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Creators/Authors contains: "Mingyu Liang"

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  1. ; ; ; ; ; ; ; (, Proceedings International Symposium on Computer Architecture)
    Accepted Manuscript Full Text Available
  2. (, IEEE Micro Special Issue on Top Picks from Computer Architecture Conference of 2021)
    Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite their benefits, microservices are prone to cascading performance issues, and can lead to prolonged periods of degraded performance. We present Sage, a machine learning-driven root cause analysis system for interactive cloud microservices that is both accurate and practical. We show that Sage correctly identifies the root causes of performance issues across a diverse set of microservices and takes action to address them, leading to more predictable, performant, and efficient cloud systems. 
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    Accepted Manuscript Full Text Available