Using automation execution

With automation controller you can watch playbooks run in real time, seeing each host as they check in. You can go back and explore the results for specific tasks and hosts in great detail, search for specific plays or hosts and see just those results, or locate errors that need to be corrected.

Use automation controller to access your favorite projects and re-trigger execution from the web interface. Automation controller asks for input variables, prompts for your credentials, starts and monitors jobs, and displays results and host history.

With automation controller you can:

Automation controller records the history of operations and who made them, including objects edited and jobs launched.

If you want to give any user or team permissions to use a job template, you can assign permissions directly on the job template. Credentials are full objects in the automation controller RBAC system, and can be assigned to many users or teams for use.

Automation controller includes an auditor type. A system-level auditor can see all aspects of the systems automation, but does not have permission to run or change automation. An auditor is useful for a service account that scrapes automation information from the REST API.

Automation controller includes a powerful optional provisioning callback feature that enables nodes to request configuration on-demand. This is an ideal solution for a cloud auto-scaling scenario and includes the following features:

The automation controller REST API is the ideal RESTful API for a systems management application, with all resources fully discoverable, paginated, searchable, and well modeled. A styled API browser enables API exploration from the API root at http://<server name>/api/, showing off every resource and relation. Everything that can be done in the user interface can be done in the API.

Ansible Automation Platform can backup and restore your systems or systems, making it easy for you to backup and replicate your instance as required.

By including an Ansible Galaxy requirements.yml file in your project directory, automation controller automatically fetches the roles your playbook needs from Galaxy, GitHub, or your local source control. For more information, see Ansible Galaxy Support.

Dynamic inventory support is available for OpenStack. With this you can target any of the virtual machines or images running in your OpenStack cloud.

For more information, see OpenStack credential type.

Use remote command execution to perform a simple task, such as adding a single user, updating a single security vulnerability, or restarting a failing service. Any task that you can describe as a single Ansible play can be run on a host or group of hosts in your inventory. You can manage your systems quickly and easily. Because of an RBAC engine and detailed audit logging, you know which user has completed a specific task.

You can collect facts by using the fact caching feature. For more information, see Fact Caching.

Keep track of the status of your automation.

You can configure the following notifications:

The following notification sources are supported:

You can also customize notification messages for each of the preceding notification types.

Automation controller supports the following integrations:

For more information, see Red Hat Satellite 6.

For more information, see Setting up Red Hat Insights for Red Hat Ansible Automation Platform Remediations.

With Custom Ansible environment support you can have different Ansible environments and specify custom paths for different teams and jobs.

Automation controller supports:

With LDAP and SAML support you can integrate your enterprise account information in a more flexible manner.

Token-based authentication permits authentication of third-party tools and services with automation controller through integrated OAuth 2 token support.

Run time management of cluster groups enables configurable scaling.

To model your complex provisioning, deployment, and orchestration workflows, you can use automation controller expanded workflows in several ways:

For more information, see Workflows in automation controller.

Take a fact gathering or configuration job running across thousands of machines and divide it into slices that can be distributed across your automation controller cluster. This increases reliability, offers faster job completion, and improved cluster use.

For example, you can change a parameter across 15,000 switches at scale, or gather information across your multi-thousand-node RHEL estate.

For more information, see Job slicing.

Automation controller deploys and runs in restricted modes such as FIPS.

Many large organizations have instances shared among many organizations. To ensure that one organization cannot use all the licensed hosts, this feature enables superusers to set a specified upper limit on how many licensed hosts can that you can allocate to each organization. The automation controller algorithm factors changes in the limit for an organization and the number of total hosts across all organizations. Inventory updates fail if an inventory synchronization brings an organization out of compliance with the policy. Additionally, superusers are able to over-allocate their licenses, with a warning.

The following inventory plugins are used from upstream collections:

With a secret management system, external credentials are stored and supplied for use in automation controller so you need not provide them directly.

The Infrastucture menu provides quick access to the following automation controller resources:

The Administration menu provides access to the administrative options of automation controller. From here, you can create, view, and edit:

You can configure some automation controller options by using the Settings menu of the User Interface.

The Settings page enables an administrator to configure the following:

These searching tips assume that you are not searching hosts.

The following are examples of syntax used for searching:

"related_search_fields": [
       "modified_by__search",
       "project__search",
       "project_update__search",
       "credentials__search",
       "unified_job_template__search",
       "created_by__search",
       "inventory__search",
       "labels__search",
       "schedule__search",
       "webhook_credential__search",
       "job_template__search",
       "job_events__search",
       "dependent_jobs__search",
       "launch_config__search",
       "unifiedjob_ptr__search",
       "notifications__search",
       "unified_job_node__search",
       "instance_group__search",
       "hosts__search",
       "job_host_summaries__search"

Where applicable, use the arrows in each column to sort by ascending order. The following is an example from the schedules list:

The direction of the arrow indicates the sort order of the column.

When an inventory synchronization is executed, the results display in the Output tab.

For more information about inventory synchronization, see Constructed inventories.

If used, the Ansible CLI displays the same information. This can be useful for debugging. The ANSIBLE_DISPLAY_ARGS_TO_STDOUT parameter is set to False for all playbook runs. This parameter matches Ansible’s default behavior and does not display task arguments in task headers in the Job Detail interface to avoid leaking certain sensitive module parameters to stdout. To restore the earlier behavior, set ANSIBLE_DISPLAY_ARGS_TO_STDOUT to True through the AWX_TASK_ENV configuration setting.

