InfoQ Homepage Presentations Continuous Optimization of Microservices Using ML
Continuous Optimization of Microservices Using ML
55:02
Summary
Ramki Ramakrishna shares Twitter’s recent experience in applying a technique from machine learning, called Bayesian optimization, to the performance tuning problem. He describes the implementation of a service for continuously optimizing microservices in the data center using this technique.
Bio
Ramki Ramakrishna is a staff software engineer in the Infrastructure Engineering Division of Twitter. He is a member of the JVM team and of the Twitter Architecture Group. His principal contributions have been in the areas of performance analysis, tuning and adaptive optimization, parallel and concurrent garbage collection, and the synchronization infrastructure within the JVM.
About the conference
Software is changing the world. QCon empowers software development by facilitating the spread of knowledge and innovation in the developer community. A practitioner-driven conference, QCon is designed for technical team leads, architects, engineering directors, and project managers who influence innovation in their teams.
Feb 06, 2018