Resource Sync Guide

This guide covers the ResourceSyncConfig CRD for enabling resource visibility and semantic search in your Kubernetes cluster.

Overview

The ResourceSyncConfig enables:

• Resource Discovery: Automatically discovers all resource types in your cluster
• Change Tracking: Watches for resource changes (create, update, delete)
• Semantic Search: Syncs resource metadata to MCP for natural language queries

Stack Installation

If you installed via the DevOps AI Toolkit Stack, ResourceSyncConfig is already configured. You can verify with:

kubectl get resourcesyncconfig -n dot-ai

Continue below only if you need to customize the configuration or installed the controller individually.

Prerequisites

• Controller installed (see Setup Guide)
• DevOps AI Toolkit MCP installed and running

Quick Start

1. Create a secret with your MCP API key:

kubectl create secret generic dot-ai-secrets \
  --namespace dot-ai \
  --from-literal=auth-token=your-auth-token-here

2. Create a ResourceSyncConfig to start syncing resources:

apiVersion: dot-ai.devopstoolkit.live/v1alpha1
kind: ResourceSyncConfig
metadata:
  name: default-sync
  namespace: dot-ai
spec:
  mcpEndpoint: http://dot-ai.dot-ai.svc.cluster.local:3456/api/v1/resources/sync
  mcpAuthSecretRef:
    name: dot-ai-secrets
    key: auth-token
  debounceWindowSeconds: 10
  resyncIntervalMinutes: 60

3. Apply it:

kubectl apply -f resourcesyncconfig.yaml

How It Works

1. Discovery: Controller discovers all resource types via the Kubernetes Discovery API
2. Informers: Dynamic informers are created for each resource type
3. Change Detection: Informer event handlers detect create/update/delete events
4. Debouncing: Changes are batched in a time window to reduce API calls
5. Sync to MCP: Batched changes are sent to MCP via HTTP
6. Periodic Resync: Full state is sent periodically to catch any missed events

What Gets Synced

For each resource, the following metadata is synced to MCP:

• Kind, APIVersion, Name, Namespace
• Labels and select annotations (description-related)
• Creation and update timestamps

This metadata enables semantic search to discover resources (e.g., "find all databases", "list deployments in production").

What's NOT Synced

The following are not synced to reduce traffic and storage:

• Resource status - fetched on-demand from Kubernetes API when needed
• Resource spec - fetched on-demand from Kubernetes API when needed
• High-volume resources: Events, Leases, EndpointSlices
• Large annotations like kubectl.kubernetes.io/last-applied-configuration

This design means resource discovery happens via semantic search in Qdrant, while current state (status/spec) is always fetched fresh from the Kubernetes API.

Configuration

Spec Fields

Field	Type	Required	Default	Description
mcpEndpoint	string	Yes	-	Full URL of the MCP resource sync endpoint
mcpAuthSecretRef	SecretReference	Yes	-	Secret containing API key for MCP authentication
debounceWindowSeconds	int	No	10	Time window to batch changes before syncing
resyncIntervalMinutes	int	No	60	Full resync interval (catches missed events)

Status

Check the status to verify the sync is working:

kubectl get resourcesyncconfig default-sync -o yaml

Status Fields

Field	Description
active	Whether the watcher is running
watchedResourceTypes	Number of resource types being watched
totalResourcesSynced	Total resources synced to MCP
lastResyncTime	Time of last full resync
syncErrors	Count of sync errors
conditions	Standard Kubernetes conditions

Conditions

Type	Description
Ready	True when watcher is active and syncing

Semantic Search

Once resources are synced, you can search using natural language through MCP:

"which databases are we running?"
"list deployments in production namespace"
"find all services related to payments"

MCP uses semantic embeddings to understand intent, so you don't need to know exact resource kinds or field names.

Query Flow

For questions about resource state (e.g., "what's the status of my databases"):

1. Discovery: Semantic search finds relevant resources in Qdrant
2. Fetch: Current status is fetched from Kubernetes API
3. Response: AI synthesizes the answer with fresh data

This ensures status information is always current, not potentially stale from a sync lag.

Example: Full Configuration

apiVersion: dot-ai.devopstoolkit.live/v1alpha1
kind: ResourceSyncConfig
metadata:
  name: production-sync
  namespace: dot-ai
spec:
  # MCP endpoint for resource sync (full URL)
  mcpEndpoint: http://dot-ai.dot-ai.svc.cluster.local:3456/api/v1/resources/sync

  # Required: authentication for MCP
  mcpAuthSecretRef:
    name: dot-ai-secrets
    key: auth-token

  # Batch changes for 10 seconds before syncing
  debounceWindowSeconds: 10

  # Full resync every hour to catch any missed events
  resyncIntervalMinutes: 60

Troubleshooting

Watcher Not Starting

Check the Ready condition:

kubectl get resourcesyncconfig default-sync -o jsonpath='{.status.conditions}'

Common issues:

• Invalid mcpEndpoint URL
• MCP service not reachable
• Missing RBAC permissions

No Resources Being Synced

Check the status:

kubectl get resourcesyncconfig default-sync -o jsonpath='{.status.watchedResourceTypes}'

If zero, check controller logs:

kubectl logs -l app.kubernetes.io/name=dot-ai-controller -n dot-ai --tail=50

Sync Errors

Check the syncErrors status field and controller logs for details:

kubectl get resourcesyncconfig default-sync -o jsonpath='{.status.syncErrors}'

Cleanup

Delete the ResourceSyncConfig to stop syncing:

kubectl delete resourcesyncconfig default-sync

This stops the watchers but does not delete synced data from MCP/Qdrant.

Next Steps

• Learn about Capability Scanning for autonomous capability discovery
• Explore Remediation Policies for event-driven remediation
• Check Troubleshooting Guide for common issues