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Slinky

Self-Service Slurm Clusters on Kubernetes with Rafay GPU PaaS

In the previous blog, 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.

Design

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 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.

Project Slinky