Blackfire Continuous Profiler
Low-overhead continuous profiling for app performance optimization.
Open-Source Projects
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Lean, high-resolution instrumentation for C++ and Python applications
Palanteer provides lightweight, nanosecond-resolution logging and automatic instrumentation for C++ and Python, enabling real-time event collection, visual analysis, and remote scripting for testing and performance monitoring.
Palanteer is a lean instrumentation suite for C++ and Python applications. By embedding a single‑header library in C++ and importing a Python module, developers gain nanosecond‑resolution event logging with an overhead of roughly 25 ns per event. The system automatically captures function entry/exit, memory allocations, exceptions, garbage‑collection cycles and coroutine activity, while also allowing manual logging of custom data.
Recorded events can be streamed to a Python script for remote control, configuration via CLI handlers, and real‑time visualisation through hierarchical logs, timelines, histograms and flame graphs. The C++ side offers compile‑time string hashing, selective instrumentation groups and optional automatic instrumentation on Linux GCC. Python instrumentation works out‑of‑the‑box and supports multithreading, asyncio and gevent, handling up to eight concurrent streams. This combination makes Palanteer suitable for performance profiling, automated testing, and monitoring of complex, concurrent software.
When teams consider Palanteer, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Real-time performance profiling
Capture nanosecond timestamps of function calls and memory usage to identify bottlenecks.
Automated regression testing
Scripted CLI commands adjust program parameters and verify event streams across runs.
Concurrent system debugging
Log lock wait times and context switches across threads to detect deadlocks.
Async coroutine monitoring
Track entry/exit and garbage‑collection events of asyncio tasks for resource analysis.
The C++ header is cross‑platform, but automatic instrumentation is only available on Linux with GCC.
Typical cost is about 25 ns per event, yielding up to 5 M events/s on a standard x64 machine.
For Python, most instrumentation is automatic; C++ requires including the header and optional macros, with compile‑time selection of instrumentation groups.
Palanteer provides visual tools such as timelines, flame graphs and histograms that can be launched from recorded log files.
Yes, it supports multithreaded programs and can record up to eight concurrent streams.
Project at a glance
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