Running Mixed Workloads on Kubernetes at the Institute for Health Metrics and Evaluation

The mission of the IHME is to apply rigorous measurement and analysis to help policy makers make better decisions on a range of health policy issues. Like other organizations, the IHME have embraced c …

The mission of the IHME is to apply rigorous measurement and analysis to help policy makers make better decisions on a range of health policy issues. Like other organizations, the IHME have embraced containers and micro-services aggressively to better support hundreds of collaborating researchers. In addition to containerized workloads, the IHME run a wide-variety of traditional analytic, simulation and high-performance computing workloads on an HPC cluster with 15,000 cores and 13PB of storage. Researchers increasingly need to combine both containerized and non-containerized elements into workflow pipelines, and a key challenge has been ensuring SLAs for various departments and avoiding duplicate infrastructure and unnecessary data movement and duplication. In collaboration with industry partners, IHME have deployed a unique solution based on Univa’s Navops technology that allows them to combine containerized and traditional analytic and high-performance application workloads on a single shared Kubernetes cluster, ensuring departmental SLAs and helping contain infrastructure costs. In this talk Dr. Grandison will discuss IHME, their experience deploying containerized applications and how they went about using Kubernetes to support a variety of new containerized applications as well as a variety of traditional analytic applications.