Grafana Pyroscope
Fastest to get started
Why teams pick it
One‑click deployment via Docker or Homebrew
Open-source alternatives to Parca
Compare community-driven replacements for Parca in continuous profiling workflows. We curate active, self-hostable options with transparent licensing so you can evaluate the right fit quickly.
Parca
Parca provides continuous profiling using eBPF to track CPU, memory, and I/O performance. It helps developers identify bottlenecks and optimize code paths in production.Read more
Key stats
- 15Alternatives
- 11Active development
Recent commits in the last 6 months
- 9Permissive licenses
MIT, Apache, and similar licenses
Counts reflect projects currently indexed as alternatives to Parca.
Start with these picks
These projects match the most common migration paths for teams replacing Parca.
Likwid
AI-powered workflows
Why teams pick it
Automate scheduling with AI-driven assistants.
All open-source alternatives
Grafana Pyroscope
Intuitive, queryless UI for continuous application profiling
Active developmentFast to deployIntegration-friendlyGo
Why teams choose it
- Queryless Explore Profiles UI for instant visualization
- Broad language support including Go, Java, Python, Ruby, Node.js, .NET, Rust, eBPF
- Push SDKs and pull via Grafana Alloy for flexible data collection
Watch for
Requires running a dedicated Pyroscope server
Migration highlight
Proactive CPU usage reduction
Identify hot functions during load testing and refactor code to lower CPU consumption by up to 30%.
Likwid
Comprehensive CLI suite for low‑level CPU/GPU performance analysis
Active developmentIntegration-friendlyAI-powered workflowsC
Why teams choose it
- Unified interface for CPU topology, counters, and power across multiple architectures
- Thread pinning and MPI wrapper simplify hybrid parallel launches
- Micro‑benchmarking and memory sweep tools for cache behavior analysis
Watch for
Limited to Linux; no Windows or macOS support
Migration highlight
Thread placement optimization for OpenMP code
Pinning threads with likwid-pin reduces contention and improves scaling on multi‑socket systems.
Parca
Continuous eBPF profiling for cost-effective performance insights
Active developmentPermissive licenseIntegration-friendlyTypeScript
Why teams choose it
- eBPF‑based auto‑discovery for Kubernetes and systemd targets
- Standard pprof output and ingestion for broad language support
- Label‑driven storage with efficient slicing and aggregation
Watch for
Requires Linux kernel with eBPF support
Migration highlight
Identify CPU hot paths in a Kubernetes service
Pinpoint functions consuming the majority of CPU, enabling targeted optimizations that reduce resource usage.
Tracy Profiler
Nanosecond-resolution, real-time telemetry profiler for games and apps
Active developmentIntegration-friendlyAI-powered workflowsC++
Why teams choose it
- Nanosecond‑level timing with hybrid frame and sampling modes
- Comprehensive CPU and GPU support across major graphics APIs
- Multi‑language instrumentation (C, C++, Lua, Python, Fortran, etc.)
Watch for
Instrumentation adds some runtime overhead, noticeable in tight loops
Migration highlight
Frame‑by‑frame performance debugging in a game engine
Identify spikes per frame, correlate with GPU API calls, and reduce latency.
VizTracer
Low-overhead Python tracer with interactive Perfetto visualizations
Active developmentPermissive licenseFast to deployPython
Why teams choose it
- Detailed timeline with source code and function arguments
- Zero‑code‑change usage via CLI or context manager
- Supports threading, multiprocessing, async, and PyTorch profiling
Watch for
Overhead can increase for highly recursive functions
Migration highlight
Debugging a Flask web service
Identify slow request handlers and middleware latency
Speedracer
Run, trace, and report JavaScript performance with Chrome
Permissive licenseIntegration-friendlyAI-powered workflowsJavaScript
Why teams choose it
- Headless Chrome execution via DevTools protocol
- Automatic generation of compressed trace files and JSON reports
- Simple race definition using ES6/CommonJS modules
Watch for
Unmaintained; no active updates or support
Migration highlight
CI regression benchmark
Detect performance regressions between builds by comparing generated reports.
