Quarantine: fault tolerance for concurrent servers with data-driven selective isolation

Authors:
Thanumalayan Sankaranarayana Pillai;Andrea C. Arpaci-Dusseau;Remzi H. Arpaci-Dusseau
Affiliations:
Computer Sciences Department, University of Wisconsin, Madison;Computer Sciences Department, University of Wisconsin, Madison;Computer Sciences Department, University of Wisconsin, Madison
Venue:
HotPar'11 Proceedings of the 3rd USENIX conference on Hot topic in parallelism
Year:
2011

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Abstract

We present Quarantine, a system that enables data-driven selective isolation within concurrent server applications. Instead of constructing arbitrary isolation boundaries between components, Quarantine collects data to learn where such boundaries should be placed, and then instantiates said barriers to improve reliability. We present the case for data-driven selective isolation, and discuss the challenges in realizing such a system.