Fast, Light-weight, and Accurate Performance Evaluation using Representative Datacenter Behaviors
Jaewon Lee, Dongmoon Min, Ilkwon Byun, Hanhwi Jang, Jangwoo Kim · 2023
Datacenters rapidly evolve by adopting new features such as new hardware deployment and software patches. Adopting a new feature requires an accurate evaluation of its impact to minimize the risk to the multi-million dollar computing infrastructure. However, a comprehensive performance analysis of a datacenter is extremely challenging due to its cost and multitenancy. Evaluating the performance in a live datacenter is accurate but prohibitive to prevent any damage to production services. Using conventional load-testing benchmarks on small-scale testbeds is imprecise as they do not consider the effect of other co-located jobs.