Trainy
Run your GPUs like a frontier lab
Trainy is a platform for running AI training and inference workloads across GPU clusters. It addresses the operational burden of scheduling distributed jobs, handling hardware failures, and tracking experiments at scale. Jobs are defined in a YAML file and launched with a single CLI command, with support for multi-cloud queuing, health checks, and observability.
The platform includes Konduktor for GPU cluster scheduling and management, with priority scheduling, preemption, RDMA-native multi-node training, and health checks that detect failing GPUs and reschedule jobs automatically. It deploys into your own VPC across AWS, GCP, Azure, and bare metal, with observability via Prometheus, Grafana, and logs. Konduktor also handles inference endpoints with autoscaling and load balancing. Pluto is the open-source experiment tracking module, compatible with W&B and Neptune APIs, offering dual-logging, MCP integration, and a responsive UI for large run counts.
Trainy is aimed at AI teams managing distributed training infrastructure. Konduktor is priced via a custom quote based on cluster size, with a platform fee plus per-node pricing. Pluto offers a free hosted tier with limited seats and storage, a seat-based Pro tier, and free self-hosting; academics with a .edu email receive free access, and an enterprise tier is available for larger teams.
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