For more information, see ANSIBLE_DISPLAY_ARGS_TO_STDOUT in the ansible documentation.

You can Relaunch job, Cancel job, download the job output, or delete the job.

5.1.1. Inventory sync details

Access the Details tab to view details about the job execution:

You can view the following details for an executed job:

• Status: It can be any of the following:

  • Pending: The inventory sync has been created, but not queued or started yet. Any job, not just inventory source syncs, stays in pending until it is ready to be run by the system. Reasons for inventory source syncs not being ready include:

    • Dependencies that are currently running (all dependencies must be completed before the next step can execute).
    • Insufficient capacity to run in the locations it is configured for.
  • Waiting: The inventory sync is in the queue waiting to be executed.
  • Running: The inventory sync is currently in progress.
  • Successful: The inventory sync job succeeded.
  • Failed: The inventory sync job failed.
• Inventory: The name of the associated inventory group.
• Source: The type of cloud inventory.
• Inventory Source Project: The project used as the source of this inventory sync job.
• Execution Environment: The execution environment used.
• Execution node: The node used to execute the job.
• Instance Group: The name of the instance group used with this job (automation controller is the default instance group).

Selecting these items enables you to view the corresponding job templates, projects, and other objects.

When an inventory sourced from an SCM, for example git, is executed, the results are displayed in the Output tab. If used, the Ansible CLI displays the same information. This can be useful for debugging. Use the navigation menu to Relaunch job, Cancel job, download the job output, or delete the job.

When a playbook is executed, the results display in the Output tab. If used, the Ansible CLI displays the same information. This can be useful for debugging.

The events summary displays the following events that are run as part of this playbook:

You can Relaunch job, Cancel job, download the job output, or delete the job.

Hover over a section of the host status bar in the Output view and the number of hosts associated with that status displays.

The output for a playbook job is also available after launching a job from the Jobs tab of its Jobs Templates page. View its host details by clicking the line item tasks in the output.

5.3.1. Search

Use Search to look up specific events, hostnames, and their statuses. To filter only certain hosts with a particular status, specify one of the following valid statuses:

ok

Indicates that a task completed successfully but no change was executed on the host.

changed

The playbook task executed. Since Ansible tasks should be written to be idempotent, tasks can exit successfully without executing anything on the host. In these cases, the task returns ok, but not changed.

failed

The task failed. Further playbook execution stopped for this host.

unreachable

The host is unreachable from the network or has another unrecoverable error associated with it.

skipped

The playbook task skipped because no change was necessary for the host to reach the target state.

rescued

This shows the tasks that failed and then executes a rescue section.

ignored

This shows the tasks that failed and have ignore_errors: yes configured.

The following example shows a search with only unreachable hosts:

For more information on using the search, see the Search section.

The standard output view displays the events that occur on a particular job. By default, all rows are expanded so that the details are displayed. Use the collapse-all ( ) icon to switch to a view that only contains the headers for plays and tasks. Click the plus ( ) icon to view all the lines of the standard output.

You can display all the details of a specific play or task by clicking the arrow icons next to them. Click an arrow from sideways to downward to expand the lines associated with that play or task. Click the arrow back to the sideways position to collapse and hide the lines.

When viewing details in the expand or collapse mode, note the following:

• Each displayed line that is not collapsed has a corresponding line number and start time.
• An expand or collapse icon is at the start of any play or task after the play or task has completed.
• If querying for a particular play or task, it appears collapsed at the end of its completed process.
• In some cases, an error message appears, stating that the output may be too large to display. This occurs when there are more than 4000 events. Use the search and filter for specific events to bypass the error.

Click on a line of an event from the Stdout pane and a Host Events window displays in a separate window. This window shows the host that was affected by that particular event.

Note

Upgrading to the latest versions of Ansible Automation Platform involves progressively migrating all historical playbook output and events. This migration process is gradual, and happens automatically in the background after installation is complete. Installations with very large amounts of historical job output (tens or hundreds of GB of output) can have missing job output until migration is complete. The most recent data shows up at the top of the output, followed by older events.

5.3.2. Playbook run details

Access the Details tab to view details about the job execution:

You can view the following details for an executed job:

• Status: It can be any of the following:

  • Pending: The playbook run has been created, but not queued or started yet. Any job, not just playbook runs, stay in pending until it is ready to be run by the system. Reasons for playbook runs not being ready include dependencies that are currently running (all dependencies must be completed before the next step can execute), or there is not enough capacity to run in the locations it is configured to.
  • Waiting: The playbook run is in the queue waiting to be executed.
  • Running: The playbook run is currently in progress.
  • Successful: The last playbook run succeeded.
  • Failed: The last playbook run failed.
• Job Template: The name of the job template from which this job launched.
• Inventory: The inventory selected to run this job against.
• Project: The name of the project associated with the launched job.
• Project Status: The status of the project associated with the launched job.
• Playbook: The playbook used to launch this job.
• Execution Environment: The name of the execution environment used in this job.
• Container Group: The name of the container group used in this job.
• Credentials: The credentials used in this job.
• Extra Variables: Any extra variables passed when creating the job template are displayed here.

