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GKE Adds Confidential Nodes With Intel TDX Support
Learn how GKE Confidential Nodes with Intel TDX protect data in use and how to apply confidential computing to selected Kubernetes workloads.
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Tutorials, how-tos and deep dives on AI, .NET, C#, cloud and developer tools, written by the community.
Learn how GKE Confidential Nodes with Intel TDX protect data in use and how to apply confidential computing to selected Kubernetes workloads.
Learn how GKE lets Kubernetes HPA use PromQL queries from Managed Service for Prometheus to scale workloads using application-specific demand metrics.
Learn how GKE scale-to-zero reduces idle Kubernetes workload costs, how workloads wake from zero, and which applications are suitable for cold-start scaling.
Learn how GKE lets Kubernetes Horizontal Pod Autoscaler use PromQL queries to scale workloads based on Prometheus application metrics such as request rate and queue depth.
Learn how Actions Runner Controller 0.15 uses runner scale sets to run and scale GitHub Actions self-hosted runners on Kubernetes, including Helm deployment and resource planning.
Learn how GKE CPU startup boost temporarily adds CPU during Pod initialization to reduce startup latency without permanently over-provisioning resources.
Learn how to find unused Kubernetes PVCs safely, check pod and StatefulSet references, inspect PVs and reclaim policies, and avoid accidental data loss.
Learn how to test Kubernetes 1.37 CPU and memory requests, limits, throttling, OOM conditions, QoS classes, and workload resource usage safely.
Learn Kubernetes 1.37 storage security with bind mounts, hostPath, permissions, and read-only access. Follow these practices to secure node storage.
Learn how to secure Kubernetes 1.37 emptyDir permissions with non-root containers, fsGroup, and least-privilege access. Apply safer storage practices.
Learn how to check Pod and container CPU and memory resources in Kubernetes 1.37 using kubectl, inspect requests, limits, usage, nodes, events, and OOM issues.
Learn how Kubernetes Changed Block Tracking works with CSI snapshots to identify changed blocks, reduce incremental backup data, and improve large-volume backup workflows.
Learn how to test .NET 11 Native AOT performance by comparing startup, memory, CPU, throughput, binary size, compatibility, and build time with JIT deployment.
Understand Kubernetes 1.37 Pod-level resources and Memory QoS, including memory requests, limits, QoS classes, node pressure, and OOM troubleshooting.
Learn how Foundry Local on Azure Local uses Kubernetes service accounts for secure in-cluster AI inference, authentication, and workload access.
Learn how Kubernetes 1.37 native histograms improve Prometheus latency metrics while supporting existing dashboards and observability workflows.
Explore Kubernetes 1.37 in-place Pod resizing and how scheduler preemption handles CPU and memory shortages to improve resource management and workload scheduling.
Learn how Kubernetes Gateway API XBackend enables routing to AI and external services without traditional Service objects, with practical architecture considerations.
Learn how Kubernetes 1.37 Dynamic Resource Allocation enables GPU workloads without traditional device plugins, including resource management and AI workload scheduling.
Learn how Kubernetes 1.37 workload-aware scheduling can improve placement of AI and batch workloads by considering workload requirements, resources, and scheduling behavior.
Learn how Kubernetes 1.37 supports running Kubelet without root privileges and understand the security considerations, configuration requirements, and operational limitations.
Learn what to check before Kubernetes storage version migration, including API compatibility, stored resources, migration planning, validation, and upgrade risks.
Learn how Kubernetes 1.37 etcd RangeStream can affect API server memory usage, with an overview of streaming behavior, resource efficiency, and performance considerations.
Learn how Kubernetes 1.37 node lifecycle conditions can improve node maintenance by helping controllers and workloads respond safely to node health and availability changes.
Explore Kubernetes 1.37 Memory QoS and learn how it improves .NET container performance, memory isolation, resource management, and application stability under pressure.
Learn how to migrate .NET application monitoring to the Kubernetes 1.37 metrics.k8s.io API, covering resource metrics, monitoring architecture, compatibility, and migration steps.
Explore Kubernetes 1.37 gang scheduling for distributed AI workloads and learn how coordinated pod scheduling can improve resource utilization, startup behavior, and performance.
Learn how Kubernetes 1.37 KYAML can help validate and process Kubernetes manifests in CI/CD pipelines, improving configuration quality, automation, and deployment reliability.
Learn how to migrate .NET application monitoring to the Kubernetes 1.37 metrics.k8s.io API, covering resource metrics, monitoring architecture, compatibility, and migration steps.
Learn how Kubernetes 1.37 Pod Certificates can secure .NET services with workload identity, automated certificate management, authentication, and service-to-service security.
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