Ansible and RHCE Automation: Roadmap, Lab and Skills Baseline
Automation begins with a known control node, two disposable managed nodes and a learner who can already perform RHCSA tasks manually.
24 ordered lessons that move from foundations into implementation, troubleshooting, architecture decisions, security, cost control, and operational readiness.
Automation begins with a known control node, two disposable managed nodes and a learner who can already perform RHCSA tasks manually.
The control node needs an attributable Ansible version, local documentation, linting tools and a clear support boundary between ansible-core, AAP and community content.
Ansible normally reaches Linux nodes through SSH, discovers Python and uses privilege escalation only for tasks that require it.
Ansible can read configuration from several locations, so a reproducible project must prove which file and settings are active.
Inventory describes managed identities, group relationships and connection data; patterns choose a subset but do not replace authorization.
Ad hoc commands are useful for observation and one-time bounded actions, while repeatable desired state belongs in reviewed playbooks.
A play binds hosts and execution policy to ordered tasks; modules should describe the required state instead of replaying imperative commands.
Variables separate reusable automation from environment data, but duplicated definitions and high-precedence overrides can make the effective value difficult to explain.
Facts describe observed managed-node state, while magic variables expose inventory and execution context; neither should become an accidental source of secrets.
Loops apply one task contract to structured items, while conditions and filters decide whether and how each host-specific value is used.
Handlers defer side effects until notified, while blocks make expected failure, recovery and always-run evidence explicit.
Ansible has distinct modules for metadata, managed content, bounded edits, transfer and archives; choosing the wrong one can overwrite ownership or duplicate text.
A template should turn reviewed data into a complete configuration, validate the candidate file and notify a handler only after a real change.
Vault protects secret data at rest; identity selection, runtime injection, output control and rotation determine whether it remains protected in operation.
A role packages one responsibility with low-precedence defaults, tasks, handlers, files, templates, tests and an explicit input contract.
Collections distribute modules, plugins, roles and documentation; a reproducible project pins versions and records the source used to install them.
Repository trust, package state, configuration validation, handler timing and post-reboot service state form one operable transaction.
Account lifecycle automation must preserve stable IDs, key provenance, validated sudo policy, predictable removal and observable scheduled execution.
Storage automation starts with verified device identity and backups because a syntactically correct play can irreversibly format the wrong block device.
Network, listener, firewall and SELinux policy must agree; change them in an order that preserves the automation connection and provides timed recovery.
An execution environment packages ansible-core, Runner, collections and required Python/system dependencies into a versioned container image.
Automation code needs small reviewable commits, lint and syntax gates, secret detection, disposable integration tests and controlled environment promotion.
AAP controller separates projects, inventories, credentials, execution environments, templates, RBAC and retained job evidence so teams can delegate runs without distributing secrets.
The capstone starts from fresh RHEL nodes and requires inventory, roles, Vault, repositories, services, storage, security policy, validation, recovery and retained evidence under time pressure.