Select one of these items to view the corresponding job templates, projects, and other objects.

5.3.4. Isolation functionality and variables

Automation controller uses container technology to isolate jobs from each other. By default, only the current project is exposed to the container running a job template.

If you need to expose additional directories, you must customize your playbook runs. To configure job isolation, you can set variables.

By default, automation controller uses the system’s tmp directory (/tmp by default) as its staging area. This can be changed in the Job Execution Path field of the Jobs settings page, or in the REST API at /api/v2/settings/jobs:

AWX_ISOLATION_BASE_PATH = "/opt/tmp"

If there are any additional directories that should specifically be exposed from the host to the container that playbooks run in, you can specify those in the Paths to expose to isolated jobs field of the Jobs Settings page, or in the REST API at /api/v2/settings/jobs:

AWX_ISOLATION_SHOW_PATHS = ['/list/of/', '/paths']

Note

If your playbooks need to use keys or settings defined in AWX_ISOLATION_SHOW_PATHS, then add this file to /var/lib/awx/.ssh.

The fields described here can be found on the Jobs settings page:

The automation controller capacity system determines how many jobs can run on an instance given the amount of resources available to the instance and the size of the jobs that are running (referred to as Impact). The algorithm used to determine this is based on the following two things:

Capacity also impacts instance groups. Since groups are made up of instances, instances can also be assigned to multiple groups. This means that impact to one instance can affect the overall capacity of other groups.

Instance groups, not instances themselves, can be assigned to be used by jobs at various levels. For more information, see Clustering in Configuring automation execution.

When the Task Manager prepares its graph to determine which group a job runs on, it commits the capacity of an instance group to a job that is not ready to start yet.

In smaller configurations, if only one instance is available for a job to run, the Task Manager enables that job to run on the instance even if it pushes the instance over capacity. This guarantees that jobs do not get stuck as a result of an under-provisioned system.

(mem - 2048) / mem_per_fork

(4096 - 2048) / 100 == ~20

cpus * fork_per_cpu

4 * 4 == 16

16 + (20 - 16) * 0.5 = 18

Projects specify the branch, tag, or reference to use from source control in the scm_branch field. These are represented by the values specified in the Type Details fields:

When creating or editing a job you have the option to Allow branch override. When this option is checked, project administrators can delegate branch selection to the job templates that use that project, requiring only project use_role.

Creating the template does not exit the job template page but advances to the Job Template Details tab. After saving the template, you can click Launch template to start the job. You can also click Edit to add or change the attributes of the template, such as permissions, notifications, view completed jobs, and add a survey (if the job type is not a scan). You must first save the template before launching, otherwise, Launch template remains disabled.

Use the following steps to add permissions for the team.

The window to add users and teams closes to display the updated roles assigned for each user and team

To remove roles for a particular user, click the icon next to its resource.

This launches a confirmation dialog, asking you to confirm the disassociation.

Before deleting a job template, ensure that it is not used in a workflow job template.

From the navigation panel, select Automation Execution → Administration → Notifiers. You can review any notification integrations you have set up and their statuses, if they have run.

Use the toggles to enable or disable the notifications to use with your particular template. For more information, see Enable and disable notifications.

If no notifications have been set up, click Add notifier to create a new notification. For more information about configuring various notification types and extended messaging, see Notification types.

The Jobs tab provides the list of job templates that have run. Click the expand icon next to each job to view the following details:

You can filter the list of completed jobs using any of these criteria.

Sliced jobs that display on this list are labeled accordingly, with the number of sliced jobs that have run.

Access the schedules for a particular job template from the Schedules tab.

If you select Prompt on Launch for the Credentials field, and you create or edit scheduling information for your job template, a Prompt option displays on the Schedules form.

You cannot remove the default machine credential in the Prompt dialog without replacing it with another machine credential before you can save it.

Job types of Run or Check provide a way to set up surveys in the Job Template creation or editing screens. Surveys set extra variables for the playbook similar to Prompt for Extra Variables does, but in a user-friendly question and answer way. Surveys also permit for validation of user input. Select the Survey tab to create a survey.

You can ask many types of questions, including multiple-choice questions.

A benefit of automation controller is the push-button deployment of Ansible playbooks. You can configure a template to store all the parameters that you would normally pass to the Ansible Playbook on the command line. In addition to the playbooks, the template passes the inventory, credentials, extra variables, and all options and settings that you can specify on the command line.

Easier deployments drive consistency, by running your playbooks the same way each time, and allowing you to delegate responsibilities.

A job can require additional information to run. The following data can be requested at launch:

If you give values on one tab, return to a previous tab, continuing to the next tab results in having to re-provide values on the rest of the tabs. Ensure that you complete the tabs in the order that the prompts appear.

When launching, automation controller automatically redirects the web browser to the Job Status page for this job under the Jobs tab.

You can re-launch the most recent job from the list view to re-run on all hosts or just failed hosts in the specified inventory. For more information, see the Jobs in automation controller section.

When slice jobs are running, job lists display the workflow and job slices, and a link to view their details individually.

If you copy a job template, it does not copy any associated schedule, notifications, or permissions. Schedules and notifications must be recreated by the user or administrator creating the copy of the job template. The user copying the Job Template is granted administrator permission, but no permissions are assigned (copied) to the job template.

