autoscaling

Kafka HPA scaling issues with incorrect CPU metrics

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Problem – Inconsistent Kafka HPA Scaling Due to Mis‑configured CPU Metrics In a Kubernetes‑based telemetry pipeline ingesting IoT sensor data, the Horizontal Pod Autoscaler (HPA) for Kafka consumer pods either adds ~30 % extra replicas during low‑traffic periods or fails to add enough pods during traffic spikes. The symptoms manifest as: Over‑provisioned pods at night, inflating … Read more

PostgreSQL HPA not scaling under high CPU usage

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Problem – PostgreSQL HPA Not Scaling Under High CPU Usage The PostgreSQL deployment runs in a Kubernetes cluster that is part of an AI‑driven orchestration platform. During traffic spikes the API gateway generates thousands of concurrent requests per second, causing PostgreSQL CPU utilization to rise sharply. Expected behavior is that the Horizontal Pod Autoscaler (HPA) … Read more

Redis HPA scaling issues with Prometheus metrics

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Problem Description In a Kubernetes‑based real‑time data pipeline, Redis is used as an in‑memory cache. The Horizontal Pod Autoscaler (HPA) is configured to scale the downstream consumer pods based on the Prometheus metric redis_memory_used_bytes exposed by redis_exporter. Operators observed the following inconsistent behavior: During brief traffic spikes the HPA adds 3‑4 extra pods, but the … Read more

Kubernetes scheduler pod placement failure after autoscaling

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Problem Description The Claude inference service experiences a cascade of pending pods during traffic spikes. Typical symptoms observed in the kubectl get pods -n claude-prod output are: NAME READY STATUS RESTARTS AGE claude-infer-7f9c9d8c9f-abcde 0/1 Pending 0 2m30s claude-infer-7f9c9d8c9f-fghij 0/1 Pending 0 2m30s … Relevant scheduler events (extracted from kubectl describe pod <pod>) contain the following … Read more