Kubernetes has become a standard in the industry for deploying micro-service applications. One area that provides challenges is running batch workloads on top of Kubernetes. Batch workloads consist of finite lifetime computations such as AI or scientific computing workflows. These workloads can consist of extensive resource requirements such as high memory, CPU and/or GPU requirements. Various Cloud Native Computing Foundation (CNCF) projects have been founded for running batch workflows (Argo Workflows, Volcano, Kubeflow, etc) but there is a significant limitation in that they do not support multi cluster. In this talk, we propose an open source application for running batch workloads across multiple Kubernetes instances.