Koordinator vs Slurm Workload Manager

Koordinator is a free, self-hosted QoS scheduling system for Kubernetes microservices, AI, big-data, audio, and video workloads. It adds priority and quality-of-service controls so different pods and workload types can share nodes. Application profiling supports resource overcommitment while preserving QoS guarantees, and fine-grained isolation targets latency-sensitive work alongside batch jobs. Customizable policies cover Web Service, Spark, Presto, TensorFlow, and PyTorch. QoSManager tunes pod isolation using profiling, interference detection, and SLO settings. Koord-Queue supports TFJob, PyTorchJob, Spark, Argo Workflow, Ray, and native Kubernetes Jobs, with Kueue AdmissionCheck compatibility. YARN Copilot connects Hadoop YARN jobs with Kubernetes pods. Koordinator works alongside kube-scheduler, using control-plane and node components without invasive native changes. Helm 3.5 or newer and Kubernetes 1.18 or newer are required.

Slurm Workload Manager is free, open-source software for allocating compute resources and scheduling work across Linux clusters. It starts and monitors jobs on allocated nodes and manages queues of pending work. Optional plugins add accounting, advanced reservations, gang and backfill scheduling, topology-aware resource selection, resource limits, and multifactor job prioritization. The system uses a central slurmctld manager and slurmd daemons on compute nodes; accounting and REST components are optional. GPU plugins support NVIDIA, AMD, Intel, AWS Trainium, and AWS Inferentia accelerators, along with NVIDIA MPS and GPU sharing. Accounting can use MySQL or MariaDB and can record data in a text file, directly in a database, or through slurmdbd for multiple clusters. Slurmrestd provides REST access, but the API is not designed for direct internet exposure and supports only unencrypted HTTP. Linux is thoroughly tested on arm64, ppc64, and x86_64; FreeBSD and NetBSD support is limited, and macOS is unsupported. Deployment is self-hosted.