Abstract: Serverless computing offerings from cloud providers have gained significant traction in recent years due to the advantages that these platforms bring with their flexible pricing models, built-in scalability, and minimal operational requirements. In a recent survey of serverless use cases, we found a wide variety of applications that depend on these services, including implementing the core functionality at the backend of mobile applications, automating the DevOps tasks of complex distributed applications, real-time processing of IoT streaming data, and scientific applications. To properly support these applications, the platforms should be fast, self-managing, and provide support for diverse QoS requirements. As a result, novel improvements to serverless platforms are rapidly being proposed and adopted. Evaluating these solutions necessitates application-based, workload-aware benchmarking tools that the community can rely on. This talk addresses these challenges and our research efforts on tackling them, presenting a performance engineering perspective about the current state and future challenges of serverless computing research. I will describe our solutions in resource management for serverless platforms, focusing on solutions that improve performance or reduce costs via scheduling, caching, and right-sizing of resources, along with our ongoing efforts in developing an application-driven serverless benchmark.

Bio: Cristina L. Abad is a Professor in the Department of Electrical Engineering and Computer Science at Escuela Superior Politécnica del Litoral in Guayaquil-Ecuador, where she leads the Distributed Systems Research Lab and co-directs the Big Data Research Group. She received her Ph.D. in 2014 from the University of Illinois at Urbana-Champaign. For three years during her PhD, she was a Software Engineering Intern in the Hadoop Core Team at Yahoo, where she worked on workload modeling and evaluation of the HDFS and had the opportunity to contribute to the Apache Hadoop codebase. Her research interests lie at the intersection of Distributed Systems and Performance Engineering. In particular, she works on designing and building distributed systems that can self-adapt to workload changes and maximize performance, with applications in cloud computing and Big Data. Her international funding sources have included VLIR-UOS, Google, Microsoft, Amazon Web Services, and AT&T Labs Research. She has received a Fulbright Fellowship, a UIUC CS Excellence Fellowship, and two Google Faculty Research Awards. Cristina is a member of IEEE, ACM, SPEC RG, and Usenix, and is the elected Secretary of the SPEC RG.