## From Slurm to Kubernetes: A Guide for HPC Users

If you've spent years submitting batch jobs with Slurm, moving to a Kubernetes-based cluster can feel like learning a new language. The concepts are familiar — resource requests, job queues, priorities — but the vocabulary and tooling are different. This guide bridges that gap, helping HPC veterans understand how Kubernetes handles workloads and what that means day-to-day.

## Self-Service Slurm Clusters on Kubernetes with Rafay GPU PaaS

In the previous [**blog**](https://docs.rafay.co/blog/2025/06/19/project-slinky-bringing-slurm-scheduling-to-kubernetes/), we discussed how Project Slinky bridges the gap between Slurm, the de facto job scheduler in HPC, and Kubernetes, the standard for modern container orchestration.

Project Slinky and Rafay’s GPU Platform-as-a-Service (PaaS) combined provide enterprises and cloud providers with a transformative combination that enables secure, multi-tenant, self-service access to Slurm-based HPC environments on shared Kubernetes clusters. Together, they allow cloud providers and enterprise platform teams to offer Slurm-as-a-Service on Kubernetes—without compromising on performance, usability, or control.

## Project Slinky: Bringing Slurm Scheduling to Kubernetes

As high-performance computing (HPC) environments evolve, there’s an increasing demand to bridge the gap between traditional HPC job schedulers and modern cloud-native infrastructure. [**Project Slinky**](https://github.com/SlinkyProject) is an open-source project that integrates Slurm, the industry-standard workload manager for HPC, with Kubernetes, the de facto orchestration platform for containers.

This enables organizations to deploy and operate Slurm-based workloads on Kubernetes clusters allowing them to leverage the best of both worlds: Slurm’s mature, job-centric HPC scheduling model and Kubernetes’s scalable, cloud-native runtime environment.

## Introduction to Slurm-The Backbone of HPC

This is part-1 in a blog series on [**Slurm**](https://slurm.schedmd.com/documentation.html). In the first part, we will provide some introductory concepts about Slurm. We are not talking about the fictional soft drink in the world of [Futurama](https://en.wikipedia.org/wiki/Futurama). Instead, this blog is about Slurm (Simple Linux Utility for Resource Management), an open-source, fault-tolerant, and highly scalable **cluster management** job scheduler and resource manager used in high-performance computing (HPC) environments.

Slurm was originally conceptualized in 2002 at [Lawrence Livermore National Laboratory](https://www.llnl.gov/) (LLNL) and has been actively developed and maintained especially by [SchedMD](https://www.schedmd.com/). In this time, Slurm has become the defacto workload manager for HPC with >50% of the Top-500 super computers using it.