Scaling a Distributed Stateful System: A LinkedIn Case Study

Friday, June 08, 2018 - 10:00 am10:55 am

Sai Kiran Kanuri, LinkedIn

Abstract: 

A system is called scalable if it manages to take additional users and requests without losing any noticeable performance. Scaling a data system involves significant movement and replication of data within a cluster. This can put considerable load on a system that is already running hot, affecting the service experience.

Some of the topics that I would touch upon include:

  • Replication
  • Data distribution
  • Load balancing
  • Cluster management
  • Client Data
  • Capacity Management
  • Tuning
BibTeX
@conference {214977,
author = {Sai Kiran Kanuri},
title = {Scaling a Distributed Stateful System: A LinkedIn Case Study},
year = {2018},
publisher = {{USENIX} Association},
}