{"title":"An approach to benchmarking configuration complexity","authors":"Aaron B. Brown, J. Hellerstein","doi":"10.1145/1133572.1133609","DOIUrl":null,"url":null,"abstract":"Configuration is the process whereby components are assembled or adjusted to produce a functional system that operates at a specified level of performance. Today, the complexity of configuration is a major impediment to deploying and managing computer systems. We describe an approach to quantifying configuration complexity, with the ultimate goal of producing a configuration complexity benchmark. Our belief is that such a benchmark can drive progress towards self-configuring systems. Unlike traditional workload-based performance benchmarks, our approach is process-based. It generates metrics that reflect the level of human involvement in the configuration process, quantified by interaction time and probability of successful configuration. It computes the metrics using a model of a standardized human operator, calibrated in advance by a user study that measures operator behavior on a set of parameterized canonical configuration actions. The model captures the human component of configuration complexity at low cost and provides representativeness and reproducibility.","PeriodicalId":285758,"journal":{"name":"EW 11","volume":"146 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EW 11","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1133572.1133609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
Configuration is the process whereby components are assembled or adjusted to produce a functional system that operates at a specified level of performance. Today, the complexity of configuration is a major impediment to deploying and managing computer systems. We describe an approach to quantifying configuration complexity, with the ultimate goal of producing a configuration complexity benchmark. Our belief is that such a benchmark can drive progress towards self-configuring systems. Unlike traditional workload-based performance benchmarks, our approach is process-based. It generates metrics that reflect the level of human involvement in the configuration process, quantified by interaction time and probability of successful configuration. It computes the metrics using a model of a standardized human operator, calibrated in advance by a user study that measures operator behavior on a set of parameterized canonical configuration actions. The model captures the human component of configuration complexity at low cost and provides representativeness and reproducibility.