Ansible Automation Reference on Dettonville

Core System Hardening Roles

Thu, 21 May 2026 00:00:00 +0000

The baseline security of the entire datacenter depends on the initial stabilization pass applied to the underlying operating system. The platform handles this through two critical automation components: a dedicated initial access role (bootstrap_ansible_user) and a multi-tier orchestration role (bootstrap_linux) that executes modular configuration steps before invoking our authoritative security standard (harden_os_linux).

Technical Stand-Up Pipeline

The execution sequence within the system hardening track transitions a newly provisioned, untrusted OS footprint into a fully managed, locked-down node:

Runtime Fabric & Containment Roles

Thu, 21 May 2026 00:00:00 +0000

Once the underlying operating system is fully stabilized and hardened by the foundational bootstrap phase, the platform provisions its active execution fabric. By isolating all downstream workloads inside standard container spaces, the system ensures zero package drift on the host nodes while supporting high-density compute and accelerated local AI processing.

Execution Fabric Stand-Up Flow

The runtime fabric roles transition a bare operating system node into an active container cluster or accelerated hardware endpoint:

Control-Plane Service Roles

Thu, 21 May 2026 00:00:00 +0000

Once a host node is established, accelerated, and encapsulated by the runtime fabric, the platform applies target-specific service definitions. Rather than treating hosts as generic servers, site.yml matches specific inventory group scopes—such as AI inference compute clusters, corporate domain definitions, or management gateways—and configures them using dedicated service paths.

Service Track Execution Map

The control-plane service tier parses the node’s final group assignment to apply purpose-driven system profiles:

graph TD
A[Active Runtime Fabric<br/><code>bootstrap_docker_stack Complete</code>] --> B{Inventory Group Scope?}
B -- ollama_hosts / aibrix_prod --> C[Local Inference Platforms<br/><code>bootstrap_llm_host</code>]
B -- ca_domain_prefix_groups --> D[Inventory Domain Architecture<br/><code>Dynamic Target Mapping</code>]
B -- ansible_controller --> E[Declarative Automation Panels<br/><code>bootstrap_awx_resources</code>]
style A fill:#f1f5f9,stroke:#cbd5e1,stroke-width:2px;
style B fill:#fff,stroke:#cbd5e1,stroke-width:2px;
style C fill:#f1f5f9,stroke:#cbd5e1,stroke-width:2px;
style D fill:#f1f5f9,stroke:#cbd5e1,stroke-width:2px;
style E fill:#f1f5f9,stroke:#cbd5e1,stroke-width:2px;

1. Local AI Inference Infrastructure (`bootstrap_llm_host`)

For air-gapped or localized enterprise machine learning spaces, the platform isolates model runtime loops entirely within your local computing farm.

Ansible Automation Reference on Dettonville

Core System Hardening Roles

Technical Stand-Up Pipeline

Runtime Fabric & Containment Roles

Execution Fabric Stand-Up Flow

Control-Plane Service Roles

Service Track Execution Map

1. Local AI Inference Infrastructure (bootstrap_llm_host)

1. Local AI Inference Infrastructure (`bootstrap_llm_host`)