Scan jobs are no longer supported starting with automation controller 3.2. This system tracking feature was used as a way to capture and store facts as historical data. Facts are now stored in the controller through fact caching. For more information, see Fact Caching.

Job template scan jobs in your system before automation controller 3.2, are converted to type run, like normal job templates. They retain their associated resources, such as inventories and credentials. By default, job template scan jobs that do not have a related project are assigned a special playbook. You can also specify a project with your own scan playbook. A project is created for each organization that points to awx-facts-playbooks and the job template was set to the playbook: https://github.com/ansible/tower-fact-modules/blob/master/scan_facts.yml.

6.10.1. Fact scan playbooks

The scan job playbook, scan_facts.yml, contains invocations of three fact scan modules - packages, services, and files, along with Ansible’s standard fact gathering. The scan_facts.yml playbook file is similar to this:

- hosts: all
  vars:
    scan_use_checksum: false
    scan_use_recursive: false
  tasks:
    - scan_packages:
    - scan_services:
    - scan_files:
        paths: '{{ scan_file_paths }}'
        get_checksum: '{{ scan_use_checksum }}'
        recursive: '{{ scan_use_recursive }}'
      when: scan_file_paths is defined

The scan_files fact module is the only module that accepts parameters, passed through extra_vars on the scan job template:

scan_file_paths: /tmp/scan_use_checksum: true scan_use_recursive: true

• The scan_file_paths parameter can have multiple settings (such as /tmp/ or /var/log).
• The scan_use_checksum and scan_use_recursive parameters can also be set to false or omitted. An omission is the same as a false setting.

Scan job templates should enable become and use credentials for which become is a possibility. You can enable become by checking Privilege Escalation from the options list:

Bootstrap Ubuntu (16.04)
---
- name: Get Ubuntu 16, and on ready
 hosts: all
 sudo: yes
 gather_facts: no
 tasks:
 - name: install python-simplejson
   raw: sudo apt-get -y update
   raw: sudo apt-get -y install python-simplejson
   raw: sudo apt-get install python-apt

Bootstrap Fedora (23, 24)
---
- name: Get Fedora ready
 hosts: all
 sudo: yes
 gather_facts: no
 tasks:
 - name: install python-simplejson
   raw: sudo dnf -y update
   raw: sudo dnf -y install python-simplejson
   raw: sudo dnf -y install rpm-python

scan_foo.py:
def main():
    module = AnsibleModule(
        argument_spec = dict())


    foo = [
      {
        "hello": "world"
      },
      {
        "foo": "bar"
      }
    ]
    results = dict(ansible_facts=dict(foo=foo))
    module.exit_json(**results)


main()

[
   {
     "hello": "world"
   },
   {
     "foo": "bar"
   }
 ]

- hosts: all
  gather_facts: false
  tasks:
    - name: Clear gathered facts from all currently targeted hosts
      meta: clear_facts

Cloud Credentials can be used when syncing a cloud inventory. They can also be associated with a job template and included in the runtime environment for use by a playbook. The following Cloud Credentials are supported:

clouds:
  devstack:
    auth:
      auth_url: http://devstack.yoursite.com:5000/v2.0/
      username: admin
      password: your_password_here
      project_name: demo

- hosts: all
  gather_facts: false
  vars:
    config_file: "{{ lookup('env', 'OS_CLIENT_CONFIG_FILE') }}"
    nova_tenant_name: demo
    nova_image_name: "cirros-0.3.2-x86_64-uec"
    nova_instance_name: autobot
    nova_instance_state: 'present'
    nova_flavor_name: m1.nano


    nova_group:
      group_name: antarctica
      instance_name: deceptacon
      instance_count: 3
  tasks:
    - debug: msg="{{ config_file }}"
    - stat: path="{{ config_file }}"
      register: st
    - include_vars: "{{ config_file }}"
      when: st.stat.exists and st.stat.isreg


    - name: "Print out clouds variable"
      debug: msg="{{ clouds|default('No clouds found') }}"


    - name: "Setting nova instance state to: {{ nova_instance_state }}"
      local_action:
        module: nova_compute
        login_username: "{{ clouds.devstack.auth.username }}"
        login_password: "{{ clouds.devstack.auth.password }}"

- vsphere_guest:
    vcenter_hostname: "{{ lookup('env', 'VMWARE_HOST') }}"
    username: "{{ lookup('env', 'VMWARE_USER') }}"
    password: "{{ lookup('env', 'VMWARE_PASSWORD') }}"
    guest: newvm001
    from_template: yes
    template_src: linuxTemplate
    cluster: MainCluster
    resource_pool: "/Resources"
    vm_extra_config:
      folder: MyFolder

Provisioning Callbacks are a feature of automation controller that enable a host to start a playbook run against itself, rather than waiting for a user to launch a job to manage the host from the automation controller console.

Provisioning Callbacks are only used to run playbooks on the calling host and are meant for cloud bursting. Cloud bursting is a cloud computing configuration that enables a private cloud to access public cloud resources by "bursting" into a public cloud when computing demand spikes.

The job template launched only runs against the host requesting the provisioning.

This is often accessed with a firstboot type script or from cron.

./request_tower_configuration.sh -h
Usage: ./request_tower_configuration.sh <options>


Request server configuration from Ansible Tower.


