Converts perf and DTrace profiling output to Chrome DevTools .cpuprofile format for performance analysis.
cpuprofilify is a Node.js tool that converts profiling data from system-level profilers like Linux perf and macOS DTrace into the .cpuprofile format used by Chrome DevTools. It solves the problem of analyzing low-level performance traces by making them viewable in a familiar browser-based profiling interface.
Node.js developers and performance engineers who need to analyze application performance using system profiling tools but want to visualize results in Chrome DevTools.
Developers choose cpuprofilify because it provides a standardized way to convert raw profiling data into a format compatible with powerful visualization tools, eliminating the need to learn separate analysis interfaces for different profiling systems.
Converts output of various profiling/sampling tools to the .cpuprofile format so it can be loaded into Chrome DevTools.
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Handles both Linux perf and macOS DTrace outputs, enabling performance analysis across different operating systems as demonstrated in the README with separate command examples.
Configurable options to exclude V8 internals, system calls, and unresolved addresses, improving trace clarity by default, with flags like --nov8gc for fine-tuning.
Provides both CLI tools for quick conversions and a JavaScript API for programmatic integration, catering to different workflows as shown in the API section.
Reads symbol information from perf map files automatically, ensuring accurate stack trace resolution without manual intervention, per the API documentation.
Requires sudo privileges for DTrace on macOS and system-level tool access, adding security and operational hurdles, as seen in the installation instructions.
Involves multiple steps like enabling Node.js with --perf-basic-prof and managing map files, increasing initial configuration time and potential for errors.
Only converts to Chrome DevTools .cpuprofile format, restricting use with other profiling visualization tools or alternative analysis platforms.