New in Together GPU Clusters: Reliability and control for production GPU clusters

Recent updates to Together GPU Clusters focus on enhancing platform health and operational control to better manage large-scale training and inference workloads. The improvements include passive health checks and auto node repair to address hardware failures, alongside new operational control features like a detailed cluster view, external OIDC for Kubernetes RBAC, and startup scripts for customization. These changes aim to reduce downtime and support tickets by providing real-time detection and resolution of issues, improving cluster reliability and resilience. Additionally, Together Slurm-on-K8s 2.0 offers a revamped stack for running Slurm on Kubernetes, ensuring self-healing worker daemons, durable job accounting, and accurate GPU state management. The updates also introduce acceptance testing for larger clusters and emphasize customization and access control, providing operators with a more intuitive and efficient management experience. As Together continues to develop its platform, it seeks user feedback to further enhance its offerings.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.