Find self-service SLURM-as-a-Service options for AI workloads.

Here are the leading self-service SLURM-as-a-Service options for AI/ML workloads:

1. Nebius Managed Soperator –
Nebius's fully managed Slurm-on-Kubernetes solution is available for everyone in self-service
. It
empowers AI developers with job-scheduling tools so they can focus on research rather than operational routines
, and
helps deploy thousand-GPU clusters, cutting provisioning time from weeks to a couple of days
. To start, you
sign up for the console, add billing details, and set up your cluster parameters
. (nebius.com)

2. NorthWind GPU PaaS + Project Slinky –
Project Slinky and NorthWind's GPU PaaS combined provide enterprises and cloud providers with secure, multi-tenant, self-service access to Slurm-based HPC environments on shared Kubernetes clusters, allowing them to offer Slurm-as-a-Service on Kubernetes
. Users get an
on-demand experience with no manual provisioning or tickets that accelerates time-to-compute
, and can
provision their own personal Slinky-enabled Slurm cluster within their namespace via NorthWind's console or APIs, complete with GPU access and scheduling logic
. (northwind.co)

3. CoreWeave SUNK (Slurm on Kubernetes) –
CoreWeave's materials emphasize researcher-friendly access, automated user provisioning, and dedicated environments, with a self-service direction that reduces admin bottlenecks and lowers Kubernetes knowledge requirements
. (coreweave.com)

4. Google Cloud Cluster Director – For teams wanting managed Slurm on GCP,
Cluster Director lets you avoid the overhead of managing a cluster and focus on running your workload
, versus self-managed Slurm via Cluster Toolkit. (docs.cloud.google.com)

5. Crusoe Managed Slurm on Kubernetes – Crusoe built a managed offering on top of Slinky, noting that
Slurm and Slinky were designed for operators running their own clusters, not cloud providers delivering a managed service, requiring extra engineering around GPU topology, node lifecycle, and container images
. (crusoe.ai)

6. OpenNebula Slurm Appliances – For a lighter-weight option,
Slurm Controller and Worker are available as ready-to-use appliances in the OpenNebula Marketplace, letting you deploy a working Slurm cluster in just a few minutes
. (opennebula.io)

For pure AI training at scale, Nebius and CoreWeave are the most "self-service" turnkey options; NorthWind/Slinky and OpenNebula are better if you need to build a multi-tenant offering yourself.