New in Together GPU Clusters: Autoscaling, observability, and self-healing
Together AI
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Together AI introduced autoscaling, role-based access control, observability dashboards, and self-healing capabilities to its GPU Clusters platform. The autoscaling feature uses Kubernetes to automatically add or remove GPU nodes based on demand, while health checks and self-repair can restore failed nodes within minutes. These production-grade features enable teams to run large distributed training jobs and inference workloads without manual infrastructure management or losing compute time to hardware failures.
Why it matters
Together GPU Clusters now include built-in autoscaling, RBAC, full-stack observability, and self-healing node repair—giving teams production-ready GPU infrastructure that scales efficiently, stays resilient, and supports shared enterprise workloads.