OPTIONS:
 -h      Show this message
 -s      Controller server (e.g. https://ac.example.com) (required)
 -k      Allow insecure SSL connections and transfers
 -c      Host config key (required)
 -t      Job template ID (required)
 -e      Extra variables

When you pass survey variables, they are passed as extra variables (extra_vars) within automation controller. However, passing extra variables to a job template (as you would do with a survey) can override other variables being passed from the inventory and project.

By default, extra_vars are marked as !unsafe unless you specify them on the Job Template’s Extra Variables section. These are trusted, because they can only be added by users with enough privileges to add or edit a Job Template. For example, nested variables do not expand when entered as a prompt, as the Jinja brackets are treated as a string. For more information about unsafe variables, see Unsafe or raw strings.

To ensure the variables that you pass are not overridden, ensure they are included by redefining them in the survey. You can define extra variables at the inventory, group, and host levels.

If you are specifying the ALLOW_JINJA_IN_EXTRA_VARS parameter, see the The ALLOW_JINJA_IN_EXTRA_VARS variable section of Configuring automation execution to configure it.

The job template extra variables dictionary is merged with the survey variables.

The following are some simplified examples of extra_vars in YAML and JSON formats:

launch_to_orbit: true
satellites:
  - sputnik
  - explorer
  - satcom

{
  "launch_to_orbit": true,
  "satellites": ["sputnik", "explorer", "satcom"]
}

The following table notes the behavior (hierarchy) of variable precedence in automation controller as it compares to variable precedence in Ansible.

When setting up job slices, consider the following:

When jobs are sliced, they can run on any node. Insufficient capacity in the system can cause some to run at a different time. When slice jobs are running, job details display the workflow and job slices currently running, and a link to view their details individually.

By default, job templates are not normally configured to execute simultaneously (you must check allow_simultaneous in the API or Concurrent jobs in the UI). Slicing overrides this behavior and implies allow_simultaneous even if that setting is clear. See Job templates for information about how to specify this, and the number of job slices on your job template configuration.

The Job templates section provides additional detail on performing the following operations in the UI:

To make it easier to find slice jobs, use the search functionality to apply a search filter to:

To create a new workflow job template, complete the following steps:

Saving the template exits the workflow template page and the workflow visualizer opens where you can build a workflow. For more information, see the Workflow visualizer section. Otherwise, select one of these methods:

Click the Team Access or User Access tab to review, grand, edit, and remove associated permissions for users along with team members.

Click Add roles to create new permissions for this workflow template by following the prompts to assign them.

For information on working with notifications in workflow job templates, see Work with notifications.

The Jobs tab provides the list of job templates that have run. Click the expand icon next to each job to view the details of each job.

From this view, you can click the job ID, name of the workflow job and see its graphical representation. The following example shows the job details of a workflow job:

The nodes are marked with labels to help you identify them. For more information, see the legend in the Workflow visualizer section.

Select the Schedules tab to access the schedules for a particular workflow job template..

For more information about scheduling a workflow job template run, see the Scheduling job templates section.

If a workflow job template used in a nested workflow has a survey, or the Prompt on launch is selected for the inventory option, the PROMPT option displays next to the SAVE and CANCEL options on the schedule form. Click PROMPT to show an optional INVENTORY step where you can give or remove an inventory or skip this step without any changes.

Workflows containing job types of Run or Check provide a way to set up surveys in the workflow job template creation or editing screens.

For more information on job surveys, including how to create a survey and optional survey questions in workflow job templates, see the Surveys in job templates section.

The Workflow Visualizer provides a graphical way of linking together job templates, workflow templates, project syncs, and inventory syncs to build a workflow template. Before you build a workflow template, see the Workflows in automation controller section for considerations associated with various scenarios on parent, child, and sibling nodes.

8.7.2. Approval nodes

Choosing an Approval node requires your intervention in order to advance a workflow. This functions as a means to pause the workflow in between playbooks so that you can give approval to continue on to the next playbook in the workflow. This gives the user a specified amount of time to intervene, but also enables you to continue as quickly as possible without having to wait on another trigger.

The default for the timeout is none, but you can specify the length of time before the request expires and is automatically denied. After you select and supply the information for the approval node, it displays on the graphical view with a pause icon beside it.

The approver is anyone who meets the following criteria:

• A user that can execute the workflow job template containing the approval nodes.
• A user who has organization administrator or above privileges (for the organization associated with that workflow job template).
• A user who has the Approve permission explicitly assigned to them within that specific workflow job template.

If pending approval nodes are not approved within the specified time limit (if an expiration was assigned) or they are denied, then they are marked as "timed out" or "failed", and move on to the next "on fail node" or "always node". If approved, the "on success" path is taken. If you try to POST in the API to a node that has already been approved, denied or timed out, an error message notifies you that this action is redundant, and no further steps are taken.

The following table shows the various levels of permissions allowed on approval workflows:

8.7.3. Building nodes scenarios

Learn how to manage nodes in the following scenarios.

Procedure

• Click the ( ) icon on the parent node to add a sibling node:

• Hover over the line that connects two nodes and click the plus ( ), to insert another node in between nodes. Clicking the plus ( ) icon automatically inserts the node between the two nodes:

• Click START again, to add a root node to depict a split scenario:

• At any node where you want to create a split scenario, hover over the node from which the split scenario begins and click the plus ( ) icon. This adds multiple nodes from the same parent node, creating sibling nodes:

Note

When adding a new node, the PROMPT option also applies to workflow templates. Workflow templates prompt for inventory and surveys.

