What problem does it solve? Troubleshooting AKS cluster issues requires manually correlating control plane logs, cluster snapshots, and internal documentation across multiple Kusto databases and wikis, which is slow and error-prone for CSS engineers. ## Core Features & Use Cases - Guided Troubleshooting Workflow: Walks through information gathering, wiki search, cluster snapshot retrieval, KQL queries, and root-cause summarization in a structured sequence. - Pre-Built KQL Query Library: Provides schema-verified query templates for AKSprod, AKSccplogs, AKSinfra, and AKSmetrics databases covering cluster info, health checks, node lifecycle, autoscaler, and audit logs. - Schema-Aware Querying: Ships JSON table schemas and a quick-reference guide to prevent common column-name mistakes like using ccpNamespace instead of namespace on ManagedClusterSnapshot. - Use Case: A customer reports nodes stuck in NotReady after an upgrade. Provide the cluster resource ID and time range, and the skill retrieves the ccpNamespace, checks node events in AKSKubeEvents, inspects ClusterAutoscaler logs, and summarizes the root cause with evidence. ## Quick Start Ask the skill to investigate why pods are failing to schedule on your AKS cluster by providing the cluster resource ID and the time range when the issue occurred.