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Optimizing the Integration of Agent-Based Cloud Orchestrators and Higher-Level Workloads

机译:优化基于代理的云协调器和更高级工作负载的集成

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The flexibility of cloud computing has put significant strain on operations teams. Manually installing and configuring applications in the cloud simply isn't an option anymore. Configuration management automation solves the issue of getting a single application into a certain state automatically and reliably. However, the issue of automatic dependency management between multiple applications is still an "open, hard problem" according to researchers at Google. Agent-based modeling and orchestration tools like Juju solve the issue of getting from zero to a working set of correctly clustered and connected frameworks. The shortcomings of these state-of-the-art tools are that they don't provide efficient ways to model and orchestrate workloads running on top of these frameworks. This paper presents a number of ways to deploy and orchestrate workloads with Juju, compares their performance and overhead, and suggests how this overhead can be minimized.
机译:云计算的灵活性在运营团队中对此产生了重大压力。手动安装和配置云中的应用程序只是不再是选项。配置管理自动化解决了自动且可靠地将单个应用程序获得某个状态的问题。但是,根据Google的研究人员,多个应用程序之间的自动依赖管理问题仍然是一个“开放,难题”。基于代理的建模和编排工具,如juju解决了从零到正确群集和连接框架的工作集的问题。这些最先进的工具的缺点是它们不提供有效的方式来模拟和协调在这些框架之上运行的工作负载。本文介绍了多种部署和协调与juju的工作负载的方法,比较了它们的性能和开销,并提出了如何最小化开销。

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