1. Goal

Deep Dive and Submission Example for Goal

A complete treatment of Goal contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Goal

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Goal

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Goal is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Goal

This section is not just a definition. In the workshop, Goal is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Goal

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Goal

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Goal

Operations Note for Goal

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Goal is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

2. Project Structure

Deep Dive and Submission Example for Project Structure

A complete treatment of Project Structure contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Project Structure

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Project Structure

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Project Structure is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Project Structure

This section is not just a definition. In the workshop, Project Structure is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Project Structure

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Project Structure

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Project Structure

Operations Note for Project Structure

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Project Structure is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

3. Inventory Design

Deep Dive and Submission Example for Inventory Design

A complete treatment of Inventory Design contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Inventory Design

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Inventory Design

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Inventory Design is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Inventory Design

This section is not just a definition. In the workshop, Inventory Design is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Inventory Design

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Inventory Design

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Inventory Design

Operations Note for Inventory Design

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Inventory Design is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

4. Playbook Design

Deep Dive and Submission Example for Playbook Design

A complete treatment of Playbook Design contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Playbook Design

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Playbook Design

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Playbook Design is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Playbook Design

This section is not just a definition. In the workshop, Playbook Design is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Playbook Design

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Playbook Design

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Playbook Design

Operations Note for Playbook Design

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Playbook Design is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

5. Module Choice

Deep Dive and Submission Example for Module Choice

A complete treatment of Module Choice contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Module Choice

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Module Choice

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Module Choice is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Module Choice

This section is not just a definition. In the workshop, Module Choice is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Module Choice

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Module Choice

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Module Choice

Operations Note for Module Choice

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Module Choice is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

6. Idempotence

Deep Dive and Submission Example for Idempotence

A complete treatment of Idempotence contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Idempotence

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Idempotence

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Idempotence is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Idempotence

This section is not just a definition. In the workshop, Idempotence is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Idempotence

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Idempotence

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Idempotence

Operations Note for Idempotence

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Idempotence is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

7. Variable Model

Deep Dive and Submission Example for Variable Model

A complete treatment of Variable Model contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Variable Model

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Variable Model

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Variable Model is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Variable Model

This section is not just a definition. In the workshop, Variable Model is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Variable Model

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Variable Model

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Variable Model

Operations Note for Variable Model

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Variable Model is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

8. Templates

Deep Dive and Submission Example for Templates

A complete treatment of Templates contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Templates

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Templates

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Templates is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Templates

This section is not just a definition. In the workshop, Templates is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Templates

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Templates

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Templates

Operations Note for Templates

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Templates is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

9. Roles

Deep Dive and Submission Example for Roles

A complete treatment of Roles contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Roles

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Roles

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Roles is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Roles

This section is not just a definition. In the workshop, Roles is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Roles

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Roles

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Roles

Operations Note for Roles

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Roles is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

10. Collections

Deep Dive and Submission Example for Collections

A complete treatment of Collections contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Collections

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Collections

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Collections is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Collections

This section is not just a definition. In the workshop, Collections is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Collections

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Collections

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Collections

Operations Note for Collections

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Collections is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

11. Secrets

Deep Dive and Submission Example for Secrets

A complete treatment of Secrets contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Secrets

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Secrets

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Secrets is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Secrets

This section is not just a definition. In the workshop, Secrets is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Secrets

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Secrets

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Secrets

Operations Note for Secrets

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Secrets is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

12. Privilege Escalation

Deep Dive and Submission Example for Privilege Escalation

A complete treatment of Privilege Escalation contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Privilege Escalation

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Privilege Escalation

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Privilege Escalation is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Privilege Escalation

This section is not just a definition. In the workshop, Privilege Escalation is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Privilege Escalation

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Privilege Escalation

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Privilege Escalation

Operations Note for Privilege Escalation

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Privilege Escalation is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

13. CI and Linting

Deep Dive and Submission Example for CI and Linting

A complete treatment of CI and Linting contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for CI and Linting

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for CI and Linting

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, CI and Linting is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of CI and Linting

This section is not just a definition. In the workshop, CI and Linting is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for CI and Linting

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for CI and Linting

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for CI and Linting

Operations Note for CI and Linting

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

CI and Linting is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

14. Testing with Molecule

Deep Dive and Submission Example for Testing with Molecule

A complete treatment of Testing with Molecule contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Testing with Molecule

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Testing with Molecule

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Testing with Molecule is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Testing with Molecule

This section is not just a definition. In the workshop, Testing with Molecule is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Testing with Molecule

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Testing with Molecule

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Testing with Molecule

Operations Note for Testing with Molecule

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Testing with Molecule is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

15. Runbooks

Deep Dive and Submission Example for Runbooks

A complete treatment of Runbooks contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Runbooks

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Runbooks

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Runbooks is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Runbooks

This section is not just a definition. In the workshop, Runbooks is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Runbooks

