There is an increasing interest in extending traditional cloud-native technologies, such as Kubernetes, outside the data center to build a continuum towards the edge and between. However, traditional resource orchestration algorithms do not work well in this case, and it is also difficult to test applications for a heterogeneous cloud infrastructure without actually building it. To address these challenges, we propose a new methodology to aid in deploying, testing, and analyzing the effects of microservice placement and scheduling in a heterogeneous Cloud environment. With this methodology, we can investigate any combination of deployment scenarios and monitor metrics in accordance with the placement of microservices in the cloud-edge continuum. Edge devices may be simulated, but as we use Kubernetes, any device which can be attached to a Kubernetes cluster could be used. In order to demonstrate our methodology, we have applied it to the problem of network function placement of an open-source 5G core implementation.
翻译:人们越来越关心将传统的云原技术,如Kubernetes等传统云原技术推广到数据中心之外,以建立向边缘和之间之间的连续体。然而,传统资源管弦算法在本案中效果不佳,而且如果不实际建立云层基础设施,也很难测试多种云层基础设施的应用情况。为了应对这些挑战,我们提议了一种新的方法,以协助部署、测试和分析在多变云环境中的微观服务安置和时间安排的影响。通过这种方法,我们可以根据将微观服务置于云端连续体中的情况,调查各种部署情景的任何组合,并监测各种指标。可以模拟电磁装置,但随着我们使用Kubernetes,可以使用与Kubernetes集群连接的任何装置。为了证明我们的方法,我们应用了这种方法来帮助在网络功能中放置开放源5G核心执行功能的问题。