• You can undo the last inserted node by using one of these methods:

  • Click on another node without making a selection.
  • Click Cancel.

The following example workflow contains all three types of jobs initiated by a job template. If it fails to run, you must protect the sync job. Regardless of whether it fails or succeeds, proceed to the inventory sync job:

Refer to the key by clicking the compass ( ) icon to identify the meaning of the symbols and colors associated with the graphical depiction.

Note

If you remove a node that has a follow-on node attached to it in a workflow with a set of sibling nodes that has varying edge types, the attached node automatically joins the set of sibling nodes and retains its edge type:

Variables added for a workflow job template are automatically added in automation controller when launching, along with any extra variables set in the workflow job template and survey.

Events related to approvals on workflows are displayed in the activity stream ( ) with detailed information about the approval requests, if any.

With automation controller you can copy a workflow job template. When you copy a workflow job template, it does not copy any associated schedule, notifications, or permissions. Schedules and notifications must be recreated by the user or system administrator creating the copy of the workflow template. The user copying the workflow template is granted the administrator permission, but no permissions are assigned (copied) to the workflow template.

For more information see the Extra variables section.

When building workflows, consider the following:

Workflows use surveys to specify variables to be used in the playbooks in the workflow, called extra_vars. Survey variables are combined with extra_vars defined on the workflow job template, and saved to the workflow job extra_vars. extra_vars in the workflow job are combined with job template variables when spawning jobs within the workflow.

Workflows use the same behavior (hierarchy) of variable precedence as job templates with the exception of three additional variables. See the Automation controller Variable Precedence Hierarchy in the Extra variables section of Job templates. The three additional variables include:

Workflows included in a workflow follow the same variable precedence, they only inherit variables if they are specifically prompted for, or defined as part of a survey.

In addition to the workflow extra_vars, jobs and workflows run as part of a workflow can inherit variables in the artifacts dictionary of a parent job in the workflow (also combining with ancestors further upstream in its branch). These can be defined by the set_stats Ansible module.

If you use the set_stats module in your playbook, you can produce results that can be consumed downstream by another job.

---
- hosts: localhost
  tasks:
    - name: "Artifact integration test results to the web"
      local_action: 'shell curl -F "file=@integration_results.txt" https://file.io'
      register: result


    - name: "Artifact URL of test results to Workflows"
      set_stats:
        data:
          integration_results_url:  "{{ (result.stdout|from_json).link }}"

---
- hosts: localhost
  tasks:
    - name: "Get test results from the web"
      uri:
        url: "{{ integration_results_url }}"
        return_content: true
      register: results


    - name: "Output test results"
      debug:
        msg: "{{ results.content }}"

The set_stats module processes this workflow as follows:

The workflow job can have the following states (no Failed state):

In the workflow scheme, canceling a job cancels the branch, while canceling the workflow job cancels the entire workflow.

To edit and delete a workflow job template, you must have the administrator role. To create a workflow job template, you must be an organization administrator or a system administrator. However, you can run a workflow job template that contains job templates that you do not have permissions for. System administrators can create a blank workflow and then grant an admin_role to a low-level user, after which they can delegate more access and build the graph. You must have execute access to a job template to add it to a workflow job template.

You can also perform other tasks, such as making a duplicate copy or re-launching a workflow, depending on which permissions are granted to a user. You must have permissions to all the resources used in a workflow, such as job templates, before relaunching or making a copy.

For more information, see Managing access with role based access control.

For more information about performing the tasks described, see Workflow job templates.

You can create schedules from a template, project, or inventory source, and directly on the main Schedules page.

To create a new schedule on the Schedules page:

To create a new schedule from a resource page:

You can create a logical collection of playbooks, called projects in automation controller.

The set of permissions assigned to a project (role-based access controls) that provide the ability to read, change, and administer projects, inventories, job templates, and other elements are privileges.

To access the project permissions, select the Access tab of the Projects page. This screen displays a list of users that currently have permissions to this project.

You can sort and search this list by Username, First Name, or Last Name.

At the end of a project update, automation controller searches for the requirements.yml file in the roles directory, located at <project-top-level-directory>/roles/requirements.yml.

If this file is found, the following command automatically runs:

ansible-galaxy role install -r roles/requirements.yml -p <project-specific cache location>/requirements_roles -vvv

This file enables you to reference Ansible Galaxy roles or roles within other repositories which can be checked out in conjunction with your own project. The addition of Ansible Galaxy access eliminates the need to create git submodules to achieve this result. Given that SCM projects, along with roles or collections, are pulled into and executed from a private job environment, a <private job directory> specific to the project within /tmp is created by default.

The cache directory is a subdirectory inside the global projects folder. You can copy the content from the cache location to <job private directory>/requirements_roles.

By default, automation controller has a system-wide setting that enables you to dynamically download roles from the roles/requirements.yml file for SCM projects. You can turn off this setting in the Job Settings screen from the navigation panel Settings → Job, by switching the Enable Role Download toggle to Off.

