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Retro: Targeted Resource Management in Multi-tenant Distributed Systems.

, , , and . NSDI, page 589-603. USENIX Association, (2015)

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Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters., , , , , and . HotCloud, USENIX Association, (2009)Automatic exploration of datacenter performance regimes., , , , , and . ACDC@ICAC, page 1-6. ACM, (2009)Retro: Targeted Resource Management in Multi-tenant Distributed Systems., , , and . NSDI, page 589-603. USENIX Association, (2015)Combining Visualization and Statistical Analysis to Improve Operator Confidence and Efficiency for Failure Detection and Localization., , , , , , , , , and 1 other author(s). ICAC, page 89-100. IEEE Computer Society, (2005)The SCADS Director: Scaling a Distributed Storage System Under Stringent Performance Requirements., , , , , and . FAST, page 163-176. USENIX, (2011)2DFQ: Two-Dimensional Fair Queuing for Multi-Tenant Cloud Services., , , , and . SIGCOMM, page 144-159. ACM, (2016)HiLighter: Automatically Building Robust Signatures of Performance Behavior for Small- and Large-Scale Systems., , and . SysML, USENIX Association, (2008)Automating Datacenter Operations Using Machine Learning.. University of California, Berkeley, USA, (2010)VideoEdge: Processing Camera Streams using Hierarchical Clusters., , , , , , and . SEC, page 115-131. IEEE, (2018)Evaluating how interactive visualizations can assist in finding samples where and how computer vision models make mistakes., , and . PacificVis, page 307-312. IEEE, (2024)