What is the best Garbage Collector for low-latency apps?

For latency-critical applications with heaps larger than 4GB, ZGC or Shenandoah are recommended to maintain pause times under 10ms (or <1ms for ZGC).

Which profiler is recommended for production environments?

For CPU profiling in production, async-profiler is highly recommended because it is safepoint-free and has very low overhead (typically ~2% CPU).

Can I use this for general Java syntax questions?

No, this skill is specifically tuned for runtime analysis, profiling, and performance debugging. It is not intended for general-purpose Java coding or syntax help.

How does this skill help with Kubernetes OOMKilled errors?

It provides strategies for container-aware memory management, recommending specific JVM flags like MaxRAMPercentage and helping budget for non-heap memory overhead.

Can this skill help identify unused or dead code?

Yes, it provides a selection matrix for both static analysis (like ProGuard) and runtime analysis (like Scavenger) to find unreachable code based on production data.

JVM Performance & Runtime Analysis

Name: JVM Performance & Runtime Analysis
Author: yzavyas

byyzavyas

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Analytics & Monitoring

Analyzes, optimizes, and debugs JVM applications using production-safe profiling, garbage collection tuning, and dead code detection patterns.

About

This skill provides specialized guidance for deep JVM analysis, moving beyond standard syntax support to focus on performance engineering and production troubleshooting. It offers decision frameworks for selecting profilers like async-profiler and JFR, optimizing garbage collectors such as G1, ZGC, and Shenandoah, and diagnosing complex memory leaks or thread contention. By emphasizing safepoint-free profiling and container-aware memory management, it helps developers build highly efficient, stable Java applications that scale effectively in modern cloud and Kubernetes environments.

Key Features

Decision matrices for Garbage Collector (GC) tuning and selection
Container-aware JVM memory optimization and OOMKilled prevention
3 GitHub stars
Production-safe profiling selection using async-profiler and JFR
Advanced heap and thread dump analysis for root cause identification
Static and runtime dead code detection workflows

Use Cases

Diagnosing intermittent memory leaks and OutOfMemoryErrors in production
Optimizing JVM resource allocation and container sizing for Kubernetes
Reducing application latency and GC pause times for high-traffic microservices

About

Key Features

Decision matrices for Garbage Collector (GC) tuning and selection
Container-aware JVM memory optimization and OOMKilled prevention
3 GitHub stars
Production-safe profiling selection using async-profiler and JFR
Advanced heap and thread dump analysis for root cause identification
Static and runtime dead code detection workflows

Use Cases

Diagnosing intermittent memory leaks and OutOfMemoryErrors in production
Optimizing JVM resource allocation and container sizing for Kubernetes
Reducing application latency and GC pause times for high-traffic microservices