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Production AI Radar

Kubernetes for AI workloads

Running training and inference on shared K8s clusters with GPU scheduling.

AssessPlatform & DevEx
Why this ring
Right for platform-mature teams. Assess whether managed endpoints or serverless inference fit better first.
Production risk if ignored
GPU scheduling contention and noisy neighbors take down inference during peak load.
Typical effort
months
High FinOps impact

Use cases

  • Multi-model serving
  • Shared GPU pool
  • Platform engineering

Adoption steps

  1. TCO vs managed endpoints
  2. GPU quota per team
  3. KServe or custom serving
  4. FinOps labels day one

Related tools

In your assessment

Platform fit assessment + TCO comparison