Shadi Noghabi, UIUC. “Building Large-Scale Production Systems for Latency-sensitive Applications”

Position:  PhD Student

Current Institution:  University of Illinois, Urbana-Champaign

Abstract:  Building Large-Scale Production Systems for Latency-sensitive Applications

In today’s era of increased engagement with technology, the myriad interactive and latency-sensitive applications around us necessitate handling large scale data quickly and efficiently. My research focuses on designing and developing production-quality systems with particular attention to improving end-to-end latency and building massive-scale solutions. At large scale, providing low latency becomes increasingly challenging with many issues around distribution of data and computation, providing load balance, handling failures, and continuous scaling. We explore these issues on a wide range of systems from, a large-scale geo-distributed blob storage system that is running in production serving 450 million users (Ambry), to a stateful stream processing system handling 100s of TBs for a single job (Samza), and a real-time edge computing framework transparently running jobs in an edge-cloud environment (Fluid-Edge).


Shadi Noghabi is a fifth-year PhD student in the Department of Computer Science Department at UIU, co-advised by Professor Indranil Gupta and Professor Roy Campbell. Her research interests are in distributed systems, cloud computing, big data, and edge computing. She published in SIGMOD and VLDB and collaborated extensively with industry (in particular with LinkedIn and Microsoft Research). Her research career has led to and contributed to many production open-source projects including Ambry (LinkedIn’s geo-distributed object store) and Samza (a top-level Apache project used by over 15 companies). She received the Microsoft Research Dissertation Grant and the Mavis Future Faculty Fellowship.