Many organizations have 20-30% of resources wasted with easily optimized code paths. The Polar Signals 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, Polar Signals 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, are traditionally difficult to troubleshoot but are a breeze with continuous profiling.
Polar Signals is a continuous profiling product 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!
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.
Supports any pprof formatted profiles allowing for wide language adoption and interoperability with existing tooling.
Open Source is part of our DNA. Polar Signals originally created the Parca project, and maintains it.
Our agent supports all compiled languages, eg. C, C++, Rust, Go (with extended support for Go). With native libraries, any pprof formatted profile can be written to Polar Signals. Further language support coming in the upcoming weeks and months.
We have observed <1% in CPU, but more elaborate and reproducible reports coming.
No. Profiling data is made up of statistics representing for example how much time the CPU has spent in a particular function, but the function metadata is decoupled from the actual executable code. Think of it as statistics and metadata for us humans to make sense of the statistics.