SLAOrchestrator: Reducing the Cost of Performance SLAs for Cloud Data Analytics


Jennifer Ortiz, Brendan Lee, and Magdalena Balazinska, University of Washington; Johannes Gehrke, Microsoft; Joseph L. Hellerstein, eScience Institute


SLAOrchestrator is a new system designed to reduce the price increases necessary to support performance SLAs in cloud analytics systems. SLAOrchestrator is designed for SLAs that guarantee per-query execution times. Its core architecture consists of a double learning loop that improves both SLAs and resource management over time. It further utilizes an efficient combination of elastic query scheduling and multi-tenant resource provisioning algorithms to reduce the costs of performance guarantees.

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@inproceedings {216035,
author = {Jennifer Ortiz and Brendan Lee and Magdalena Balazinska and Johannes Gehrke and Joseph L. Hellerstein},
title = {{SLAOrchestrator}: Reducing the Cost of Performance {SLAs} for Cloud Data Analytics},
booktitle = {2018 USENIX Annual Technical Conference (USENIX ATC 18)},
year = {2018},
isbn = {978-1-939133-01-4},
address = {Boston, MA},
pages = {547--560},
url = {},
publisher = {USENIX Association},
month = jul,

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