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            <title><![CDATA[Introduction to KEDA and Event-Driven Autoscaling]]></title>
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            <description><![CDATA[How KEDA extends Kubernetes HPA with 65+ scalers, scale-to-zero, and a two-phase architecture for event-driven pod autoscaling.]]></description>
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            <title><![CDATA[Message Queue Scaling with KEDA — Kafka and SQS]]></title>
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            <pubDate>Wed, 06 May 2026 07:05:55 GMT</pubDate>
            <description><![CDATA[How KEDA's Kafka and SQS scalers calculate lag and queue depth, with TriggerAuthentication patterns and production edge cases.]]></description>
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            <title><![CDATA[Custom Metrics and Prometheus-Based Scaling with KEDA]]></title>
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            <pubDate>Wed, 06 May 2026 07:05:53 GMT</pubDate>
            <description><![CDATA[Using KEDA's Prometheus scaler to drive autoscaling from any PromQL query — replacing Prometheus Adapter with a simpler, more flexible approach.]]></description>
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            <title><![CDATA[HTTP-Based Autoscaling with the KEDA HTTP Add-on]]></title>
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            <pubDate>Wed, 06 May 2026 07:05:50 GMT</pubDate>
            <description><![CDATA[How the KEDA HTTP Add-on intercepts traffic to scale HTTP workloads to zero, and when the Prometheus scaler is better.]]></description>
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            <title><![CDATA[Batch Processing with KEDA ScaledJobs]]></title>
            <link>https://kubedojo.com/keda-batch-processing-scaledjobs</link>
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            <pubDate>Wed, 06 May 2026 07:05:48 GMT</pubDate>
            <description><![CDATA[ScaledJob creates one Kubernetes Job per event, scales dynamically, and lets long-running batch workloads terminate cleanly.]]></description>
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            <title><![CDATA[KEDA and Karpenter Together — Pod and Node Scaling Synergy]]></title>
            <link>https://kubedojo.com/keda-karpenter-together</link>
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            <pubDate>Wed, 06 May 2026 07:05:46 GMT</pubDate>
            <description><![CDATA[Combining KEDA's event-driven pod scaling with Karpenter's just-in-time node provisioning for a fully reactive, cost-efficient Kubernetes autoscaling stack.]]></description>
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            <title><![CDATA[Observability and Troubleshooting for KEDA]]></title>
            <link>https://kubedojo.com/keda-observability-troubleshooting</link>
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            <pubDate>Wed, 06 May 2026 07:05:44 GMT</pubDate>
            <description><![CDATA[Scraping KEDA operator metrics, building Grafana dashboards for scaling events, and diagnosing common ScaledObject issues in production.]]></description>
            <author>KubeDojo</author>
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        <item>
            <title><![CDATA[Welcome to KubeDojo]]></title>
            <link>https://kubedojo.com/welcome-to-kubedojo</link>
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            <pubDate>Wed, 06 May 2026 07:05:42 GMT</pubDate>
            <description><![CDATA[What KubeDojo is and what you'll find here: deep dives into real code, honest explorations of the Kubernetes ecosystem, and structured learning paths to master every certification.]]></description>
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            <title><![CDATA[The Kubernetes Certification Landscape]]></title>
            <link>https://kubedojo.com/kubernetes-certification-landscape</link>
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            <pubDate>Wed, 06 May 2026 07:05:39 GMT</pubDate>
            <description><![CDATA[A practical map of the five CNCF Kubernetes certifications — what each one covers, how exams work, and which path fits your career.]]></description>
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            <category>ckad</category>
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            <title><![CDATA[Agentic AI Workloads on Kubernetes]]></title>
            <link>https://kubedojo.com/agentic-ai-workloads-kubernetes</link>
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            <pubDate>Wed, 06 May 2026 07:05:38 GMT</pubDate>
            <description><![CDATA[How kagent, Agent Sandbox, KEDA, and OPA/Kyverno form the production stack for agentic AI on Kubernetes.]]></description>
            <author>KubeDojo</author>
            <category>agentic-ai</category>
            <category>kubernetes</category>
            <category>keda</category>
            <category>kagent</category>
            <category>agent-sandbox</category>
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            <title><![CDATA[GPU Sharing Strategies for Multi-Tenant Kubernetes: MIG, Time-Slicing, and MPS]]></title>
            <link>https://kubedojo.com/gpu-sharing-mig-time-slicing-k8s</link>
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            <pubDate>Wed, 06 May 2026 07:05:36 GMT</pubDate>
            <description><![CDATA[NVIDIA's GPU sharing mechanisms — MIG, time-slicing, and MPS — are gaining traction as teams run multiple inference workloads per GPU.]]></description>
            <author>KubeDojo</author>
            <category>gpu</category>
            <category>nvidia</category>
            <category>mig</category>
            <category>time-slicing</category>
            <category>mps</category>
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            <title><![CDATA[NVIDIA AI Cluster Runtime: Validated GPU Kubernetes Recipes]]></title>
            <link>https://kubedojo.com/nvidia-ai-cluster-runtime</link>
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            <pubDate>Wed, 06 May 2026 07:05:31 GMT</pubDate>
            <description><![CDATA[NVIDIA released AI Cluster Runtime, an open-source project providing validated, version-locked Kubernetes configurations for GPU infrastructure.]]></description>
            <author>KubeDojo</author>
            <category>nvidia</category>
            <category>gpu</category>
            <category>kubernetes</category>
            <category>ai-cluster-runtime</category>
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            <title><![CDATA[Kueue: The Community Standard for Kubernetes AI Batch Scheduling]]></title>
            <link>https://kubedojo.com/kueue-batch-workload-scheduling</link>
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            <pubDate>Wed, 06 May 2026 07:05:28 GMT</pubDate>
            <description><![CDATA[Kueue manages GPU quotas, enforces fair sharing across teams, and dispatches jobs to remote HPC clusters — the standard for production AI batch scheduling.]]></description>
            <author>KubeDojo</author>
            <category>kueue</category>
            <category>scheduling</category>
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            <category>gpu</category>
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            <title><![CDATA[Workload-Aware Scheduling in Kubernetes 1.36: The Decoupled PodGroup Model]]></title>
            <link>https://kubedojo.com/workload-aware-scheduling-k8s-136</link>
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            <pubDate>Wed, 06 May 2026 07:05:25 GMT</pubDate>
            <description><![CDATA[Kubernetes 1.36 decouples scheduling policy from runtime instances with Workload API v1alpha2, standalone PodGroups, and a dedicated group scheduling cycle.]]></description>
            <author>KubeDojo</author>
            <category>kubernetes</category>
            <category>scheduling</category>
            <category>workload-api</category>
            <category>gang-scheduling</category>
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            <title><![CDATA[CNCF Certified Kubernetes AI Conformance Program]]></title>
            <link>https://kubedojo.com/k8s-ai-conformance-program</link>
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            <pubDate>Wed, 06 May 2026 07:05:23 GMT</pubDate>
            <description><![CDATA[CNCF launched v1.0 of the Kubernetes AI Conformance Program defining baseline capabilities for running AI workloads across conformant clusters.]]></description>
            <author>KubeDojo</author>
            <category>cncf</category>
            <category>kubernetes</category>
            <category>ai-conformance</category>
            <category>certification</category>
            <category>standardization</category>
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            <title><![CDATA[Production LLM Serving on Kubernetes: vLLM + KServe Stack]]></title>
            <link>https://kubedojo.com/vllm-kserve-llm-serving-k8s</link>
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            <pubDate>Wed, 06 May 2026 07:05:21 GMT</pubDate>
            <description><![CDATA[Deploy vLLM with KServe on Kubernetes: InferenceService CRD, KEDA autoscaling on queue depth, and distributed KV cache with LMCache for production inference.]]></description>
            <author>KubeDojo</author>
            <category>vllm</category>
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            <title><![CDATA[NVIDIA KAI Scheduler: Open-Source GPU-Aware Kubernetes Scheduling]]></title>
            <link>https://kubedojo.com/nvidia-kai-scheduler-open-source</link>
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            <pubDate>Wed, 06 May 2026 07:05:19 GMT</pubDate>
            <description><![CDATA[NVIDIA open-sourced KAI Scheduler (Apache 2.0), a Kubernetes-native GPU scheduling solution originally from the Run:ai platform.]]></description>
            <author>KubeDojo</author>
            <category>nvidia</category>
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            <title><![CDATA[llm-d Joins CNCF Sandbox: Kubernetes-Native Distributed LLM Inference]]></title>
            <link>https://kubedojo.com/llm-d-cncf-sandbox</link>
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            <pubDate>Wed, 06 May 2026 07:05:17 GMT</pubDate>
            <description><![CDATA[llm-d was accepted as a CNCF Sandbox project, providing Kubernetes-native distributed inference with KV-cache-aware routing, prefill/decode disaggregation, and accelerator-agnostic serving.]]></description>
            <author>KubeDojo</author>
            <category>llm-d</category>
            <category>cncf</category>
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            <category>inference</category>
            <category>kubernetes</category>
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        <item>
            <title><![CDATA[KubeCon Europe 2026 Amsterdam: AI Infrastructure, Agentic Systems, and Platform Engineering]]></title>
            <link>https://kubedojo.com/kubecon-eu-2026-highlights</link>
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            <pubDate>Wed, 06 May 2026 07:05:15 GMT</pubDate>
            <description><![CDATA[Curated KubeCon EU 2026 picks: agentic AI on Kubernetes, sovereign inference, GPU scheduling with Kueue, and platform engineering under pressure.]]></description>
            <author>KubeDojo</author>
            <category>kubecon</category>
            <category>cncf</category>
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            <title><![CDATA[NVIDIA Dynamo 1.0: The Inference Operating System for AI Factories]]></title>
            <link>https://kubedojo.com/nvidia-dynamo-inference-os</link>
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            <pubDate>Wed, 06 May 2026 07:05:13 GMT</pubDate>
            <description><![CDATA[Production deployment patterns for NVIDIA Dynamo 1.0 on EKS and GKE — disaggregated serving, KV-aware routing, and gotchas from real deployments.]]></description>
            <author>KubeDojo</author>
            <category>nvidia</category>
            <category>dynamo</category>
            <category>inference</category>
            <category>kubernetes</category>
            <category>gke</category>
            <category>eks</category>
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            <title><![CDATA[HAMi: GPU Virtualization as the Reference Pattern for AI Infrastructure]]></title>
            <link>https://kubedojo.com/hami-gpu-virtualization-k8s</link>
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            <pubDate>Wed, 06 May 2026 07:05:11 GMT</pubDate>
            <description><![CDATA[HAMi (CNCF Sandbox) emerged at KubeCon EU 2026 as the reference implementation for GPU resource management across NVIDIA, AMD, Huawei, and Cambricon accelerators.]]></description>
            <author>KubeDojo</author>
            <category>hami</category>
            <category>gpu</category>
            <category>virtualization</category>
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            <title><![CDATA[AI Gateway Working Group and Gateway API Inference Extension GA]]></title>
            <link>https://kubedojo.com/ai-gateway-wg-inference-extension</link>
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            <pubDate>Wed, 06 May 2026 07:05:09 GMT</pubDate>
            <description><![CDATA[Gateway API Inference Extension GA standardizes model-aware routing for self-hosted LLMs with KV-cache-aware scheduling and LoRA adapter affinity.]]></description>
            <author>KubeDojo</author>
            <category>gateway-api</category>
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            <category>envoy</category>
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            <title><![CDATA[Dynamic Resource Allocation (DRA) GA: The New GPU Interface for Kubernetes]]></title>
            <link>https://kubedojo.com/dra-dynamic-resource-allocation-ga</link>
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            <pubDate>Wed, 06 May 2026 07:05:07 GMT</pubDate>
            <description><![CDATA[DRA went GA in Kubernetes v1.34 and continues evolving — replacing Device Plugins with richer semantics including DeviceClass, ResourceClaim, CEL-based filtering, and topology awareness.]]></description>
            <author>KubeDojo</author>
            <category>dra</category>
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            <title><![CDATA[Armada: Multi-Cluster GPU Scheduling as a Single Resource Pool]]></title>
            <link>https://kubedojo.com/armada-multi-cluster-scheduling</link>
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            <pubDate>Wed, 06 May 2026 07:05:06 GMT</pubDate>
            <description><![CDATA[Armada treats multiple Kubernetes clusters as a single resource pool for GPU-intensive AI workloads, with global queue management, gang scheduling, and production-scale throughput.]]></description>
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            <title><![CDATA[Ingress2Gateway 1.0: Migrating 50% of Clusters from ingress-nginx to Gateway API]]></title>
            <link>https://kubedojo.com/ingress2gateway-gateway-api-migration</link>
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            <pubDate>Wed, 06 May 2026 07:05:04 GMT</pubDate>
            <description><![CDATA[Ingress2Gateway 1.0 provides stable migration from ingress-nginx to Gateway API with 30+ supported annotations and integration-tested translation.]]></description>
            <author>KubeDojo</author>
            <category>ingress-nginx</category>
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            <title><![CDATA[AI Security for LLM-Powered Applications: Prompt Injection Defense]]></title>
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            <description><![CDATA[Spot-to-Spot consolidation, instance diversification, right-sizing pod requests, and the real-world strategies that cut Kubernetes compute costs by 20-40%.]]></description>
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            <title><![CDATA[Observability and Troubleshooting for Karpenter]]></title>
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            <description><![CDATA[Setting up Prometheus metrics scraping, building Grafana dashboards for node lifecycle events, and diagnosing common Karpenter issues in production.]]></description>
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