What problem does it solve?
It resolves slow, broken, or unstable Talos-based Kubernetes clusters by guiding investigation across hardware, Talos, Kubernetes, Cilium networking, Longhorn storage, GitOps drift, and security signals, then proposing remediation that requires explicit approval.
Core Features & Use Cases
- Autonomous investigation workflows for pod crashes, node failures, networking symptoms, storage problems, and GitOps sync failures with structured, multi-phase evidence gathering.
- Approval-gated remediation with explicit risk levels, rollback expectations, and optional snapshot requirements to reduce operational mistakes.
- Cross-layer correlation using Talos health/logs, Kubernetes events/logs/metrics, Cilium/Hubble flow evidence, Longhorn replica health, ArgoCD drift checks, and security signals (Falco/Tetragon/Trivy/SPIRE).
Quick Start
Tell your AI to investigate a failing workload with: "Investigate why my pod rabbitmq-0 in production is crashing using talos-cluster-ops and propose the safest remediation I can approve."