[slurm-users] Slinky 1.2.0 released

[Marlow Warnicke via slurm-users]

We are pleased to announce the availability of Slinky version 1.2.0!

Slinky is SchedMD (now part of NVIDIA)'s set of components to integrate Slurm in Kubernetes environments. Slinky consists of two main projects, slurm-operator and slurm-bridge. Our landing page is here: https://www.slinky.ai

The slurm-operator handles cases where users wish to run Slurm jobs within the Kubernetes cluster.

Release v1.2.0:
https://github.com/SlinkyProject/slurm-operator/releases/tag/v1.2.0

New features include a ScheduledUpdate strategy for NodeSets to control when updates are applied, support for Google GKE A3 Mega instance types, and configurable pod security contexts for operator and webhook deployments.

The full changelog may be found here:
https://github.com/SlinkyProject/slurm-operator/blob/main/CHANGELOG/CHANGELOG-1.2.md


The slurm-bridge brings Kubernetes and Slurm jobs together under one scheduler. Both types of workloads share the same cluster resources.

Release v1.2.0:
https://github.com/SlinkyProject/slurm-bridge/releases/tag/v1.2.0

New features include support for LeaderWorkerSet workloads introduced in Kubernetes 1.37, priority annotations for workloads to control Slurm job scheduling order, and dynamic topology reconciliation for external and hybrid Slurm nodes.

The full changelog may be found here:
https://github.com/SlinkyProject/slurm-bridge/blob/main/CHANGELOG/CHANGELOG-1.2.md

#kubernetes #slurm #dra #ai #training #inference #hpc #nvidia #gpu #cloudnative #slinky

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