Continuous profiling is a widely used practice at Google but has only recently started gaining popularity in the Observability space, however, resources on this topic are still rare compared to other observability signals especially on open source projects.
This talk intends to educate the wider community about the possibilities of continuous profiling, and give a glimpse into open-source tooling allowing everyone to join in on the practice and enabling everyone to build better software.
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 will start this talk with an introduction to profiling with Go and demonstrate via Parca - an open-source continuous profiling project - how continuous profiling allows for an unprecedented fleet-wide understanding of code at production runtime.
Attendees will learn how to continuously profile code to help guide building robust, reliable, and performant software and reduce cloud spend systematically in various languages.
