Abstract
Systems continue to grow in complexity in response to the need to support vast quantities of data and a wide variety of workloads. Small changes in workloads and system configuration can result in significantly different system behaviour and performance characteristics. As a result, system administrators and developers spend many hours diagnosing and debugging performance problems in data systems and the applications that use them. In this paper, we present Sentinel, an analysis tool that assists these users by constructing fine-grained models of system behaviour and comparing these models to pinpoint differences in system behaviour for different workloads and system configurations. Importantly, Sentinel's insights are derived from built-in debug logging libraries without necessitating that their log messages be written to disk, thereby generalizing to all systems that use debug logging without incurring its overheads. Our experiments demonstrate Sentinel's superiority in analyzing the execution behaviour and performance characteristics of database systems, client applications, and web servers compared to prior approaches.
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