ML Cost Management
← Back to ML Infrastructure
Controlling the high costs of ML compute. Strategies include spot/preemptible instances (60-90% cheaper), auto-scaling (scale down when idle), right-sizing GPU instances (match GPU to workload), and monitoring utilization.
Related
- GPU Management (optimize GPU utilization)
- ML Platforms (platform cost controls)