Summary:
Removed the prole-db-manager microservice and simplified deployment to use
prole-authority as the internal management and authorization point. Fixed two
blocking bugs that prevented silent install from completing on knoe-dev-cluster.
Removed: prole-db-manager
- Deleted db-manager-deployment.yaml and db-manager-service.yaml from opentofu manifests
- Deleted src/db-manager/ (Dockerfile, server.js, package.json, tests)
- Removed prole-db-manager port-forward mapping from installer/core/env.py
- Removed init_db_manager.sh from Initialization Scripts (milestones.py, actions.py)
- Removed init_certmgr.sh and init_db_manager.sh tabs from services screen (services.py)
- Removed live k8s Deployment/Service from knoe-dev-cluster
Fixed: PostgreSQL version downgrade error (pg17 -> pg18)
- Created conf/postgresql/.version with value 18
- Updated k8s/prole/prole-db.yaml and prole-db-recovery.yaml.tpl imageName to prole-db:18-089
- Fixed _init_database_options_state() to restore saved version_type from prole.cfg
so db_version_type defaults to v18 (pg18) instead of silently reverting to pg17
- Added database_options.* keys to _collect_input_snapshot() in cfg.py so
distribution, version_type, and all extension toggles persist to prole.cfg
Fixed: Cluster name inconsistency
- Removed stale prole-dev-cluster references; all scripts now use knoe-dev-cluster
- Added knoe-dev-cluster to mode-detection case in etc/prole_cfg.sh
Config: conf/prole.cfg
- Set kerberos_config.enabled = False, KERBEROS_AUTO_ENABLED = False
- Added database_options.distribution = percona, version_type = v18
- Added all 13 extension flags set to True (postgis, pgvector, pgcrypto, pgaudit,
pg_repack, pg_stat_statements, pg_buffercache, pg_freespacemap, pgrowlocks,
postgres_fdw, dblink, pg_stat_monitor, pgbadger)
Verification:
./install.py -s -l -v -c conf/prole.cfg completed successfully.
CNPG deployed prole-db:18-089 to knoe-dev-cluster; all milestones passed.
Co-authored-by: Junie <junie@jetbrains.com>
- Dockerfile: Resolved interactive tzdata prompts with debconf and fixed Percona package names (percona-pg-stat-monitor18 and percona-postgresql-contrib).
- Configuration: Updated prole.cfg with specific namespace (prole-hq0-db0), user (chrisfu), and encrypted secrets.
- Installer: Enhanced initialization scripts (init_openbao.sh, init_certmgr.sh) and updated service layers for cluster deployment.
- Tests: Added coverage for dependent image collection in installer core.
- Version: Bumped prole-db version to 77.
Co-authored-by: Junie <junie@jetbrains.com>
- Tighten Cluster Environment screen layout; switch Service/Prod to kubectx context selection; keep namespace and key controls on one line; ensure Repair button remains reachable.
- Add UI layout regression test to render with large mock data and assert key widgets remain visible and console is scrollable.
- Make kubeconfig generation deterministic under tests by avoiding overwriting cert-based kubeconfigs; write token sidecar kubeconfig when needed.
- Update common-services init scripts and add k3s/Helm deployment bits (svc-check, Kong/CertMgr tasks).
- Moved files from 'prole/' subdirectory to root level or appropriate subdirectories (tests, authority, infrastructure) to flatten the project structure.
- Updated 'install.py' and initialization scripts in 'etc/' to reflect the new directory layout.
- Added 'etc/repair_pipeline.sh' for automated pipeline repairs.
- Updated configuration files including 'conf/prole.cfg' and 'env.sh'.
- Integrated ArgoCD manifests in 'k8s/argocd/'.
- Updated 'prole-app' environment and properties.
- Moved and updated test scripts for better organization and reliability.
- Added 'tests/silent_install_test.sh' for automated installation testing.
- install.py: Major update including configuration variable expansion, improved k3s/k3d handling, and enhanced installation logic.
- etc/ scripts: Significant refactoring of initialization scripts (Kerberos, Port Forwards, Garage Store, etc.).
- Port Forwards: Transitioned from XML to port-mappings.conf for managing kubectl port-forwards.
- Status Reporting: Improved status checking for common services.
- Infrastructure: Updated Ansible inventory and rsyslog role configurations.
- Tests: Added a comprehensive suite of tests for 'etc' initialization scripts in prole/tests/etc/.
- Documentation: Added prole-db-documentation-mcp-architecture.md.
- General: Updated Dockerfiles and various helper scripts.
- Installer: Updated k3s deployment logic and configuration generation.
- k3s Role: Implemented token drift protection to verify Vault secrets against live node tokens.
- DNS: Enhanced samba_reverse_dns role to support multiple reverse zones.
- Service Init: Updated initialization scripts and status reporting.
- Infrastructure: Added prole management role and k3s diagnostic playbook.
- Configuration: Updated prole.cfg and added vaulted group variables.
- Consolidated and split initialization scripts in etc/:
- Removed init_prole-db.sh and init_authority.sh.
- Added init_kdc.sh for in-cluster MIT Kerberos KDC (prole-authority).
- Added init_ollama.sh for Ollama AI service integration.
- Added init_service_layer.sh for high-level service orchestration.
- Added init_k3s_registry.sh for private registry management.
- Major updates to install.py:
- Support for new Ollama and KDC configuration.
- Improved prole.cfg rendering and namespace handling.
- Updated unattended install flags.
- Infrastructure and Deployment:
- Updated K3s Ansible role with private registry support (registries.yaml template).
- Added prole-authority Dockerfile.
- Updated OpenBao Kerberos ConfigMap and other K8s manifests.
- Configuration:
- Updated prole.cfg with new sections for Ollama and Monitoring.
- Refined environment variable exports in env.sh and prole_cfg.sh.
- Introduced scripts `init_common_services.sh` and `status_common_services.sh` for deploying and checking common services (OpenBao, OpenTofu, registry) within Kubernetes namespaces.
- Improved service namespace configuration in `install.py` and updated initialization logic.
- Updated `prole.cfg` and `kerberos-configmap.yaml` with necessary changes to integrate the new features.
