Parca

Profiling Python with eBPF: A New Frontier in Performance Analysis Profiling Python applications can be challenging, especially in scenarios involving high-performance requirements or complex workloads. Existing tools often require code instrumentation, making them impractical for certain use cases. Enter eBPF (Extended Berkeley Packet Filter)—a revolutionary Linux technology—and the open-source project Parca, which together are reshaping the landscape of Python profiling. In this post, I’ll explore how eBPF enables continuous profiling, discuss challenges like stack unwinding in Python, and demonstrate the power of modern profiling tools. ...

For years Google has consistently been able to cut down multiple percentage points in their fleet-wide resource usage every quarter, using techniques described in their “Google-Wide Profiling” paper. Ad-hoc profiling has long been part of the developer’s toolbox to analyze CPU and memory usage of a running process, however, through continuous profiling, the systematic collection of profiles, entirely new workflows suddenly become possible. Matthias and Kemal will start this talk with an introduction to profiling with Go and demonstrate via Conprof - an open-source continuous profiling project - how continuous profiling allows for an unprecedented fleet-wide understanding of code at runtime. Attendees will learn how to continuously profile Go code to help guide building robust, reliable, and performant software and reduce cloud spend systematically. ...