A command-line Swiss Army knife for JVM diagnostics, troubleshooting, and profiling using JMX, JVM attach, and perf counters.
SJK (Swiss Java Knife) is a command-line tool and library for JVM diagnostics, troubleshooting, and profiling. It solves problems related to monitoring Java application performance, analyzing memory usage, and profiling thread activity by leveraging standard JVM interfaces like JMX and JVM attach. It provides a unified set of utilities to replace or enhance scattered diagnostic commands.
Java developers, DevOps engineers, and performance analysts who need to diagnose production JVM issues, profile application performance, or build custom monitoring tools.
Developers choose SJK for its comprehensive feature set that goes beyond basic JDK tools, its ability to work without enabling JMX servers, and its extensibility as a library for embedding diagnostics into applications.
Small set of tools for JVM troublshooting, monitoring and profiling.
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Tracks thread CPU usage, memory allocation rates, and safe point time, providing insights beyond basic jstack outputs from JDK tools.
Offers class histograms with dead object detection and top bucket filtering, aiding in memory leak identification as highlighted in the HH command documentation.
Enables reading, updating, and invoking MBeans from the terminal with wildcard support and PID connectivity without requiring JMX servers to be enabled.
Generates hyper-dense stack trace dumps with high compression and flame graphs, allowing detailed performance analysis with minimal storage overhead.
Lacks a graphical user interface, making it less accessible for users who prefer visual tools like VisualVM or Java Mission Control for interactive diagnostics.
Requires a JVM to execute, which adds overhead and can be a barrier in environments where Java is not installed or where lightweight, native tools are preferred.
Documentation is split across multiple Markdown files (e.g., COMMANDS.md and individual command docs), potentially making it harder to navigate and learn compared to a unified guide.