Whenever a project synchronization runs, automation controller determines if the project source and any roles from Galaxy or Collections are out of date with the project. Project updates download the roles inside the update.

If jobs need to pick up a change made to an upstream role, updating the project ensures that this happens. A change to the role means that a new commit was pushed to the provision-role source control.

To make this change take effect in a job, you do not have to push a new commit to the playbooks repository. You must update the project, which downloads roles to a local cache.

For instance, say you have two git repositories in source control. The first one is playbooks and the project in automation controller points to this URL. The second one is provision-role and it is referenced by the roles/requirements.yml file inside of the playbooks git repository.

Jobs download the most recent roles before every job run. Roles and collections are locally cached for performance reasons. You must select Update Revision on Launch in the project Options to ensure that the upstream role is re-downloaded before each job run:

The update happens much earlier in the process than the sync, so this identifies errors and details faster and in a more logical location.

For more information and examples on the syntax of the requirements.yml file, see the role requirements section in the Ansible documentation.

If there are any directories that must be specifically exposed, you can specify those in the Job Settings screen from the navigation panel Settings → Job, in Paths to Expose to isolated Jobs. You can also update the following entry in the settings file:

AWX_ISOLATION_SHOW_PATHS = ['/list/of/', '/paths']

If you made changes in the settings file, be sure to restart services with the automation-controller-service restart command after your changes have been saved.

In the UI, you can configure these settings in the Jobs Settings window.

Automation controller supports project-specific Ansible collections in job runs. If you specify a collections requirements file in the SCM at collections/requirements.yml, automation controller installs collections in that file in the implicit project synchronization before a job run.

Automation controller has a system-wide setting that enables collections to be dynamically downloaded from the collections/requirements.yml file for SCM projects. You can turn off this setting in the Job Settings screen from the navigation panel Settings → Job, by switching the Enable Collection(s) Download toggle button to Off.

Roles and collections are locally cached for performance reasons, and you select Update Revision on Launch in the project Options to ensure this:

To use the GPG key for content signing and validation in automation controller, add it by running the following command in the CLI:

$ gpg --list-keys
$ gpg --export --armour <key fingerprint> > my_public_key.asc

Use the ansible-sign utility to provide options for the user to sign and verify whether the project is signed.

Signing a project involves an Ansible project directory. For more information on project directory structures, see Sample Ansible setup in the Ansible documentation.

The following sample project has a very simple structure: an inventory file, and two small playbooks under a playbooks directory:

$ cd sample-project/
$ tree -a .
.
├── inventory
└── playbooks
    └── get_uptime.yml
    └── hello.yml

    1 directory, 3 files

ansible-sign protects content from tampering by taking checksums (SHA256) of all of the secured files in the project, compiling those into a checksum manifest file, and then signing that manifest file.

To sign content, create a MANIFEST.in file in the project root directory that tells ansible-sign which files to protect.

Internally, ansible-sign uses the distlib.manifest module of Python’s distlib library, therefore MANIFEST.in must follow the syntax that this library specifies. For an explanation of the MANIFEST.in file directives, see the Python Packaging User Guide.

In the sample project, two directives are included, resulting in the following MANIFEST.in file:

include inventory
recursive-include playbooks *.yml

With this file in place, generate your checksum manifest file and sign it. Both of these steps are achieved in a single ansible-sign command:

$ ansible-sign project gpg-sign .

Successful execution displays output similar to the following:

[OK   ] GPG signing successful!
[NOTE ] Checksum manifest: ./.ansible-sign/sha256sum.txt
[NOTE ] GPG summary: signature created

The project has now been signed.

Note that the gpg-sign subcommand resides under the project subcommand.

For signing project content, every command starts with ansible-sign project.

Every ansible-sign project command takes the project root directory . as its final argument.

ansible-sign makes use of your default keyring and looks for the first available secret key that it can find, to sign your project. You can specify a specific secret key to use with the --fingerprint option, or even a completely independent GPG home directory with the --gnupg-home option.

Note that an .ansible-sign directory was created in the project directory. This directory contains the checksum manifest and a detached GPG signature for it.

$ tree -a .
.
├── .ansible-sign
│   ├── sha256sum.txt
│   └── sha256sum.txt.sig
├── inventory
├── MANIFEST.in
└── playbooks
    ├── get_uptime.yml
    └── hello.yml

To verify that a signed Ansible project has not been altered, you can use ansible-sign to check whether the signature is valid and that the checksums of the files match what the checksum manifest says they should be. The ansible-sign project gpg-verify command can be used to automatically verify both of these conditions.

$ ansible-sign project gpg-verify .
[OK   ] GPG signature verification succeeded.
[OK   ] Checksum validation succeeded.

If verification fails for any reason, information is displayed to help you debug the cause. More verbosity can be enabled by passing the global --debug flag, immediately after ansible-sign in your commands.

In environments with highly-trusted Continuous Integration (CI) environments such as OpenShift or Jenkins, it is possible to automate the signing process.

For example, you can store your GPG private key in a CI platform of choice as a secret, and import that into GnuPG in the CI environment. You can then run through the signing workflow within the normal CI environment.

When signing a project using GPG, the environment variable ANSIBLE_SIGN_GPG_PASSPHRASE can be set to the passphrase of the signing key. This can be injected and masked or secured in a CI pipeline.

