AI infrastructure
Pedal to Bare-Metal Kubernetes, Nutanix Forges NKP Metal
Nutanix extends its Cloud Platform to bare-metal infrastructure with NKP Metal. Learn how dual-native architecture simplifies Kubernetes for AI and edge workloads without sacrificing the Nutanix operating model ...
Adrian Bridgwater | | AI infrastructure, B-MK8S, bare-metal Kubernetes, Cloud Native AOS, container storage interface, Dual-Native Architecture, edge computing, GPU workloads, HCI, hybrid cloud, Kubernetes lifecycle management, Nutanix AHV, Nutanix AOS, Nutanix Kubernetes Platform, Nutanix NKP Metal
How AI is Transforming Cloud‑Native Operations
AI is transforming cloud-native operations with predictive scaling, AIOps and automation to improve performance, efficiency and resilience ...
Istio Weaves ‘Future-Ready’ Service Mesh for AI
At KubeCon + CNC 2026, Istio unveils Ambient Multicluster and the Gateway API Inference Extension to simplify AI infrastructure. Learn how sidecar-less mesh and agentgateway secure agentic workloads and boost deployment velocity ...
Adrian Bridgwater | | agentgateway, AI infrastructure, AI Workloads, Ambient Multi-cluster, cloud native, cncf, data plane, Gateway API Inference Extension, generative AI, Istio, KubeCon 2026, kubernetes, microservices, Node Proxy, observability, platform engineering, service mesh, Sidecar-less Mesh, traffic management, Waypoint Proxy
Google Extends Kubernetes Service to Safely Run Agentic AI Workloads
At KubeCon + CloudNativeCon North America 2025, Google unveiled major GKE upgrades — including an AI sandbox, inference gateway, pod snapshots, and 130,000-node clusters — to optimize and secure agentic AI workloads ...
CNCF Adds Program to Standardize AI Workloads on Kubernetes Clusters
CNCF introduces the Certified Kubernetes AI Conformance Program to standardize AI and ML workload deployment, ensuring interoperability and sovereign cloud compliance ...
Mike Vizard | | AI deployment, AI infrastructure, AI on Kubernetes, AI portability, AI scalability, AI Workloads, Certified Kubernetes AI Conformance Program, cloud native AI, cloud-native ecosystem, CloudNativeCon, cncf, data science, hybrid cloud, IT operations, KubeCon 2025, kubernetes, Kubernetes certification, Kubernetes conformance, Kubernetes interoperability, Kubernetes standards, ML deployment, ML frameworks, ML workloads, sovereign cloud
Why Agentic SREs Require Active Telemetry in Kubernetes
Discover how Active Telemetry enables Agentic SREs to move from reactive firefighting to autonomous diagnosis and proactive reliability in Kubernetes ...
Tucker Callaway | | Active Telemetry, Active Telemetry pipeline, Agentic SRE, AI infrastructure, AI observability, AI-driven SRE, autonomous diagnosis, autonomous operations, cloud native operations, context engineering, data context, intelligent observability, KubeCon 2025, Kubernetes reliability, MTTR reduction, operational autonomy, proactive remediation, root cause analysis, site reliability engineering, telemetry architecture
Why Traditional Kubernetes Security Falls Short for AI Workloads
AI workloads on Kubernetes bring new security risks. Learn five principles—zero trust, observability, and policy-as-code—to protect distributed AI pipelines ...
Ratan Tipirneni | | AI infrastructure, AI security, AI Workloads, cloud native AI, cloud native security, container security, data protection, DevSecOps, edge AI, GPU workloads, KubeCon 2025, kubernetes, Kubernetes observability, Kubernetes security, microsegmentation, multi-cluster security, policy as code, runtime protection, Spectro Cloud report, zero-trust
Fitting Square Kubernetes Into the Round AI-Native Apps
Kubernetes tamed cloud-native workloads, but AI-native apps push its limits. Can it evolve for GPU-first, data-intensive AI — or is it time for new control planes? ...
Alan Shimel | | AI control plane, AI infrastructure, AI pipelines Kubernetes, AI-native applications, cloud-native vs AI-native, container orchestration AI, distributed training orchestration, GPU scheduling, inference at scale, internal developer platforms, Kubeflow, KubeRay, kubernetes, Kubernetes AI workloads, Kubernetes future, Kubernetes limitations, Kubernetes vs AI, platform engineering, Ray on Kubernetes, Volcano scheduler