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Runbooks

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Runbooks

Operations Note for Runbooks

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Runbooks is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

16. Anti-Patterns

Deep Dive and Submission Example for Anti-Patterns

A complete treatment of Anti-Patterns contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Anti-Patterns

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Anti-Patterns

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Anti-Patterns is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Anti-Patterns

This section is not just a definition. In the workshop, Anti-Patterns is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Anti-Patterns

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Anti-Patterns

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Anti-Patterns

Operations Note for Anti-Patterns

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Anti-Patterns is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

17. Review Checklist

Deep Dive and Submission Example for Review Checklist

A complete treatment of Review Checklist contains both a technical artifact and a short domain explanation. The artifact can be an inventory, a playbook, a role, a template, a Vault file with dummy values, a CI configuration, or an evidence file. The explanation states why this path was chosen and which alternative was deliberately not used.

Minimal Artifacts for Review Checklist

submission/
  inventory/hosts.yml
  playbooks/site.yml
  evidence.md
  cleanup.md

For roles or collections, the structure expands:

submission/
  ansible.cfg
  collections/requirements.yml
  inventory/hosts.yml
  roles/<role>/defaults/main.yml
  roles/<role>/tasks/main.yml
  roles/<role>/handlers/main.yml
  playbooks/site.yml
  evidence.md

Grading Expectation for Review Checklist

A reviewable solution must be understandable to people who did not run it themselves. Screenshots or uncommented terminal output are not enough. Good evidence states context, command, relevant output, and assessment. If a module behaves differently in check mode, that limitation is explicitly documented.

Transfer to Real Teams

In a team context, Review Checklist is connected to code review, branch rules, CI, role ownership, release notes, and operational approval. Production-like usage also documents ownership, maintenance window, monitoring, alerting, and rollback criteria.

Practical Relevance of Review Checklist

This section is not just a definition. In the workshop, Review Checklist is always validated through a concrete flow: inspect inventory, prove target hosts, check the playbook, simulate the change, run the change, evaluate a second run, and document cleanup. This shows whether Ansible really models desired state or merely executes a command successfully once.

Example Flow for Review Checklist

ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --list-hosts
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff
ansible-playbook -i inventory/hosts.yml playbooks/site.yml
ansible-playbook -i inventory/hosts.yml playbooks/site.yml

The flow is intentionally complete. In real teams, some steps are automated but not skipped. CI can run syntax checks and linting; the domain review of scope, privileges, secret flows, and rollout risk remains a human engineering task.

Review Criteria for Review Checklist

• Inventory and patterns are narrower than all unless a reason is documented.
• Modules from ansible.builtin or reviewed collections are preferred.
• Shell or command tasks include changed_when, failed_when, or a clear reason.
• Variables are placed predictably and do not override each other surprisingly.
• Secrets do not appear in plaintext, diffs, debug tasks, or CI logs.
• The playbook can run repeatedly without unnecessary changes.
• Cleanup, fix-forward, or controlled acceptance of the target state is documented.

Common Failure Modes for Review Checklist

Operations Note for Review Checklist

For production-like usage, the lab must become a runbook. The runbook states target systems, owners, prerequisites, stop criteria, expected duration, validation, monitoring, and cleanup. Without those details, a playbook is executable but not operationally mature.

Review Checklist is a practical building block of the Ansible workshop. The desired state must be described, executed against a controlled scope, and validated before and after the run. A solid Ansible workflow answers four questions: which hosts are targeted, which change is performed, which privileges are required, and how success is measured.

Typical commands:

ansible --version
ansible-config dump --only-changed
ansible-inventory -i inventory/hosts.yml --graph
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --syntax-check
ansible-playbook -i inventory/hosts.yml playbooks/site.yml --check --diff

For reviews, a playbook is ready only when it proves its target scope, exposes its data sources, protects sensitive values, describes failure paths, and remains stable after a second run. If a module does not fully support check mode or diff mode, that limitation belongs in the runbook.

Common mistakes are broad patterns such as all, unclear variable sources, shell workarounds without idempotence, secrets in debug output, missing rollback notes, and missing separation between lab and production inventory.

Sources and Further References

• Official Ansible Community Documentation: https://docs.ansible.com/
• Ansible Getting Started: https://docs.ansible.com/projects/ansible/latest/getting_started/index.html
• Inventory Guide: https://docs.ansible.com/projects/ansible/latest/inventory_guide/index.html
• Playbook Guide: https://docs.ansible.com/projects/ansible/latest/playbook_guide/index.html
• Module Index: https://docs.ansible.com/ansible/latest/collections/ansible/builtin/index.html
• Vault Guide: https://docs.ansible.com/projects/ansible/latest/vault_guide/index.html
• Ansible Lint: https://ansible.readthedocs.io/projects/lint/
• Molecule: https://ansible.readthedocs.io/projects/molecule/
• AWX: https://github.com/ansible/awx
• Red Hat Certifications: https://www.redhat.com/en/services/certifications