Leveraging Deep Learning to Improve the Performance Predictability of Cloud Microservices

05/02/2019
by   Yu Gan, et al.
0

Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as cloud services transition from monolithic designs to microservices. Detecting QoS violations after they occur in systems with microservices results in long recovery times, as hotspots propagate and amplify across dependent services. We present Seer, an online cloud performance debugging system that leverages deep learning and the massive amount of tracing data cloud systems collect to learn spatial and temporal patterns that translate to QoS violations. Seer combines lightweight distributed RPC-level tracing, with detailed low-level hardware monitoring to signal an upcoming QoS violation, and diagnose the source of unpredictable performance. Once an imminent QoS violation is detected, Seer notifies the cluster manager to take action to avoid performance degradation altogether. We evaluate Seer both in local clusters, and in large-scale deployments of end-to-end applications built with microservices with hundreds of users. We show that Seer correctly anticipates QoS violations 91 begin with in 84 application-level design bugs, and provide insights on how to better architect microservices to achieve predictable performance.

READ FULL TEXT

page 2

page 4

page 6

research
04/24/2018

Seer: Leveraging Big Data to Navigate the Increasing Complexity of Cloud Debugging

Performance unpredictability in cloud services leads to poor user experi...
research
05/27/2021

Sinan: Data-Driven, QoS-Aware Cluster Management for Microservices

Cloud applications are increasingly shifting from large monolithic servi...
research
05/27/2019

An Open-Source Benchmark Suite for Cloud and IoT Microservices

Cloud services have recently started undergoing a major shift from monol...
research
05/25/2018

The Architectural Implications of Microservices in the Cloud

Cloud services have recently undergone a shift from monolithic applicati...
research
10/12/2022

Building Heterogeneous Cloud System for Machine Learning Inference

Online inference is becoming a key service product for many businesses, ...
research
01/01/2021

Sage: Using Unsupervised Learning for Scalable Performance Debugging in Microservices

Cloud applications are increasingly shifting from large monolithic servi...
research
04/26/2020

Signature-based Selection of IaaS Cloud Services

We propose a novel approach to select IaaS cloud services for a long-ter...

Please sign up or login with your details

Forgot password? Click here to reset