Pattern-based composite application deployment

T. Eilam, Michael Elder, A. Konstantinou, E. Snible
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引用次数: 54

Abstract

The deployment of composite applications and services in distributed or compute cloud environments is still a challenging task that is a key source of operational cost and risk. Current approaches to composite deployments can be categorized as workflow based and model based. In the workflow based approach, deployers create end-to-end workflows to automate application deployment, while in the model based approach architects design detailed “desired state” models and validate they meet all requirements and constraints. Today, there is no formally understood relationship and mapping between “desired state” models and deployment workflows, posing a challenge and limitation on architects and deployers. In this paper we propose a new model based approach to bridge the gap between deployment models and workflows. Our approach supports separation of concerns where basic automation building blocks (such as scripts and workflows) can be developed independently of the resource model and with no knowledge of it. Therefore, the method enables deployers to continue to leverage useful libraries of automation building blocks, while enjoying the benefits of a sound resource model, used for validation and constraint satisfaction. We propose algorithms and implementation to generate end-to-end workflows for input “desired state” resource models, based on given libraries of automation building blocks. Our approach has been incorporated into IBM's leading deployment modeling platform [15] and is in active use by customers in a large range of applications.
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基于模式的复合应用程序部署
在分布式或计算云环境中部署复合应用程序和服务仍然是一项具有挑战性的任务,是运营成本和风险的主要来源。当前的组合部署方法可以分为基于工作流和基于模型两类。在基于工作流的方法中,部署人员创建端到端工作流来自动化应用程序部署,而在基于模型的方法中,架构师设计详细的“期望状态”模型,并验证它们满足所有需求和约束。今天,在“期望状态”模型和部署工作流之间还没有被正式理解的关系和映射,这给架构师和部署人员带来了挑战和限制。在本文中,我们提出了一种新的基于模型的方法来弥合部署模型和工作流之间的差距。我们的方法支持关注点分离,其中基本的自动化构建块(例如脚本和工作流)可以独立于资源模型开发,并且不需要了解它。因此,该方法使部署人员能够继续利用自动化构建块的有用库,同时享受用于验证和约束满足的可靠资源模型的好处。我们提出算法和实现,以基于给定的自动化构建块库,为输入“期望状态”资源模型生成端到端工作流。我们的方法已经被整合到IBM领先的部署建模平台中[15],并且在大范围的应用程序中被客户积极使用。
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