Abstract
For modern software systems, performance analysis can be a challenging task. The software stack can be a complex, multi-layer, multi-component, concurrent, and parallel environment with multiple contexts of execution and multiple sources of performance data. Although much performance data is available, because modern systems incorporate many mature data-collection mechanisms, analysis algorithms suffer from the lack of a unifying programming environment for processing the collected performance data, potentially from multiple sources, in a convenient and script-like manner. This paper presents Weir, a streaming language for systems performance analysis. Weir is based on the insight that performanceanalysis algorithms can be naturally expressed as stream-processing pipelines. In Weir, an analysis algorithm is implemented as a graph composed of stages, where each stage operates on a stream of events that represent collected performance measurements. Weir is an imperative streaming language with a syntax designed for the convenient construction of stream pipelines that utilize composable and reusable analysis stages. To demonstrate practical application, this paper presents the authors' experience in using Weir to analyze performance in systems based on the Xen virtualization platform.
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