DNS was pointing to Gateway (10.1.71.90) instead of NGINX Ingress (10.1.71.80)
after we removed the HTTPRoute manifests. This caused traffic to hit the
Gateway's wildcard cert and get 'no healthy upstream' errors.
Added external-dns annotations to Ingress to direct DNS to correct IP:
- external-dns.alpha.kubernetes.io/hostname: the-seas.local.mk-labs.cloud
- external-dns.alpha.kubernetes.io/target: 10.1.71.80
This will update Technitium DNS to point to NGINX Ingress Controller.
The configureUserSettings field contained nginx configuration
('http2_push_preload on;') which was incorrectly being used as
CONFIG_OVERWRITE_JSON. This caused harbor-core to crash with a
JSON parse error.
CONFIG_OVERWRITE_JSON expects valid JSON for Harbor configuration
overrides, not nginx snippets. Removing this field to fix the
CrashLoopBackOff.
- ExternalSecret now pulls only HARBOR_ADMIN_PASSWORD from 1Password
- Removed database, redis, core, jobservice, registry secret references
- Harbor Helm chart auto-generates all internal secrets (standard pattern)
- Reduces complexity and aligns with Harbor best practices
This change removes dependency on 5 1Password fields that should be deleted:
- database-password
- redis-password
- core-secret
- jobservice-secret
- registry-password
Only harbor-admin-password field needed in 1Password item 'the-seas'
Harbor Helm chart requires both existingSecret and existingSecretKey
parameters to properly reference credentials. Without the key names,
the chart creates secrets with empty passwords, causing authentication
failures between components.
Added:
- database.internal.existingSecretKey: DATABASE_PASSWORD
- redis.internal.existingSecretKey: REDIS_PASSWORD
The secretName parameter was being used as a literal secret name
'CORE_SECRET' which doesn't exist. This caused harbor-core pods to
fail mounting volumes.
The correct approach is to use existingSecret for credential keys,
and let Harbor manage its own internal secrets.
Harbor Helm chart expects 'secret' key not 'CORE_SECRET' for the
CORE_SECRET environment variable. This was causing jobservice pod
to fail with CreateContainerConfigError.
Fixes: harbor-jobservice-757bbf44cc-tvznq error
Removing Firecrawl ArgoCD application and all manifests. The deployment
was failing due to missing container images that need to be built from
source. This requires platform infrastructure we don't have yet.
Will return to Firecrawl deployment after Harbor registry and Tekton
pipelines are deployed and configured.
Note: ArgoCD also needs a thematic EPCOT name at some point.
- Changed from ghcr.io/mendableai/* to ghcr.io/firecrawl/*
- Updated all three services: main API, playwright-service, and nuq-postgres
- Changed tag from v1.0.0 to latest (official images use latest tag)
- Fixes ImagePullBackOff errors caused by incorrect registry namespace
Per official Firecrawl docker-compose.yaml, images are published under
ghcr.io/firecrawl/, not ghcr.io/mendableai/
CRITICAL FIXES:
✅ Add PersistentVolumeClaims for all stateful services
- PostgreSQL: 20Gi PVC on nfs-emporium (data persistence)
- Redis: 10Gi PVC on nfs-emporium (cache and queue)
- RabbitMQ: 5Gi PVC on nfs-emporium (message queue)
✅ Pin all image versions (no more 'latest' tags)
- Firecrawl API/Worker: v1.0.0
- Playwright Service: v1.0.0
- PostgreSQL (nuq-postgres): v1.0.0
- Redis: 7.4.1-alpine
- RabbitMQ: 3.13.7-management-alpine
✅ Convert raw manifests to proper Helm chart
- Template-based configuration
- Centralized values.yaml
- Proper Helm helpers and labels
- Easy configuration management
WHAT CHANGED:
- Created chart/ directory with full Helm chart structure
- Moved old manifests to old-manifests/ for reference
- Updated ArgoCD Application to use Helm chart source
- Added comprehensive README and MIGRATION docs
- All services now use nfs-emporium storage class
- Redis configured with AOF persistence
- Proper resource limits and health checks
- Gateway/HTTPRoute configs integrated into chart
DEPLOYMENT:
ArgoCD will automatically sync and apply changes.
Old ephemeral data will be lost (fresh start with persistence).
Resolves data loss issues and brings deployment to production standards.
