15 SpringBoot Performance Tweaks to Handle Million-Scale Concurrency

This guide walks through exposing metrics, integrating Prometheus and Grafana, using async‑profiler flame graphs, tuning Tomcat/Undertow, optimizing JVM flags, applying SkyWalking tracing, and applying layer‑wise code, cache, and thread‑pool improvements so a SpringBoot service can reliably serve millions of concurrent requests.

GrafanaNginxPrometheus

0 likes · 20 min read

15 SpringBoot Performance Tweaks to Handle Million-Scale Concurrency

AsiaInfo Technology: New Tech Exploration

Nov 22, 2024 · Operations

How Inferred Spans Boost Distributed Tracing Accuracy and Coverage

The article examines the implementation of inferred spans as an advanced observability technique that enriches traditional distributed tracing by automatically generating additional spans, improving coverage, pinpointing latency sources, and offering performance‑optimisation insights while discussing practical integration, algorithmic details, and associated trade‑offs.

Distributed TracingJavaasync-profiler

0 likes · 9 min read

How Inferred Spans Boost Distributed Tracing Accuracy and Coverage

JD Retail Technology

Mar 18, 2024 · Operations

Diagnosing Full GC and High CPU Issues in Java Services with Arthas, async‑profiler, VisualVM and GCEasy

This article demonstrates how to quickly locate and resolve frequent full GC and CPU spikes in Java backend services by combining Arthas‑integrated async‑profiler flame graphs with VisualVM, GCEasy analysis, and practical step‑by‑step deployment procedures.

ArthasCPU profilingJava

0 likes · 7 min read

Diagnosing Full GC and High CPU Issues in Java Services with Arthas, async‑profiler, VisualVM and GCEasy

SQB Blog

Jun 16, 2023 · Operations

Boost Java Performance: Optimize JFR Analysis with Flame Graphs and Async‑Profiler

This article explores the evolution of continuous performance profiling, explains why traditional tracing falls short, and details a series of optimizations—including batch processing, object‑reference serialization, aggregation insertion, and multi‑chunk handling—to dramatically reduce memory usage and speed up Java Flight Recorder analysis using async‑profiler and flame graphs.

JFRJavaObservability

0 likes · 13 min read

Boost Java Performance: Optimize JFR Analysis with Flame Graphs and Async‑Profiler

FunTester

Dec 14, 2022 · Backend Development

Using async-profiler to Optimize CPU Usage in a Dynamic QPS Test Case

The article details how the author used async-profiler to analyze a Java dynamic QPS test case, identified a CPU hotspot in a time‑checking method, replaced it with a timestamp check, and achieved a modest 0.1% reduction in overall CPU usage, illustrated with flame‑graph images and code snippets.

CPU profilingJava performanceasync-profiler

0 likes · 12 min read

Using async-profiler to Optimize CPU Usage in a Dynamic QPS Test Case