2026 · AIOPS
KubePulse
KubePulse watches Kubernetes pod metrics in real time and predicts memory-related failures before they cause an outage. A hybrid LSTM + LightGBM model trained on Prometheus metrics flags anomalies ahead of the breach, a custom Prometheus exporter feeds the prediction back into the cluster for autoscaling, and Gemini 1.5 Pro generates the exact kubectl remediation command once an anomaly is confirmed.
Stack
PythonGoTensorFlowLightGBMKubernetesPrometheusLangChainGemini 1.5 ProDocker
Highlights
- Hybrid LSTM + LightGBM model on Prometheus metrics cut CrashLoopBackOff events 38% versus threshold-based alerting
- Custom Prometheus exporter surfaces a predicted-memory metric that drives HPA autoscaling directly
- Gemini 1.5 Pro generates targeted kubectl remediation commands on confirmed anomalies, cutting MTTR 40%