Evaluation and Improvement of Application Deployment in Hybrid Edge Cloud Environment : Using OpenStack, Kubernetes, and Spinnaker

Detta är en Master-uppsats från KTH/Skolan för elektroteknik och datavetenskap (EECS)

Sammanfattning: Traditional mechanisms of deployment of deferent applications can be costly in terms of time and resources, especially when the application requires a specific environment to run upon and has a different kind of dependencies so to set up such an application, it would need an expert to find out all required dependencies. In addition, it is difficult to deploy applications with efficient usage of resources available in the distributed environment of the cloud. Deploying different projects on the same resources is a challenge. To solve this problem, we evaluated different deployment mechanisms using heterogeneous infrastructure-as-a-service (IaaS) called OpenStack and Microsoft Azure. we also used platform-as-a-service called Kubernetes. Finally, to automate and auto integrate deployments, we used Spinnaker as the continuous delivery framework. The goal of this thesis work is to evaluate and improve different deployment mechanisms in terms of edge cloud performance. Performance depends on achieving efficient usage of cloud resources, reducing latency, scalability, replication and rolling upgrade, load balancing between data nodes, high availability and measuring zero- downtime for deployed applications. These problems are solved basically by designing and deploying infrastructure and platform in which Kubernetes (PaaS) is deployed on top of OpenStack (IaaS). In addition, the usage of Docker containers rather than regular virtual machines (containers orchestration) will have a huge impact. The conclusion of the report would demonstrate and discuss the results along with various test cases regarding the usage of different methods of deployment, and the presentation of the deployment process. It includes also suggestions to develop more reliable and secure deployment in the future when having heterogeneous container orchestration infrastructure.

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