Karmada

Implement default resource interpreters for RayCluster and RayJob workloads in Karmada. Expected Outcome: This includes interpreter development, validation, and comprehensive documentation on deploying and managing Ray workloads with Karmada. Present the integration and usage guide to the KubeRay community.

Now Resource Interpreter framework enabled both built-in and customized interpreter, we are going to provide a way for people customize the interpreter by applying a configuration.

The Karmada dashboard has already implemented the management of resources in the control plane. Apart from that, we hope to implement the management of resources in the member cluster: once users add Kubernetes resources and the corresponding policy resources on the control plane, they can switch to the corresponding member cluster seamlessly, check the status of Kubernetes resources in the specific member cluster. Kubernetes dashboard is one of the most popular single-cluster management tools, which uses client-go sdk to communicate with the apiserver to manage resources in the cluster. A great deal of client-go related logic can be extended to muli-cluster easily, due to the karmada-aggregated-apiserver component and the compatibility design between Kubernetes resource and Karmada resoruces. So we hope to combine the Kubernetes dashboard with the karmada-aggregated-apiserver component to implement multi-cluster management in the Karmada dashboard. Expected Outcome: 1. Proposal for multi-cluster management base on karmada-aggregated-apiserver. 2. Tools to lift Kubernetes dashboard with specific version into Karmada dashboard repo, and implement management of resources in member cluster based on karmada-aggregated-apiserver. 3. Typical ui for member-cluster management: a. list/detail/delete/update action for deployment resources. b. log viewer for pod. c. web terminal for pod, which user can attach the running pod, and execute temporary commands.

Provide an automatic promotion mechanism for dependent resources in karmadactl. When promoting a resource, all the resources that it depends on will be automatically promoted as well. For example, promoting the Secret that is dependent by a Deployment. - Expected Outcome: - Technical Documentation: design description and analysis - Function Implementation: support promote the dependent resources automatically - Test coverage: add test cases to cover new functions

Karmada would like to improve the UT coverage of the code to better maintain the quality of the code and reduce the introduction of defects. Increase the UT coverage rate to 50% to 60% (currently, the UT coverage rate is [28.26%](https://app.codecov.io/gh/karmada-io/karmada) ). The entire Karmada repository is a bit large for one project, so we will split it into two projects. The current parts mainly target the `karmada-controller-manager` and `karmada-scheduler` components. Expected Outcome: - Increase the UT (Unit Test) coverage by more than 25% and add more than 4000 lines of code coverage in the following directories: pkg/controllers pkg/dependenciesdistributor pkg/descheduler pkg/detector pkg/estimator pkg/scheduler pkg/resourceinterpreter pkg/util