2024/08/08 by Jakob Görgen, Görgen, Jakob, Vaastav Anand +7
Computer Science · Decision Sciences · #Embedded Systems Design Techniques #FOS: Computer and information sciences #Operating Systems (cs.OS) #Parallel Computing and Optimization Techniques #Performance (cs.PF) #Simulation Techniques and Applications
paper · pdf · doi:10.48550/arxiv.2408.05251
openalex publication_date 2024/08/08 · openalex created_date 2024/09/10 · openalex updated_date 2026/07/28
Fully understanding performance is a growing challenge when building next-generation cloud systems. Often these systems build on next-generation hardware, and evaluation in realistic physical testbeds is out of reach. Even when physical testbeds are available, visibility into essential system aspects is a challenge in modern systems where system performance depends on often sub-μs interactions between HW and SW components. Existing tools such as performance counters, logging, and distributed tracing provide aggregate or sampled information, but remain insufficient for understanding individual requests in-depth. In this paper, we explore a fundamentally different approach to enable in-depth understanding of cloud system behavior at the software and hardware level, with (almost) arbitrarily fine-grained visibility. Our proposal is to run cloud systems in detailed full-system simulations, configure the simulators to collect detailed events without affecting the system, and finally assemble these events into end-to-end system traces that can be analyzed by existing distributed tracing tools.