Automated analytics systems to navigate the complexity of performance unpredictability in cloud applications
Abstract
Performance unpredictability is a major roadblock to cloud adoption and has cost and revenue ramifications. As a result, engineers spend most of their time in (1) diagnosing performance problems using monitoring data of the applications and (2) frequently updating their applications to remediate performance. This talk presents automated analytics approaches using statistically driven techniques that are essential to accurately localize and diagnose performance variations in the code and help prevent them in the frequent code delivery cycles.
Bio:
Mert Toslali is a computer engineering Ph.D. student at Boston University. His research involves monitoring, performance analytics, online experimentation, and distributed tracing.
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Meeting ID: 960 3825 1227
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Meeting ID: 960 3825 1227
Passcode: see colloquium email