KubeCon 2026 Inference Shift: A Platform Playbook for Dapr Agents and Kubernetes AI Runtime
How to prepare Kubernetes platforms for inference-heavy workloads with durable agent orchestration, GPU scheduling, and reliability guardrails.
How to prepare Kubernetes platforms for inference-heavy workloads with durable agent orchestration, GPU scheduling, and reliability guardrails.
Reports of major compression advances renew the quantization race. Here is a practical path to ship lower-cost inference without quality collapse.
A practical architecture for deploying low-latency small voice models at the edge with observability, fallback strategy, and cost discipline.
Large defense AI procurement deals demand modern software assurance, from secure MLOps baselines to reproducible model governance and audit-ready delivery.
Why teams need reproducible model-to-hardware routing policies as local inference and heterogeneous fleets expand.
A practical framework for governments and regulated enterprises evaluating domestic AI models for broad internal deployment.