Jump Capital
AI workloads are breaking Kubernetes' core assumptions around statelessness and interchangeable compute, creating opportunities in inference observability, KV-cache orchestration, and GPU scheduling—three infrastructure gaps the author is tracking at KubeCon 2026.
Topics: AI Infrastructure · Developer Tools
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