Data sources
Seven source areas
The infrastructure signals WasteLens brings together to detect waste, quantify impact and identify optimization opportunities.
Cloud Cost & Usage
Understand where cloud spend is going and identify resources whose cost isn't matched by meaningful utilization.
Kubernetes & Container Usage
Analyze workloads, requests, limits and utilization to uncover inefficient container capacity.
GPU & Accelerator Telemetry
Identify under-utilized GPUs, idle accelerator capacity and opportunities to improve expensive compute utilization.
LLM & AI API Usage
Understand model usage, token consumption and request patterns to identify unnecessary or inefficient AI spend.
Infrastructure Telemetry
Analyze CPU, memory, storage, network and other infrastructure signals to find unused or inefficient capacity.
AI Workload & Job Data
Connect workload behavior with infrastructure consumption to understand where AI jobs are consuming more resources than necessary.
AI Model Recommendation
Go beyond infrastructure optimization. Identify opportunities to use a more appropriate model, capacity profile or workload configuration.