Litcius/Paper detail

Accelerometer

Akshitha Sriraman, Abhishek Dhanotia

202076 citationsDOI

Abstract

At global user population scale, important microservices in warehouse-scale data centers can grow to account for an enormous installed base of servers. With the end of Dennard scaling, successive server generations running these microservices exhibit diminishing performance returns. Hence, it is imperative to understand how important microservices spend their CPU cycles to determine acceleration opportunities across the global server fleet. To this end, we first undertake a comprehensive characterization of the top seven microservices that run on the compute-optimized data center fleet at Facebook.

Topics & Concepts

MicroservicesComputer scienceServerPopulationScalingScale (ratio)AccelerometerOperating systemDatabaseCloud computingMathematicsGeometryDemographyPhysicsQuantum mechanicsSociologyCloud Computing and Resource ManagementIoT and Edge/Fog ComputingCaching and Content Delivery