves it with numbers.

I take CinéTrack, a real Spring Boot 4 monolith, and push it from its baseline throughput to fifty times that over twenty-eight chapters. Every chapter starts with a profiler, finds an actual bottleneck, applies a single change, and measures the result side by side. Some changes buy 30%. Some buy 3%. Some buy nothing. I say so.

You will learn the measurement discipline that separates engineers who tune from engineers who guess: how to read a flame graph, how to interpret p99 latency, how to tell a GC problem from a thread-pool problem from a query problem before you touch a line of code.

Then you will learn the tuning stack: virtual threads, ZGC, Hibernate batch loading, connection pool sizing, Redis caching, Kafka back-pressure, GraalVM native image. Not as a menu of options but as a sequence of decisions, each grounded in what the profiler actually showed.

For engineers who have built something with Spring Boot and now have to make it fast.

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Kick off your book project, get started with GhostAI, get better at marketing, or spend the day doing all three! Free live workshops on Zoom. Saturday, June 27, 2026.

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