AutoTune: Improving End-to-end Performance and Resource Efficiency for Microservice Applications
Preprint 2021 en
Authors
MC
Michael Alan Chang
AP
Aurojit Panda
HW
Hantao Wang
Abstract
1 min read
Most large web-scale applications are now built by composing collections (from a few up to 100s or 1000s) of microservices. Operators need to decide how many resources are allocated to each microservice, and these allocations can have a large impact on application performance. Manually determining allocations that are both cost-efficient and meet performance requirements is challenging, even for experienced operators. In this paper we present AutoTune, an end-to-end tool that automatically minimizes resource utilization while maintaining good application performance.
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