fgprof
Unified wall‑clock profiler for Go applications with mixed I/O and CPU
Permissive licenseIntegration-friendlyAI-powered workflowsGo
Why teams choose it
- Samples all goroutine stacks, capturing both CPU and I/O wait time
- Exports to standard pprof format and folded stacks for FlameGraph
- Runs alongside Go's built‑in profilers via a simple HTTP handler
Watch for
Overhead grows with the number of active goroutines, noticeable > 10 k
Migration highlight
Identify hidden I/O latency in a web service
Shows that a slow network request dominates wall‑clock time, guiding developers to add caching or retry logic
py-spy
Zero‑overhead sampling profiler for live Python applications
Active developmentPermissive licenseFast to deployRust
Why teams choose it
- No code instrumentation; attaches to running processes
- Extremely low overhead thanks to Rust and out‑of‑process sampling
- Generates flame graphs, speedscope files, live top view, and stack dumps
Watch for
Root or sudo may be required to attach to existing processes
Migration highlight
Generate flame graph for a production web service
Visualize hot paths without restarting, identify bottlenecks, and reduce latency.
Why teams choose it
- ETW and EventPipe trace collection and parsing
- Built-in UI for CPU and memory bottleneck investigation
- Integrated TraceEvent library for programmatic trace manipulation
Watch for
Primary UI runs only on Windows
Migration highlight
Identify GC‑induced latency spikes
Pinpoint garbage collection pauses and optimize memory allocation patterns.
System Informer
Powerful Windows tool for monitoring, debugging, and malware detection
Active developmentPermissive licenseFast to deployC
Why teams choose it
- Real-time graphs and statistics for pinpointing resource hogs
- File lock viewer to identify processes preventing file operations
- Network connection inspector with one-click termination
Watch for
Windows‑only; no macOS/Linux support
Migration highlight
Identify runaway processes draining CPU
Graphical CPU usage view quickly reveals offending processes, allowing termination to restore system responsiveness.
Perforator
Zero‑impact continuous CPU profiling for large‑scale Linux services
Active developmentAI-powered workflowsC++
Why teams choose it
- eBPF‑based kernel and userspace stack collection without frame pointers
- Scalable storage of profiles and binaries with a built‑in query language
- Interactive flamegraph UI supporting C++, Go, Rust (Java/Python experimental)
Watch for
Limited to x86_64 Linux platforms
Migration highlight
Identify CPU hotspots in a microservice fleet
Developers pinpoint hot functions via flamegraphs, reduce latency, and lower cloud costs.
Why teams choose it
- Zero‑config activation via environment variable or web UI
- 22 built‑in metrics covering time, memory, I/O, and objects
- Interactive UI with timeline, flat profile, and flamegraph
Watch for
Experimental status; API may change
Migration highlight
Profiling a Composer update
Identify functions consuming most time and memory to speed up dependency management
Palanteer
Lean, high-resolution instrumentation for C++ and Python applications
AI-powered workflowsC++
Why teams choose it
- Nanosecond-resolution event logging with ~25 ns overhead
- Automatic instrumentation for Python functions, memory, exceptions and coroutines
- Single-header, cross-platform C++ library with compile-time string hashing and stripping
Watch for
Automatic C++ instrumentation limited to Linux GCC
Migration highlight
Real-time performance profiling
Capture nanosecond timestamps of function calls and memory usage to identify bottlenecks.
MTuner
Cross‑platform C/C++ memory profiler with time‑based history
Permissive licenseAI-powered workflowsC++
Why teams choose it
- Full time‑based history of every allocation and free
- Cross‑platform support: Windows, PlayStation, Switch, Android
- Powerful query engine for deep memory behavior analysis
Watch for
Requires Qt and related build dependencies to compile
Migration highlight
Console game memory leak detection
Identify and fix leaks across frames, reducing crashes on PlayStation and Switch.
Scalene
Fast line‑level CPU, GPU, and memory profiling with AI suggestions
Active developmentPermissive licenseAI-powered workflowsPython
Why teams choose it
- Line‑level CPU, GPU, and memory profiling with low overhead
- AI‑driven optimization suggestions from multiple providers
- Interactive web‑based GUI with sortable, color‑coded reports
Watch for
GPU profiling limited to NVIDIA hardware
Migration highlight
Find CPU hotspots in a web service
Identify and refactor the slowest functions, reducing request latency by up to 30%.
Choosing a continuous profiling alternative
Teams replacing Parca in continuous profiling workflows typically weigh self-hosting needs, integration coverage, and licensing obligations.
- 11 options are actively maintained with recent commits.
Tip: shortlist one hosted and one self-hosted option so stakeholders can compare trade-offs before migrating away from Parca.