Sponsored by LightStep
July 31, 2018
11 AM ET
Applications have evolved – again – and it’s time for performance analysis to follow suit
In the last twenty years, the internet applications that improve our lives and drive our economy have become far more powerful. As a necessary side-effect, these applications have become far more complex, and that makes it much harder for us to measure and explain their performance—especially in real-time. Despite that, the way that we both reason about and actually measure performance has barely changed.
Join Kay Ousterhout, Software Engineer at LightStep, as she discusses how to improve our mental model for recognizing and diagnosing system anomalies.
Kay Ousterhout, Software Engineer at LightStep
Kay Ousterhout is a software engineer at LightStep, where she’s building performance management tools that enable users to understand the performance of complex distributed systems. Before LightStep, Kay received a PhD from UC Berkeley. Her thesis focused on building high-performance data analytics frameworks that allow users to reason about - and optimize for - performance. Kay is also a committer and PMC member for Apache Spark; her work on Spark has focused on improving scheduler performance.
Additional References:
- Company Website: www.lightstep.com
- Company Twitter: @LightStepHQ
- Company GitHub: @LightStep
- Personal Website: Kayousterhout.org
- Personal Twitter: @kayousterhout
- Personal GitHub: @kayousterhout