Diagnoses and resolves common CAST AI agent, API, and autoscaler issues within Kubernetes clusters.
The CAST AI Common Errors skill is a specialized diagnostic toolkit designed to troubleshoot the most frequent challenges encountered when using CAST AI for Kubernetes cost optimization. It provides structured logic for Claude to identify agent connectivity failures, verify API authentication, and resolve scaling bottlenecks. By combining kubectl commands with API checks, it helps developers and DevOps engineers quickly address issues like CrashLoopBackOff errors, unschedulable pods, and policy misconfigurations, ensuring continuous cloud cost savings and cluster reliability.
Características Principales
01Automated diagnostic routines for CAST AI agent connectivity and heartbeat issues
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03API authentication verification and error code troubleshooting
04Detection of configuration drift between Terraform and the CAST AI console
05Configuration auditing for spot instance fallbacks and node downscalers
06Step-by-step resolution for Kubernetes node scaling and provisioning failures
Casos de Uso
01Debugging why Kubernetes nodes are not scaling up for pending or unschedulable pods
02Resolving 401 Unauthorized errors during CAST AI API interactions
03Troubleshooting CAST AI agents that appear 'Disconnected' in the management console
