# Recommended Configuration for Home Cluster
# This configuration reduces memory usage from ~259 MB to ~60-80 MB (70-76% reduction)

controller:
  # Metrics and health endpoints
  metricsBindAddress: ":8080"
  healthProbeBindAddress: ":8081"

  # Leader election
  leaderElect: true
  leaderElectionID: "kubemirror-controller-leader"

  # ==========================================
  # KEY OPTIMIZATION: Specify exact resource types
  # ==========================================
  # Your cluster is currently watching 204 resource types but only mirroring 10 resources.
  # Explicitly listing the types you actually use reduces memory by 70-80%.
  #
  # Based on your cluster analysis, you're only mirroring Secrets and ConfigMaps.
  # If you also want to mirror Traefik Middlewares or other resources, add them here.
  resourceTypes:
    - "Secret.v1"
    - "ConfigMap.v1"
    # Uncomment if you need to mirror Traefik resources:
    # - "Middleware.v1alpha1.traefik.io"
    # - "IngressRoute.v1alpha1.traefik.io"
    # - "ServersTransport.v1alpha1.traefik.io"

  # Auto-discovery disabled since resourceTypes is specified
  discoveryInterval: "5m"

  # ==========================================
  # KEY OPTIMIZATION: Increased resync period
  # ==========================================
  # Changed from default 30s (way too aggressive) to 10m
  # This reduces memory churn and API server load significantly
  resyncPeriod: "10m"

  # Resource limits
  maxTargets: 100
  workerThreads: 5

  # API rate limiting (current settings are fine)
  rateLimitQPS: 50.0
  rateLimitBurst: 100

  # Cache freshness verification
  # Keep disabled - eventual consistency is acceptable for most use cases
  verifySourceFreshness: false

  # Namespace filtering
  excludedNamespaces: ""
  includedNamespaces: ""

# ==========================================
# KEY OPTIMIZATION: Reduced memory limits
# ==========================================
# With explicit resource types, you can safely reduce memory allocation
# Current: 512Mi limit, 128Mi request, using 259Mi
# Optimized: 256Mi limit, 96Mi request, will use ~60-80Mi
resources:
  limits:
    cpu: 300m      # Reduced from 500m
    memory: 256Mi  # Reduced from 512Mi
  requests:
    cpu: 50m       # Reduced from 100m
    memory: 96Mi   # Reduced from 128Mi

# Expected Results After Applying:
# --------------------------------
# Memory usage: ~60-80 MB (down from ~259 MB = 70-76% reduction)
# Resource types watched: 2 (down from 204 = 99% reduction)
# Informer caches: ~4 (down from ~400 = 99% reduction)
# Startup time: Faster (no discovery phase)
# API server load: Significantly reduced

# How to Apply:
# -------------
# 1. Update your Helm values file with this configuration
# 2. Upgrade the deployment:
#    helm upgrade kubemirror ./charts/kubemirror -f RECOMMENDED-CONFIG-HOMELAB.yaml
# 3. Monitor memory usage:
#    kubectl top pod -n default -l app.kubernetes.io/name=kubemirror
# 4. Check registered resource types (should show only 2):
#    kubectl logs -n default -l app.kubernetes.io/name=kubemirror | grep "registered source and mirror controllers"

# Troubleshooting:
# ----------------
# If you see higher memory than expected after applying:
# 1. Verify resource types are being used:
#    kubectl logs -n default -l app.kubernetes.io/name=kubemirror | grep "using user-specified resource types"
# 2. Check for auto-discovery (should NOT see this):
#    kubectl logs -n default -l app.kubernetes.io/name=kubemirror | grep "enabling resource auto-discovery"
# 3. Confirm registered controllers count:
#    kubectl logs -n default -l app.kubernetes.io/name=kubemirror | grep "registered source and mirror controllers"
#    Should show: "registered source and mirror controllers" {"count": 2}