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Haitao Pan 609a88ddcf feat(bridge): fail fast when bridge domain is empty/non-FQDN under Caddy exposure 
Non-empty pass-through check: xworkmate_bridge_domain feeds /etc/hostname and the
caddy site name; an empty/non-FQDN/127.0.0.1 value yields an invalid Caddyfile.
Assert a valid FQDN when caddy_enabled (public ingress), with a clear remediation
message (set XWORKMATE_BRIDGE_DOMAIN or provide CMDB service_domains).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-24 20:50:19 +08:00
..
agent_skills refactor(agent_skills): run on target host, git-clone sources, drop delegate_to localhost 2026-06-24 14:57:49 +08:00
ai_agent_runtime fix(ai-workspace): deploy robustness on Debian13/Ubuntu26.04 (py3.13) 2026-06-24 03:02:43 +08:00
azure_dev_desktop_lifecycle/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
charts feat(gpu_inference): add comprehensive GPU inference infrastructure with Sealos, Ray, and vLLM 2026-04-23 19:17:23 +08:00
cloud_cli_prereqs fix(permissions): add missing become:true to all cross-platform /usr/local/bin writes 2026-06-19 18:56:47 +08:00
cloud_vm_inventory_emit/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
cloud_vm_request_validate/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
cloudflare_dns Migrate XRDP and Cloudflare playbooks 2026-04-05 16:54:48 +08:00
cloudflare_svc_plus_dns deploy: align console ingress and dns contract 2026-04-12 18:14:28 +08:00
dev_desktop_common feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
dev_desktop_debian_kde/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
dev_desktop_fedora_gnome/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
dev_desktop_windows feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
docker fix: quote strings in caddy_base_dir Jinja (invalid unquoted expr) 2026-06-21 09:55:12 +00:00
gcp_dev_desktop_lifecycle/tasks feat(playbooks): add cloud desktop bootstrap flow 2026-04-10 17:09:59 +08:00
github chore: commit pending infra playbook changes including ssh initialization script 2026-06-19 18:09:16 +08:00
grafana-dashboard feat(ansible): extract playbooks and roles into standalone repository 2025-12-21 19:09:46 +08:00
harden_ssh_root_key_only Migrate XRDP and Cloudflare playbooks 2026-04-05 16:54:48 +08:00
readonly_ssh_user Add readonly SSH audit user role and playbooks 2026-04-10 11:08:47 +08:00
vhosts feat(bridge): fail fast when bridge domain is empty/non-FQDN under Caddy exposure 2026-06-24 20:50:19 +08:00
README.md feat(playbooks): add comprehensive vhosts roles and ops scripts 2025-12-21 19:23:19 +08:00

README.md

Playbook roles planning

This document clarifies what should live under /playbooks/roles/ for host-level automation (Ansible) versus what should be delivered through Helm charts, and ensures we cover the five tiers across data platforms: data warehouse → big data → ML → DL → large models.

Scope rules

  • Ansible roles: host-coupled configuration that is not itself a cloud resource (GPU driver/runtime, OS tuning, user/SSH prep, rendering on-host config files, database bootstrapping, etc.).
  • Helm charts: anything that runs as a Kubernetes workload (operators, clusters, services running in pods).

Base roles shared across tiers (Ansible)

  • GPU driver and CUDA stack installation.
  • Docker/Containerd runtime setup.
  • System parameter tuning (kernel limits, hugepages, network stack), plus user home/SSH layout.
  • Database initialization tasks (e.g., bootstrap PostgreSQL/ClickHouse on hosts) and rendering templated configs such as ClickHouse/users.xml.

Coverage by capability tier

Tier Host-focused roles (Ansible) Kubernetes services (Helm)
Data warehouse ClickHouse host bootstrap & config render; PostgreSQL init where needed. —
Big data JVM/runtime, local disks, and OS tuning for data nodes. Spark Operator; Flink Operator; Kafka/Redpanda; MinIO.
ML GPU runtime base (drivers, container runtime), Python ML base image prep; user workspace/SSH. Ray Cluster; MLflow; JupyterHub.
DL Same GPU/system tuning plus inference node bootstrap (tensorRT/cuDNN as needed). Triton Inference Server; LMDeploy (for deployment runtimes).
Large models Secure SSH/user profiles and config templating for model storage/IO. vLLM serving; model-specific Helm releases atop Ray/K8s.

Suggested role layout under /playbooks/roles/

  • common/ (new): shared tasks for system tuning, users/SSH, and package repos for GPU/runtime support.
  • gpu/: install GPU drivers + CUDA toolkit.
  • container_runtime/: install and configure Docker/Containerd with GPU runtime integration.
  • database_init/: bootstrap on-host databases (e.g., PostgreSQL, ClickHouse), render config files (users.xml, etc.).
  • bigdata_node_prep/: OS/disk tuning for Spark/Flink/Kafka/Redpanda/MinIO hosts.
  • ml_node_prep/: Python/conda base, SSH workspace prep for ML workloads.
  • dl_inference_node/: tensorRT/cuDNN dependencies and runtime checks for Triton/LMDeploy nodes.

Helm-delivered components should live under playbooks/roles/charts/ or the repo’s Helm release structure and include Spark/Flink Operators, Kafka/Redpanda/MinIO, Ray Cluster, Triton, vLLM/LMDeploy, MLflow, and JupyterHub.