What is Parca?
Parca is a continuous profiling project for applications and infrastructure. It helps you save money, improve performance and understand incidents better.
Continuous profiling is the act of taking profiles (such as CPU, Memory, I/O and more) of programs in a systematic way. Parca collects, stores and makes profiles available to be queried over time. It features a powerful multi-dimensional data model, storage and query engine specifically designed for profiling data. Find out more in the Overview.
A single profiler, using eBPF, automatically discovering targets from Kubernetes or systemd across the entire infrastructure with very low overhead. Supports C, C++, Rust, Go, and more!
Optimized Storage & Querying
Efficiently storing profiling data while retaining raw data and allowing slicing and dicing of data through a label-based search. Aggregate profiling data infrastructure wide, view single profiles in time or compare on any dimension.
The configuration and querying experience has been specifically designed to combine naturally with existing Prometheus setups. From configuration paradigms, over target discovery, to querying via arbitrary label-selectors.
Many organizations have 20-30% of resources wasted with easily optimized code paths. The Parca Agent aims to lower the entry bar by requiring 0 instrumentation for the whole infrastructure. Deploy in your infrastructure and get started!
Using profiling data collected over time, Parca can with confidence and statistical significance determine hot paths to optimize. Additionally it can show differences between any label dimension, such as deploys, versions, and regions.
Profiling data provides unique insight and depth into what a process executed over time. Memory leaks, but also momentary spikes in CPU or I/O causing unexpected behavior, is traditionally difficult to troubleshoot are a breeze with continuous profiling.
Join the community!
Join users and companies that are using Parca in production.
Parca was originally created by Polar Signals, Inc.