30 open-source projects similar to jvm-profiling-tools/async-profiler, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Async Profiler alternative.
FlameGraph is a performance profiling and visualization toolkit designed to identify bottlenecks in software execution. It functions as a processing engine that transforms raw stack trace samples into interactive, hierarchical diagrams. By representing aggregated execution frequency as nested rectangles, the tool allows developers to visualize hot code paths and analyze system behavior across both kernel and user-space environments. The project distinguishes itself through its ability to perform differential profile analysis, which highlights performance regressions or improvements by compari
Arthas is a Java diagnostic tool and runtime debugger designed for real-time troubleshooting of applications. It functions as a remote diagnostics agent that allows users to inspect the runtime state of a Java process, including its heap objects and classloader hierarchies, without requiring a process restart. The project distinguishes itself through advanced bytecode manipulation capabilities, enabling live class hotswapping and the modification of bytecode in running processes. It supports in-memory source compilation and runtime bytecode decompilation to verify and update logic instantly w
This project is a comprehensive technical guide and diagnostic manual for analyzing memory, performance, and asynchronous behavior within Node.js applications. It provides detailed methods for asynchronous tracing, memory diagnostics, and performance analysis to resolve runtime errors and execution bottlenecks. The resource distinguishes itself by covering advanced diagnostic workflows, including the use of flame graphs for CPU profiling, the capture and comparison of heap snapshots for memory leak detection, and the mapping of asynchronous call stacks. It also provides technical guidance on
PerfView is a set of integrated profiling and tracing tools built on Windows Event Tracing for Windows (ETW), designed to diagnose CPU, memory, and ETW-based performance issues in .NET applications. It captures ETW events to analyze runtime behavior, CPU usage, and memory allocations, serving as a .NET performance profiler that measures both CPU time and garbage collection events. The tool distinguishes itself with a diff comparison engine that compares two performance traces side-by-side to highlight changes in method costs and event rates. It renders profiled call stacks as flame graphs whe
This project is a technical reference and a collection of internal analysis notes focused on the Go language runtime and compiler. It provides a detailed breakdown of the language internals, covering memory management, garbage collection, and the execution model of the scheduler. The material distinguishes itself by providing deep dives into low-level system details, including a reference for Go assembly instructions, register usage, and system call interfacing. It specifically analyzes the internal implementation of concurrency primitives, such as the goroutine scheduling mechanism, channel
go-torch is a profiling tool for capturing the execution state of Go programs and transforming raw binary data into visual representations of program performance. It functions as a flame graph profiler and performance visualization utility that identifies expensive code paths through the collection of CPU and memory stack traces. The tool features a network-capable remote process profiler that connects to endpoints to capture and export execution profiles from Go binaries. It utilizes stochastic profiling to synthesize execution data into call graphs, allowing for the identification of bottle
OSV is a unikernel operating system and cloud-native execution environment designed to run as a secure microVM on hypervisors such as KVM, Firecracker, Xen, and VMware. It functions as a Linux binary compatible runtime, allowing unmodified Linux binaries to be executed as secure microVMs without requiring recompilation. The project distinguishes itself through its ability to package applications into minimal bootable images and its provide of a virtual machine management API. This REST interface enables remote monitoring of system health, management of execution traces, and control over guest
Memray is a memory profiler for Python that tracks heap allocations in both Python code and native C or C++ extensions. It captures memory events by hooking into the language runtime and traversing call stacks, providing a comprehensive view of how an application consumes memory. The tool is designed to minimize performance impact on the target application by using thread-local buffering and streaming data to an external process or file. The project distinguishes itself through its ability to monitor complex, multi-threaded systems and child processes in real-time. It provides diagnostic util
Async-profiler is a sampling profiler for Java applications that tracks CPU time and stack traces across execution frames to identify performance bottlenecks. It is designed to capture profiling data without introducing timing bias. The project provides capabilities for JVM memory analysis to locate native and heap allocation hotspots and memory leaks. It also includes system contention analysis to identify resource bottlenecks through the tracking of contended locks and hardware performance counters. The tool converts raw profiling data into visual performance reports, including interactive
gperftools is a collection of specialized tools for profiling CPU usage, detecting memory errors, and providing high-performance memory allocation. It provides a memory profiling toolkit for C++ applications, including a sampling CPU profiler and a heap profiler for analyzing consumption patterns. The project includes a high-performance memory allocator designed as a multi-threaded replacement for standard allocation to reduce contention and improve execution speed. It further provides a memory debugger to identify illegal memory access and double frees. The toolkit covers broad diagnostic c
