用于云的自动化工具分析服务

Ryan Chard, K. Chard, Bryan K. F. Ng, K. Bubendorfer, Alex Rodriguez, R. Madduri, Ian T Foster
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引用次数: 14

摘要

云提供商提供了一组具有不同资源容量的不同实例类型,旨在满足广泛的用户需求。虽然这种灵活性是云计算模型的主要优点,但在为给定应用程序选择最合适的实例类型时,它也会带来挑战。次优实例选择可能导致性能差和/或成本增加,在重复执行应用程序时会产生重大影响。然而,选择最佳实例类型是一项挑战,因为每种实例类型可以配置不同,应用程序性能依赖于输入数据和配置,并且实例类型和应用程序经常更新。我们提供了一个服务,它支持在不同实例类型上自动分析应用程序性能,以创建丰富的应用程序配置文件,这些配置文件可用于比较、配置和调度。此服务可以动态地提供云实例、自动部署和上下文化应用程序、传输输入数据集、监视执行性能,并创建具有细粒度资源使用信息的组合配置文件。我们使用了来自四个生产基因组网关的真实使用数据,并估计在自主供应系统中使用配置文件可以减少高达15.7%的执行时间和高达86.6%的成本。
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An Automated Tool Profiling Service for the Cloud
Cloud providers offer a diverse set of instance types with varying resource capacities, designed to meet the needs of a broad range of user requirements. While this flexibility is a major benefit of the cloud computing model, it also creates challenges when selecting the most suitable instance type for a given application. Sub-optimal instance selection can result in poor performance and/or increased cost, with significant impacts when applications are executed repeatedly. Yet selecting an optimal instance type is challenging, as each instance type can be configured differently, application performance is dependent on input data and configuration, and instance types and applications are frequently updated. We present a service that supports automatic profiling of application performance on different instance types to create rich application profiles that can be used for comparison, provisioning, and scheduling. This service can dynamically provision cloud instances, automatically deploy and contextualize applications, transfer input datasets, monitor execution performance, and create a composite profile with fine grained resource usage information. We use real usage data from four production genomics gateways and estimate the use of profiles in autonomic provisioning systems can decrease execution time by up to 15.7% and cost by up to 86.6%.
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