面向服务的多租户(SO-MT):使用Docker为现有的服务组合引擎启用多租户

G. Nikol, Michael Träger, Simon Harrer, G. Wirtz
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引用次数: 7

摘要

在基于Web服务的soa中,BPEL 2.0是通过组合现有服务来定义服务的选择。基于BPEL的服务可以直接在BPEL引擎上执行。随着云计算的兴起,公司的目标是将服务托管外包给云提供商。为了实现规模经济,云提供商必须用最少的资源托管这些服务,并保持来自不同租户的服务隔离。但是BPEL引擎通常不支持多租户。因此,供应商要么必须自己扩展引擎,要么在自己的(虚拟)机器上托管每个服务,从而使用昂贵的开发或计算资源。我们的方法解决了这个问题,将每个服务托管在自己独立的最小容器中,通过api公开管理功能,支持复杂的多租户特性或在顶部进行水平扩展。我们的目标是通过a)利用Docker容器来隔离彼此之间的服务,b)从容器中删除未使用的软件,c)用最少的资源启动BPEL引擎,以及d)在保留管理api的同时提取管理功能来实现这一点。我们对Apache ODE的案例研究表明,我们只需要少量的开发工作就可以节省大量的运行时资源。虽然这种方法有助于将soa迁移到云中,但也可以利用它来构建更便宜的资源高效的基于bpel的微服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Service-Oriented Multi-tenancy (SO-MT): Enabling Multi-tenancy for Existing Service Composition Engines with Docker
In Web Services-based SOAs, BPEL 2.0 is the choice for defining services by composing existing ones. BPEL-based services can be directly executed on BPEL engines. With the rise of the cloud, companies aim to outsource service hosting to cloud providers. To achieve economies of scale, a cloud provider must host such services with minimal resources and keep the services from different tenants isolated. But BPEL engines typically do not support multi-tenancy. As a result, a vendor either has to extend the engine himself or host every service on its own (virtual) machine, thereby using either costly development or computing resources. Our approach solves this problem by hosting each service in its own isolated and minimal container which exposes the management functionality through APIs enabling complex multi-tenancy features or horizontal scaling on top. We aim to implement this by a) leveraging Docker container to isolate the services from each other, b) removing unused software from the container, c) starting the BPEL engine with minimal resources, and d) extracting management functionality while keeping management APIs. Our case study with Apache ODE shows that we can save significant runtime resources with only minor development effort. While this approach helps in moving SOAs into the cloud, it can also be leveraged to build resource efficient BPEL-based microservices cheaper.
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