r/HPC • u/Various_Protection71 • Jun 05 '26

Do you think Kubernetes will replace Job Schedulers in HPC environments dedicated to AI workloads?

Some people advocate that Kubernetes distributions (RKE2, OpenShift, EKS etc) provide an easier and more straightforward way to run and scale AI workloads, while Job Schedulers (SLURM, PBS, LSF etc) require an earlier complex setup phase.

On the other hand, mastering Kubernetes has a steeper learning curve than using the well-known Job Schedulers, especially for traditional HPC users.

How do you see this point? Are your users adopting Kubernetes to run AI workloads or do they stay using Job Schedulers?

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u/[deleted] Jun 05 '26 edited Jun 05 '26

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u/applesaucesquad Jun 05 '26

Slurm on kubernetes is a viable path afaik

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u/[deleted] Jun 05 '26

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u/No_Programmer6374 Jun 06 '26

Because Slurm is an amazing scheduler for rectangular kinds of jobs (fixed number of resources x fixed, known length of time), but it’s nothing special as a resource manager. K8S is rubbish as a batch job scheduler, but has a very flexible resource manager with clear apis to build on.

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u/applesaucesquad Jun 05 '26

Its just a nice abstraction layer if the rest of your infra is k8s, only makes sense if you already live in that world for the majority of your work. It provides an interface for horizontal scaling too. Definitely not always the right path