Automated AI / GPU Infrastructure Optimization
Maximize the yield from expensive GPUs.
SREs, Platform Owners and FinOps teams
are succeeding and saving $millions.
GPU Resource Request Optimization
Right-size GPU workloads to eliminate waste and improve performance.
- Recommends optimal GPU allocation for each workload
- Prevents over-requesting and reduces GPU node sprawl
- Continuously adapts to changing model and pipeline behavior
Optimized GPU Model Selection
Match workloads with the ideal GPU type for peak efficiency.
- Analyzes compute, memory, and throughput needs to choose the right GPU
- Avoids running light workloads on expensive high-end GPUs
- Balances performance and cost across diverse AI pipelines
NVIDIA MIG Planning
Maximize GPU density with intelligent MIG partitioning.
- Recommends ideal MIG profiles based on workload demand
- Improves cluster utilization by packing workloads efficiently
- Ensures reliable performance across multi-tenant clusters
GPU Utilization, Memory & Power Tracking
Get deep visibility into every GPU for maximum efficiency.
- Provides real-time metrics across utilization, memory consumption, and power draw
- Continuously detects idle or under-utilized GPUs
- Reveals hidden gaps in GPU usage and workload
The result:
-
60 %
Higher GPU utilization
-
50 %
Cost savings
-
0
Zero guesswork
See the benefits of optimized
Kubernetes Resources
AI-driven analytics that precisely determine optimal resource settings for Kubernetes.
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