VAMP: Visual Analytics for Microservices Performance
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing(2024)
摘要
Analysis of microservices' performance is a considerably challenging task due
to the multifaceted nature of these systems. Each request to a microservices
system might raise several Remote Procedure Calls (RPCs) to services deployed
on different servers and/or containers. Existing distributed tracing tools
leverage swimlane visualizations as the primary means to support performance
analysis of microservices. These visualizations are particularly effective when
it is needed to investigate individual end-to-end requests' performance
behaviors. Still, they are substantially limited when more complex analyses are
required, as when understanding the system-wide performance trends is needed.
To overcome this limitation, we introduce vamp, an innovative visual analytics
tool that enables, at once, the performance analysis of multiple end-to-end
requests of a microservices system. Vamp was built around the idea that having
a wide set of interactive visualizations facilitates the analyses of the
recurrent characteristics of requests and their relation w.r.t. the end-to-end
performance behavior. Through an evaluation of 33 datasets from an established
open-source microservices system, we demonstrate how vamp aids in identifying
RPC execution time deviations with significant impact on end-to-end
performance. Additionally, we show that vamp can support in pinpointing
meaningful structural patterns in end-to-end requests and their relationship
with microservice performance behaviors.
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