ThrottleBot - Performance without Insight
Michael Alan Chang, Aurojit Panda, Yuan-Cheng Tsai, Hantao, Wang, Scott Shenker

TL;DR
ThrottleBot is an automated system designed to identify the most impactful resource allocations for microservices in large-scale applications, simplifying performance optimization and resource provisioning.
Contribution
It introduces ThrottleBot, a novel system that automates resource impact analysis for microservices, enhancing deployment efficiency and performance tuning.
Findings
Effective in synthetic and real-world applications
Automates resource impact identification
Facilitates push-button deployment with orchestrators
Abstract
Large scale applications are increasingly built by composing sets of microservices. In this model the functionality for a single application might be split across 100s or 1000s of microservices. Resource provisioning for these applications is complex, requiring administrators to understand both the functioning of each microservice, and dependencies between microservices in an application. In this paper we present ThrottleBot, a system that automates the process of determining what resource when allocated to which microservice is likely to have the greatest impact on application performance. We demonstrate the efficacy of our approach by applying ThrottleBot to both synthetic and real world applications. We believe that ThrottleBot when combined with existing microservice orchestrators, e.g., Kubernetes, enables push-button deployment of web scale applications.
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Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · IoT and Edge/Fog Computing
