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
This commit is contained in:
Viktor Barzin 2026-03-08 18:17:46 +00:00
parent ead33b23dd
commit d352d6e7f8
19 changed files with 154 additions and 18 deletions

View file

@ -18,7 +18,6 @@ resource "kubernetes_namespace" "realestate-crawler" {
labels = {
"istio-injection" : "disabled"
tier = local.tiers.aux
"resource-governance/custom-quota" = "true"
}
}
}
@ -321,6 +320,16 @@ resource "kubernetes_deployment" "realestate-crawler-celery" {
image = "viktorbarzin/realestatecrawler:latest"
image_pull_policy = "Always"
command = ["python", "-m", "celery", "-A", "celery_app", "worker", "--loglevel=info", "--pool=threads"]
resources {
requests = {
cpu = "50m"
memory = "512Mi"
}
limits = {
cpu = "1"
memory = "3Gi"
}
}
port {
name = "metrics"
container_port = 9090