The website for the 2021 HotCloudPerf edition is up.
Abstract: Interesting approaches to counteract performance variability within cloud datacenters include sending multiple request clones, either immediately or after a specified waiting time. In this paper we present a performance model of cloud applications that utilize the latter concept, known as speculative execution. We study the popular Join-Shortest-Queue load-balancing strategy under the processor sharing queuing discipline. Utilizing the near-synchronized service property of this setting, we model speculative execution using a simplified synchronized service model. Our model is approximate, but accurate enough to be useful even for high utilization scenarios. Furthermore, the model is valid for any, possibly empirical, inter-arrival and service time distributions. We present preliminary simulation results, showing the promise of our proposed model.
2. Migrating from Monolithic to Serverless: A FinTech Case Study - Alireza Goli, Omid Hajihassani, Hamzeh Khazaei, Omid Ardakanian, Moe Rashidi, Tyler Dauphinee
Abstract: Serverless computing is steadily becoming the implementation paradigm of choice for a variety of applications, from data analytics to web applications, as it addresses the main problems with serverfull and monolithic architecture. In particular, it abstracts away resource provisioning and infrastructure management, enabling developers to focus on the logic of the program instead of worrying about resource management which will be handled by cloud providers. In this paper, we consider a document processing system used in FinTech as a case study and describe the migration journey from a monolithic architecture to a serverless architecture. Our evaluation results show that the serverless implementation significantly improves performance while resulting in only a marginal increase in cost.
3. Beyond Microbenchmarks: The SPEC-RG Vision for a Comprehensive Serverless Benchmark - Erwin van Eyk, Joel Schreuner, Simon Eismann, Cristina Abad, Alexandru Iosup
Abstract: Serverless computing services, such as Function-as-a-Service (FaaS), hold the attractive promise of a high level of abstraction and high performance, combined with the minimization of operational logic. Several large ecosystems of serverless platforms, both open- and closed-source, aim to realize this promise. Consequently, a lucrative market has emerged. However, the performance trade-offs of these systems are not well-understood. Moreover, it is exactly the high level of abstraction and the opaqueness of the operational-side that make performance evaluation studies of serverless platforms challenging. Learning from the history of IT platforms, we argue that a benchmark for serverless platforms could help address this challenge. We envision a comprehensive serverless benchmark, which we contrast to the narrow focus of prior work in this area. We argue that a comprehensive benchmark will need to take into account more than just runtime overhead, and include notions of cost, realistic workloads, more (open-source) platforms, and cloud integrations. Finally, we show through preliminary real-world experiments how such a benchmark can help compare the performance overhead when running a serverless workload on state-of-the-art platforms.