Characterizing Service Level Objectives for Cloud Services: Motivation of Short-Term Cache Allocation Performance Modeling
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Date
2020-05
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The Ohio State University
Abstract
Service level objectives (SLOs) stipulate performance goals for cloud applications, microservices, and infrastructure. SLOs are widely used, in part, because system managers can tailor goals to their products, companies, and workloads. Systems research intended to support strong SLOs should target realistic performance goals used by system managers in the field. Evaluations conducted with uncommon SLO goals may not translate to real systems. Some textbooks discuss the structure of SLOs but (1) they only sketch SLO goals and (2) they use outdated examples. We mined real SLOs published on the web, extracted their goals and characterized them. Many web documents discuss SLOs loosely but few provide details and reflect real settings. Systematic literature review (SLR) prunes results and reduces bias by (1) modeling expected SLO structure and (2) detecting and removing outliers. We collected 75 SLOs where response time, query percentile and reporting period were specified. We used these SLOs to confirm and refute common perceptions. For example, we found few SLOs with response time guarantees below 10 ms for 90% or more queries. This reality bolsters perceptions that single digit SLOs face fundamental research challenges.
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Keywords
service level objectives, characterization, cloud computing, performance modeling, systematic literature review
Citation
Published version: J. Ding, R. Cao, I. Saravanan, N. Morris and C. Stewart, "Characterizing Service Level Objectives for Cloud Services: Realities and Myths," 2019 IEEE International Conference on Autonomic Computing (ICAC), Umea, Sweden, 2019, pp. 200-206. https://doi.org/10.1109/ICAC.2019.00032