Bistoury is a production diagnostics tool for Java applications that provides a distributed debugging console, a performance profiler, and a runtime bytecode manipulator. It enables real-time application debugging and production diagnostics by analyzing running Java applications through dynamic instrumentation and state inspection. The system distinguishes itself through a remote agent manager that coordinates diagnostic connections and a runtime bytecode manipulator capable of redefining classes in memory without requiring process restarts. It features a web interface for capturing heap dump
Scalene is a high-performance diagnostic utility designed to measure resource consumption during the execution of Python applications. It functions as a line-level monitor, providing granular insights that pinpoint the specific source code responsible for performance overhead. The tool distinguishes itself through statistical profiling that captures stack traces and resource usage without requiring manual instrumentation of the source code. It tracks CPU, GPU, and memory consumption by intercepting library-level calls and hardware driver commands, allowing for the analysis of both managed and
BCC is an eBPF development toolkit and tracing framework used for monitoring and analyzing the Linux kernel. It functions as a performance analysis tool and debugging utility to capture system events, measure kernel latency, and provide network observability. The project distinguishes itself by providing a build system that integrates with LLVM to compile C-like code into BPF bytecode at runtime. It utilizes BPF Type Format data for relocations to maintain cross-kernel compatibility and extracts kernel headers to ensure the generated programs match the specific kernel version. The toolkit co
Node-clinic is a performance profiling suite for Node.js designed to diagnose CPU bottlenecks, memory leaks, and asynchronous event loop issues. It provides specialized diagnostic tools for visualizing asynchronous flows, generating CPU flame graphs, and analyzing heap memory allocation. The suite includes a CPU flame graph tool to identify functions consuming the most processing time, a heap memory analyzer to track object allocation and leaks, and an asynchronous I/O profiler to map operation flows and find event loop bottlenecks. These tools cover broader capabilities in CPU execution pro
Samply is a cross-platform CPU sampling profiler and performance analysis utility. It consists of a command-line tool for recording process stack traces at regular intervals and a visual interface for analyzing the resulting execution data. The system includes a debug symbol resolver that maps raw memory addresses to human-readable function names using local or remote symbol information. It transforms recorded execution data into flame graphs and timelines to pinpoint function-level hotspots. The tool provides capabilities for CPU execution recording, stack unwinding, and symbol resolution a
Moon is a monorepo build system and task runner designed to orchestrate complex projects with multiple packages. It functions as a dependency graph orchestrator that executes build targets in topological order and utilizes input hashing to cache results and skip redundant work. The project features a polyglot toolchain manager that automates the installation and versioning of language runtimes and CLI tools to ensure environment consistency. It also includes a plugin framework based on WebAssembly, allowing developers to extend build logic and toolchain behavior using any supported language.
The Intel Processor Performance Monitor is a set of specialized diagnostic tools designed for monitoring raw hardware events, memory latency, PCIe throughput, and processor power states on Intel architecture. The project provides dedicated utilities for measuring data throughput across sockets and PCIe buses, tracking power usage and sleep states to identify frequency throttling, and analyzing cache misses and memory access times. It also includes a hardware event profiler for querying raw core and uncore register events to monitor specific processor behaviors. Capabilities cover comprehensi
Parca is an always-on continuous profiling platform that captures CPU and memory usage from running applications without any code modifications. It uses eBPF kernel-level tracing to automatically discover and sample stack traces across infrastructure, and provides a web-based flame graph dashboard for interactive performance analysis. Its label-based query engine lets users slice and aggregate profiling data across dimensions such as service, container, or region, using a Prometheus-style selector syntax. Unlike basic profilers, Parca stores profile samples in a columnar format using Apache A
BenchmarkDotNet is a library and tool suite for measuring the execution time and memory allocation of .NET code. It utilizes statistical sampling and warm-up iterations to determine the stability and precise execution speed of specific methods. The project provides a JIT disassembly viewer to inspect processor disassembly and analyze how the compiler executes code paths. It includes a memory allocation profiler that tracks managed and native memory traffic to identify efficiency bottlenecks. Additionally, a runtime performance comparator allows the same benchmarks to be executed across differ
The Android NDK samples provide a comprehensive collection of code examples demonstrating how to integrate C and C++ native code into Android applications. This repository serves as a practical guide for developers utilizing the Android Native Development Kit to implement performance-critical application components that require direct hardware access and low-level system interaction. The project highlights the use of the Java Native Interface to bridge managed code with native modules, enabling cross-language function calls and efficient data exchange. It demonstrates how to manage native act
