From a client perspective, the HPC scheduler runs as a service deployed in Kubernetes pods, operating just as it would on a bare metal cluster. Navops Command provides additional scheduling features including things like resource reservation, run-time quotas, workload preemption and more. This environment works equally well for on-premise, cloud-based or hybrid deployments.

## Deploying mixed workloads at IHME

One client having success with mixed workloads is the Institute for Health Metrics & Evaluation (IHME), an independent health research center at the University of Washington. In support of their globally recognized Global Health Data Exchange (GHDx), IHME operates a significantly sized environment comprised of 500 nodes and 20,000 cores running a mix of analytic, HPC, and container-based applications on Kubernetes. [This case study](http://navops.io/ihme-case-study.html) describes IHME’s success hosting existing HPC workloads on a shared Kubernetes cluster using Navops Command.

 ![](https://lh5.googleusercontent.com/GJeP6e89r6drl72yzZM_OsZ81MYDp7Zm5xEFpItpmioian3lOp535H4jy1_eELKrzGMYr_wnjGwpK3Uku9dwg2-vqmMC1A1GrMtJc-PZR6GR6Z-fAZNJMEr_Uw3HqvWvi86mF_63XTozysaLpg)

For sites deploying new clusters that want access to the rich capabilities in Kubernetes but need the flexibility to run non-containerized workloads, this approach is worth a look. It offers the opportunity for sites to share infrastructure between Kubernetes and HPC workloads without disrupting existing applications and businesses processes. It also allows them to migrate their HPC workloads to use Docker containers at their own pace.