![]() ![]() Our test suite includes six different stress tests - a CPU intensive test, a memory intensive test, a disk intensive test, two network intensive tests (send and receive) and a fork bomb. In this paper, we present the design of a performance isolation benchmark that quantifies the degree to which a virtualization system limits the impact of a misbehav- ing virtual machine on other well-behaving virtual ma- chines running on the same physical machine. The review shows the emerging challenges and trending concepts in multi-tenancy within cloud native architecture, but also discusses the improvement in multi-tenancy while considering cloud native architecture in the recent years. We applied a selection procedure resulting in 64 peer reviewed publications over the last six years between 2015 to 2022 and the selected studies were classified through the characterisation framework. We started from over 921 potentially relevant peer reviewed publications. A systematic mapping method was used to systematically compare, classify, analyse, evaluate and appraise existing works of literature on multi-tenancy in cloud-native. The purpose of this study is to survey existing research on multi-tenancy in cloud-native architecture in order to identify useful trends, opportunity, challenges and finally the needs for further researches. ![]() Multi-tenancy an essential part of the cloud computing, has not been fully. However, there are parts that are yet to be fully discovered like multi-tenancy. Finally, we develop a container orchestration framework for geo-distributed environments that offers policy-rich placement, autoscaling, bursting, network routing, and dynamic resource provisioning capabilities.Ĭloud-native architectures has become an essential part of the cloud computing paradigm with the capacity of improved horizontal and vertical scalability, automation, usability and multi-tenancy. Second, we propose a proportional controller to dynamically improve the stability of geo-distributed deployments at run-time in Kubernetes Federations. First, we present an experimental analysis of autoscaling in Kubernetes clusters at the container and Virtual Machine levels. In this thesis, we address some of the resource management challenges using container technology. However, resource management in these geo-distributed computing environments is difficult due to wide geographical distributions, poor network conditions, heterogeneity of resources, and limited capacity. Geo-distributed computing environments such as hybrid cloud, multi-cloud and Fog Computing need to be managed autonomously at large scales to improve resource utilization, maximize performance, and save costs. We shortly discuss three possible complementary solutions to tackle this challenge. However an open research challenge is that, when the number of parameters increases, the total tuning cost may also increase beyond what is acceptable for contemporary cloud-native applications. Our experiments showed that k8-resource-optimizer can find near-optimal configurations for different multi-tenant deployment settings and different types of resource parameters. We illustrate and validate the tool for optimizing different resource configuration properties of a simple job processing application. We propose a versatile tool for cost-effective SLO tuning, named k8-resource-optimizer, that relies on black-box performance tuning algorithms. However, to support cost-effective enforcement of Service Level Objectives (SLOs) about response time or throughput, an automated resource optimization approach is needed for mapping custom SLOs of different tenants to cost-efficient resource allocation policies. Resource management concepts of container orchestration platforms such as Kubernetes can be used to achieve multi-tenancy with quality of service differentiation between tenants. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |