pod-management

Kubernetes pod stuck after TensorFlow model update

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Problem Description A Kubernetes Deployment that runs tensorflow_model_server was updated to serve a new model version. After the rollout the pods entered a Running state but never became Ready. The following symptoms were observed: Readiness probe failures: Readiness probe failed: Get http://localhost:8501/v1/models/my_model/metadata: dial tcp 127.0.0.1:8501: connect: connection refused Container logs show the server exiting immediately: … Read more

Kubernetes pod OOMKilled after increasing AI model size

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Problem – Pods OOMKilled After Increasing AI Model Size An AI inference service deployed on a multi‑node Kubernetes cluster started failing shortly after the model binary grew from 2 GB to 4 GB. The symptoms observed across the cluster were: State: Terminated Reason: OOMKilled in kubectl describe pod output. Node‑level memory pressure events and occasional pod eviction … Read more

HPA not scaling pods with high CPU usage in Kubernetes

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Problem Description The Horizontal Pod Autoscaler (HPA) attached to a Deployment that serves Hugging Face Transformers inference never creates additional replicas, even when the pods report CPU utilization above the configured target (e.g., 80%). The symptom manifests as: CPU usage in kubectl top pod consistently >90%. Inference latency spikes and occasional request time‑outs. HPA status shows … Read more

Kubernetes HPA not scaling pods with NVIDIA GPU metrics

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Problem Description The Horizontal Pod Autoscaler (HPA) in a Kubernetes‑based CI/CD pipeline is expected to add or remove training pods based on GPU utilization. In practice the HPA never scales out: the replica count stays at 1 even when GPU usage spikes to 95 % during model training. The symptom manifests as a growing job queue, … Read more

Nginx serving stale data after Kubernetes pod update

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Problem – Nginx Serves Stale Data After a Kubernetes Pod Update In an on‑premises data‑center, Nginx (or the Nginx Ingress Controller) is used as a reverse proxy for a micro‑services architecture. Service endpoints are discovered through the Kubernetes EndpointSlice API. After a rolling update or a pod crash, Nginx continues to forward traffic to the … Read more

Kubernetes scheduler failing to place AI pods on AMD GPU edge nodes

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Kubernetes Scheduler Failing to Place AI Pods on AMD GPU Edge Nodes Problem Description In a remote edge site the AI inference workload never leaves the Pending state. Typical scheduler messages include: 0/5 nodes are available: 5 node(s) didn’t match node selector. Insufficient amd.com/gpu: 0/5 nodes are available: 5 node(s) have insufficient resources. scheduler: no … Read more

Kubernetes secret rotation failure for multi-GPU training pods

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Problem: Kubernetes Secret Rotation Failure for Multi‑GPU Training Pods In a production AI training platform, each training job runs in a pod that requests multiple GPUs. Access to the GPU resource provider (e.g., NVIDIA GPU Cloud, a proprietary licensing server, or a cloud‑native GPU quota service) is gated by short‑lived credentials stored in a Secret. … Read more

Kubernetes pod eviction due to OOM on AMD GPU nodes

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Problem – Frequent Pod Evictions on AMD GPU Nodes During Disaster Recovery During disaster‑recovery (DR) drills the AI training platform experiences a surge of concurrent training jobs. On clusters that use AMD MI250X GPUs the kubelet repeatedly evicts pods with the reason=OutOfmemory condition. Typical symptoms observed: Pods transition to Evicted status within minutes of the … Read more

RabbitMQ pod eviction during CI/CD pipeline load testing

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RabbitMQ pod eviction during CI/CD pipeline load testing Problem During nightly CI/CD pipeline runs the RabbitMQ StatefulSet is repeatedly evicted by the kube‑scheduler. The eviction manifests as a FailedScheduling event and the pod enters Terminating followed by a recreation of the pod with a new name. The pipeline then fails with connection timeouts and lost … Read more

Elasticsearch scheduler pod failed to place due to insufficient resources

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Problem Description In an air‑gapped Kubernetes cluster the Elasticsearch scheduler pod (managed by the Elastic Cloud on Kubernetes (ECK) operator) remains in Pending with events such as: Events: Type Reason Age From Message —- —— —- —- ——- Warning FailedScheduling 2m default-scheduler 0/5 nodes are available: 5 Insufficient cpu. Warning FailedScheduling 2m default-scheduler 0/5 nodes … Read more