Abstract
Multi-tenant distributed systems composed of small services, such as Service-oriented Architectures (SOAs) and Micro-services, raise new challenges in attaining high performance and efficient resource utilization. In these systems, a request execution spans tens to thousands of processes, and the execution paths and resource demands on different services are generally not known when a request first enters the system. In this paper, we highlight the fundamental challenges of regulating load and scheduling in SOAs while meeting end-to-end performance objectives on metrics of concern to both tenants and operators. We design Wisp, a framework for building SOAs that transparently adapts rate limiters and request schedulers system-wide according to operator policies to satisfy end-to-end goals while responding to changing system conditions. In evaluations against production as well as synthetic workloads, Wisp successfully enforces a range of end-to-end performance objectives, such as reducing average latencies, meeting deadlines, providing fairness and isolation, and avoiding system overload.
Original language | English (US) |
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Title of host publication | SoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing |
Publisher | Association for Computing Machinery, Inc |
Pages | 611-623 |
Number of pages | 13 |
ISBN (Electronic) | 9781450350280 |
DOIs | |
State | Published - Sep 24 2017 |
Event | 2017 Symposium on Cloud Computing, SoCC 2017 - Santa Clara, United States Duration: Sep 24 2017 → Sep 27 2017 |
Publication series
Name | SoCC 2017 - Proceedings of the 2017 Symposium on Cloud Computing |
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Conference
Conference | 2017 Symposium on Cloud Computing, SoCC 2017 |
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Country/Territory | United States |
City | Santa Clara |
Period | 09/24/17 → 09/27/17 |
Bibliographical note
Publisher Copyright:© 2017 Association for Computing Machinery.
Keywords
- Microservices
- Rate limiting
- Resource management
- Scheduling
- Service-oriented architectures
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Theoretical Computer Science