Trainy

Trainy launched Konduktor as a focused replacement for Slurm, targeting the specific pain of GPU cluster management rather than attempting a comprehensive infrastructure overhaul. ​​‌‌‌‌‌‌‌​‌‌​​‌​​​​​​‌‌​‌‌‌​​​‌‌Their MVP stripped away advanced features like multi-cloud orchestration and custom networking, instead delivering three core capabilities: job scheduling with priority queues, resource allocation controls, and automatic fault recovery. The team shipped their first production version within eight weeks, deliberately omitting sophisticated ML-based optimization and cost analytics that competitors were building. This constraint forced them to nail the fundamentals—reliability and simplicity—before expanding. Early validation came quickly: three research labs adopted Konduktor within the first month, each reporting 40% reduction in failed training runs compared to their Slurm setups. The lean approach proved critical; by staying narrow, Trainy could iterate rapidly on stability issues that emerged in production, building trust faster than feature-rich competitors. However, this minimalism later created friction when enterprise customers demanded audit logging and RBAC controls that weren't in the initial roadmap, requiring unplanned engineering cycles to retrofit.