This project provides a framework that runs Slurm in Kubernetes.
This project deploys Slurm on Kubernetes. These pods coexist with other running workloads on Kubernetes. This project provides controls over the Slurm cluster configuration and deployment, along with configurable autoscaling policy for Slurm compute nodes.
This project allows for much of the functionality within Slurm for workload management. This includes:
- Priority scheduling: Determine job execution order based on priorities and weights such as age
- Fair share: Resources are distributed equitably among users based on historical usage.
- Quality of Service (QoS): set of policies, such as limits of resources, priorities, and preemption and backfilling.
- Job accounting: Information for every job and job step executed
- Job dependencies: Allow users to specify relationships between jobs, from start, succeed, fail, or a particular state.
- Workflows with partitioning: Divide cluster resource into sections for job management
To best enable Slurm in Kubernetes, the project uses Custom Resources (CRs) and an Operator to extend Kubernetes with custom behaviors for Slurm clusters. In addition, Helm is used for managing the deployment of the various components of this project to Kubernetes.
Slurm 24.05 Data parsers v40, v41
See the Quickstart Guide to install.
This is a basic architecture. A more in depth description can be found in the docs directory
- CGroups is currently disabled, due to difficulties getting core information into the pods.
- Updates may be slow, due to needing to wait for sequencing before the slurm-controller can be deployed.
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Licensed under the Apache License, Version 2.0 you may not use project except in compliance with the license.
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