DevOps AI Toolkit

# Example: Solution CR for tracking dot-ai MCP server deployment # This demonstrates how the Solution CR tracks all resources deployed by the dot-ai Helm chart apiVersion: dot-ai.devopstoolkit.live/v1alpha1 kind: Solution metadata: name: dot-ai namespace: dot-ai labels: app.kubernetes.io/name: dot-ai app.kubernetes.io/instance: dot-ai spec: intent: "Deploy dot-ai MCP server for AI-powered Kubernetes operations" resources: # ServiceAccount - apiVersion: v1 kind: ServiceAccount name: dot-ai namespace: dot-ai # ClusterRole - apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole name: dot-ai # ClusterRoleBinding - apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding name: dot-ai # Secret - apiVersion: v1 kind: Secret name: dot-ai-secrets namespace: dot-ai # Deployment (standard mode) - apiVersion: apps/v1 kind: Deployment name: dot-ai namespace: dot-ai # Service (standard mode) - apiVersion: v1 kind: Service name: dot-ai namespace: dot-ai # Note: Add Ingress if enabled # - apiVersion: networking.k8s.io/v1 # kind: Ingress # name: dot-ai # namespace: dot-ai context: createdBy: "user" rationale: "Self-hosted MCP server providing intelligent Kubernetes deployment recommendations, cluster discovery, and AI-powered operations"