Hotspot is a graphical user interface for analyzing and visualizing performance data captured by the Linux perf tool. It functions as a performance profiling visualizer and assembly-level profiler that maps performance costs to specific instructions synchronized with original source code. The project distinguishes itself through a remote symbol resolver that maps performance data from embedded targets to local host debug symbols and sysroots. It also includes a specialized off-CPU analysis tool designed to identify thread wait times and I/O blocks using kernel scheduler tracepoints. The tool
Perfetto is a platform for system-level performance tracing and analysis on Linux and Android. It combines a high-throughput trace recorder, a SQL-based query engine, and a browser-based visualizer into a single toolchain. The platform covers CPU scheduling and call-stack profiling, native and Java heap memory allocation tracking, GPU and graphics events, and system-wide counters such as CPU frequency and power consumption. The architecture decouples trace recording from offline analysis, using a compact protobuf format for event encoding and columnar storage for efficient SQL queries. The we
vprof is a visual profiling tool for Python designed to identify execution bottlenecks and monitor memory consumption. It functions as a CPU and memory profiler that transforms performance data into interactive visualizations to analyze processor time and call stacks. The project distinguishes itself through a suite of visual diagnostics, including flame graphs for stack visualization and heatmaps that map execution frequency and duration directly onto source code. It also includes a remote performance monitor capable of capturing function-specific metrics from a running server and streaming
Fastfetch is a high-performance system information tool written in C designed to profile machine state and display hardware summaries with minimal resource overhead. It functions as a command line utility that retrieves hardware and software specifications and renders them as a visual summary in a terminal emulator. The project enables custom terminal branding through the rendering of ASCII art or image files as visual headers. It utilizes configuration files and format strings to control the visibility and detail of the displayed data, allowing for personalized system fetch layouts. The too
pyinstrument is a statistical sampling profiler for Python that records the call stack at regular intervals to identify performance bottlenecks with low overhead. It tracks wall-clock time, including I/O and external service calls, and provides specialized profiling for asynchronous programs by attributing time spent awaiting tasks to the calling function. The project converts captured execution data into interactive HTML reports, JSON, and flamecharts. It includes a call stack visualizer to simplify the analysis of execution paths and supports the profiling of individual cells within interac
Memory Profiler is a diagnostic library for Ruby applications designed to monitor runtime memory consumption and object lifecycles. It provides tools to track object allocations and memory usage, enabling the identification of performance bottlenecks and potential memory leaks that affect software stability. The tool functions by observing memory behavior during program execution, allowing developers to distinguish between short-lived data and objects that persist beyond their intended lifecycle. It captures the execution context of allocations by walking the call stack, which helps attribute
Matrix is a suite of mobile application performance management and analysis tools. It provides a plugin-based monitoring system for capturing crashes, lags, and memory leaks, alongside a static binary auditor for reducing installation package size and a bytecode instrumentation tool for performance tracking. The project distinguishes itself through native memory debugging and a SQLite query linter that identifies inefficient database patterns. It employs native interception techniques to detect memory leaks and heap corruption without requiring source code recompilation, and uses a custom run
Heaptrack is a heap memory profiler and diagnostic tool for applications running on Linux. It functions as a memory leak detector and performance analysis system that records heap allocations and stack traces to identify memory hotspots and consumption patterns. The project provides a graphical heap allocation visualizer for exploring memory usage through tree views and peak memory reports. It utilizes flame graphs and allocation charts to visualize memory hotspots and assist in the detection of leaks. The toolset includes capabilities for heap memory allocation tracing and the generation of
Xposed is a native Android runtime hooking framework and instrumentation tool. It provides a modified version of the Android app process binary to intercept and modify the behavior of system and application processes at the binary level. The framework enables Android operating system customization by altering internal function calls and runtime execution flow. It achieves this through native process instrumentation, allowing for the modification of functionality without altering original application files. The tool covers several low-level capabilities, including native library injection and
Goja is a JavaScript engine and ECMAScript compliant interpreter implemented entirely in Go. It serves as an embedded scripting engine that allows Go applications to execute JavaScript code and integrate a programmable scripting layer without relying on Cgo or external native dependencies. The project functions as a bridge between Go and JavaScript, enabling bidirectional data exchange and function invocation. It allows Go hosts to expose native structs, slices, and maps as JavaScript objects and arrays, while providing mechanisms to export script values and functions back into native Go type