resource quota review: fix OOM risks, close quota gaps, add HA protections

Phase 1 - OOM fixes:
- dashy: increase memory limit 512Mi→1Gi (was at 99% utilization)
- caretta DaemonSet: set explicit resources 300Mi/512Mi (was at 85-98%)
- mysql-operator: add Helm resource values 256Mi/512Mi, create namespace
  with tier label (was at 92% of LimitRange default)
- prowlarr, flaresolverr, annas-archive-stacks: add explicit resources
  (outgrowing 256Mi LimitRange defaults)
- real-estate-crawler celery: add resources 512Mi/3Gi (608Mi actual, no
  explicit resources)

Phase 2 - Close quota gaps:
- nvidia, real-estate-crawler, trading-bot: remove custom-quota=true
  labels so Kyverno generates tier-appropriate quotas
- descheduler: add tier=1-cluster label for proper classification

Phase 3 - Reduce excessive quotas:
- monitoring: limits.memory 240Gi→64Gi, limits.cpu 120→64
- woodpecker: limits.memory 128Gi→32Gi, limits.cpu 64→16
- GPU tier default: limits.memory 96Gi→32Gi, limits.cpu 48→16

Phase 4 - Kubelet protection:
- Add cpu: 200m to systemReserved and kubeReserved in kubelet template

Phase 5 - HA improvements:
- cloudflared: add topology spread (ScheduleAnyway) + PDB (maxUnavailable:1)
- grafana: add topology spread + PDB via Helm values
- crowdsec LAPI: add topology spread + PDB via Helm values
- authentik server: add topology spread via Helm values
- authentik worker: add topology spread + PDB via Helm values

stacks/servarr/flaresolverr/main.tf

@@ -31,6 +31,16 @@ resource "kubernetes_deployment" "flaresolverr" {
           image = "ghcr.io/flaresolverr/flaresolverr:latest"
           name  = "flaresolverr"
 
+          resources {
+            requests = {
+              cpu    = "10m"
+              memory = "150Mi"
+            }
+            limits = {
+              cpu    = "500m"
+              memory = "384Mi"
+            }
+          }
           port {
             container_port = 8191
           }

stacks/servarr/prowlarr/main.tf

@@ -53,6 +53,16 @@ resource "kubernetes_deployment" "prowlarr" {
           image = "lscr.io/linuxserver/prowlarr:latest"
           name  = "prowlarr"
 
+          resources {
+            requests = {
+              cpu    = "10m"
+              memory = "192Mi"
+            }
+            limits = {
+              cpu    = "500m"
+              memory = "384Mi"
+            }
+          }
           port {
             container_port = 9696
           }