Ana Klimovic (Stanford University): Elastic Ephemeral Storage for Serverless Computing

22.06.2018 10:00

CAB E 72

Talk by Ana Klimovic (Stanford University): Elastic Ephemeral Storage for Serverless Computing


Serverless computing is an increasingly popular cloud service, enabling users to launch thousands of short-lived tasks ("lambdas") with high elasticity and fine-grain resource billing. High elasticity and granular resource allocation make serverless computing appealing for interactive data analytics. However, a key challenge is sharing intermediate data between tasks in analytics jobs. Exchanging data directly between short-lived lambdas is difficult, thus the natural approach is to store ephemeral data in a common remote data store. Unfortunately, existing storage systems are not designed to meet the elasticity, performance and granular cost requirements of serverless applications. We first characterize the ephemeral I/O requirements of serverless analytics applications. We then present our design and implementation of a distributed data store that elastically and automatically scales to rightsize storage cluster resources across multiple dimensions (storage capacity, CPU cores and network bandwidth). We show the system cost-effectively satisfies dynamic application I/O requirements. Short


Ana Klimovic is a final year Ph.D. student at Stanford University, advised by Professor Christos Kozyrakis. Her research interests are in computer systems and architecture. She is particularly interested in building high performance, resource efficient storage and computing systems for large-scale datacenters. Ana has interned at Facebook and Microsoft Research. Before coming to Stanford, Ana graduated from the Engineering Science undergraduate program at the University of Toronto. She is a Microsoft Research Ph.D. Fellow, Stanford Graduate Fellow and Accel Innovation Scholar. --