Extending the Kubernetes operator Kubegres to handle database restoration from dump files

Detta är en Uppsats för yrkesexamina på avancerad nivå från Luleå tekniska universitet/Institutionen för system- och rymdteknik

Sammanfattning: The use of cloud-native technologies has grown in popularity in recent years. With its ability to take advantage of the full benefits of cloud computing, cloud-native architecture has become a hot topic among developers and IT professionals. It refers to building and running applications using cloud services and architectures, including containerization, microservices, and automation tools such as Kubernetes to enable fast and continuous delivery of software applications. In Kubernetes, the desired state of a resource is described declaratively and then handles the details of how to get there. Databases are notoriously hard to deploy in such environments, and the Kubernetes operator pattern extends the resources it manages and how to get to the desired state, called reconcile function. Operators exist to manage PostgreSQL databases with backup and restore functionality, and some require a license to be used. Kubegres is a free-to-use open-source operator, but it lacks restore functionality. This thesis aims to extend the Kubegres operator to support database restoration using dump files. It includes how to create the restore process in Kubernetes, what modifications must be done to the current architecture, and how to make the reconcile function robust and self-healing yet customizable to fit many different needs. Research has been done to explore the design of other operators that already support database restoration. It inspired the design of the resource definition and the restoration process. A new resource definition was added to define the desired state of the database restoration and a new reconcile function to define how to act on it. The state is repeatedly created each time the reconcile function is triggered. During the restoration, a new database is always the target, and once completed, the resources to restore it are deleted, and only the PostgreSQL database is left. The performance of the modified operator impact compared to the original operator was measured to evaluate the operator. The tests consisted of operations both versions of the operator supported, including PostgreSQL database creation, cluster scaling, and changing resource limits. The two collected metrics, CPU- and memory usage, increased by 0.058-0.4 mvCPU (12-33%) and 8.2 MB (29%), respectively. A qualitative evaluation of the operator using qualities such as robustness, self-healing, customizability, and correctness showed that the design fulfils most of the qualities.

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