Broken down by method name, class name, and line number. Without complex overhead, in any language or framework.
Thanks to eBPF's nature, Parca Agent operates in Linux kernel space allowing it to grab exactly the data needed at low overhead.
Get a full picture of how your app performs in production.
Multi-dimensional data model
Optimized, built-in storage
Support for pushing and
pulling profiles from targets
Query engine specifically
designed for profiling data
Targets are discovered via service
discovery or static configuration
Label-selector based query
Never miss the important data with a continuous profiling.
You never know at which point in time you are going to need profiling data, so always collect it at low overhead.Learn more
Build faster and more reliable apps with Parca
Many organizations have 20-30% of resources wasted in easily optimized code paths. The Parca Agent aims to lower the bar of starting to profile by requiring zero-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 query, such as comparing versions of software or any other dimension.
Profiling data provides unique insight and depth into what code a process executed over time. Situations, traditionally difficult to troubleshoot, memory leaks, but also momentary spikes in CPU or I/O causing unexpected behavior can be easily understood with continuous profiling.
The latest deploy of your application has a performance regression? Understand with a single query where CPU time is spent differently now.