Depending on the scenario, ansible-sign returns with a different exit-code, during both signing and verification. This can also be useful in the context of CI and automation, as a CI environment can act differently based on the failure. For example, it can send alerts for some errors, but fail silently for others.

These are the current exit codes used in ansible-sign, which can be considered stable:

Use the following procedure to access the topology viewer from the automation controller UI.

Smart Inventories are collections of hosts defined by a stored search that can be viewed like a standard inventory and can be easily used with job runs. Organization administrators have admin permission for inventories in their organization and can create Smart Inventories.

A Smart Inventory is identified by KIND=smart.

You can define a Smart Inventory using the same method being used with Search. InventorySource is directly associated with an Inventory.

The Inventory model has the following new fields that are blank by default but are set accordingly for Smart Inventories:

The host model has a related endpoint, smart_inventories that identifies a set of all the Smart Inventories a host is associated with. The membership table is updated every time a job runs against a smart inventory.

You can view inventories without being editable:

You cannot create hosts from a Smart Inventory host endpoint (/inventories/N/hosts/) as with a normal inventory. The administrator of a Smart Inventory has permission to edit fields such as the name, description, variables, and the ability to delete, but does not have the permission to modify the host_filter, because that affects which hosts (that have a primary membership inside another inventory) are included in the smart inventory.

host_filter only applies to hosts inside of inventories inside the Smart Inventory’s organization.

To modify host_filter, you must be the organization administrator of the inventory’s organization. Organization administrators have implicit "admin" access to all inventories inside the organization, therefore, this does not convey any permissions they did not already possess.

Administrators of the Smart Inventory can grant other users (who are not also admins of your organization) permissions such as "use" and "adhoc" to the smart inventory. These permit the actions indicated by the role, as with other standard inventories. However, this does not grant any special permissions to hosts (which live in a different inventory). It does not permit direct read permission to hosts, or permit them to see additional hosts under /#/hosts/, although they can still view the hosts under the smart inventory host list.

In some situations, you can modify the following:

Hosts associated with the Smart Inventory are manifested at view time. If the results of a Smart Inventory contains more than one host with identical hostnames, only one of the matching hosts is included as part of the Smart Inventory, ordered by Host ID.

/api/v2/hosts?host_filter=ansible_facts__ansible_processor_vcpus=8

/api/v2/hosts/?host_filter=name=localhost
/api/v2/hosts/?host_filter=ansible_facts__ansible_date_time__weekday_number="3"
/api/v2/hosts/?host_filter=ansible_facts__ansible_processor[]="GenuineIntel"
/api/v2/hosts/?host_filter=ansible_facts__ansible_lo__ipv6[]__scope="host"
/api/v2/hosts/?host_filter=ansible_facts__ansible_processor_vcpus=8
/api/v2/hosts/?host_filter=ansible_facts__ansible_env__PYTHONUNBUFFERED="true"
/api/v2/hosts/?host_filter=(name=localhost or name=database) and (groups__name=east or groups__name="west coast") and ansible_facts__an

groups.name:groupA

ansible_facts.ansible_fips:false

host_filter=name=my_host

host_filter=ansible_facts__packages__dnsmasq[]__version="2.66"

You can create a new inventory (called a constructed inventory) from a list of input inventories.

A constructed inventory has copies of hosts and groups in its input inventories, permitting jobs to target groups of servers across many inventories. Groups and hostvars can be added to the inventory content, and hosts can be filtered to limit the size of the constructed inventory.

Constructed inventories use the ansible.builtin.constructed inventory model.

The key factors of a constructed inventory are:

Constructed inventories take source_vars and limit as inputs and transform its input_inventories into a new inventory, complete with groups. Groups (existing or constructed) can then be referenced in the limit field to reduce the number of hosts produced.

You can construct groups based on these host properties:

The examples described in later sections are organized by the structure of the input inventories.

[account_1234]
host1
host2 state=shutdown

[account_4321]
host3
host4 state=shutdown

[account_1234:vars]
account_alias=product_dev

[account_4321:vars]
account_alias=sustaining

source_vars:

plugin: constructed
strict: true
groups:
  shutdown_in_product_dev: state | default("running") == "shutdown" and account_alias == "product_dev"
compose:
  resolved_state: state | default("running")
  is_in_product_dev: account_alias == "product_dev"

limit: ``

all:
  children:
    groupA:
      vars:
        filter_var: filter_val
      children:
        groupB:
          hosts:
            host1: {}
    ungrouped:
      hosts:
        host2: {}

`source_vars`:

plugin: constructed

`limit`: `groupA`

source_vars:

plugin: constructed
strict: true
groups:
  filter_var_is_filter_val: filter_var | default("") == "filter_val"

limit: filter_var_is_filter_val

source_vars:

plugin: constructed
strict: true
groups:
  hosts_using_xterm: ansible_env.TERM == "xterm"

limit: hosts_using_xterm

source_vars:

plugin: constructed
strict: true
groups:
  intel_hosts: "GenuineIntel" in ansible_processor

limit: intel_hosts

Inventory updates use dynamically-generated YAML files which are parsed by their inventory plugin. In automation controller v4.4, you can provide the inventory plugin configuration directly to automation controller using the inventory source source_vars for the following inventory sources:

Newly created configurations for inventory sources contain the default plugin configuration values. If you want your newly created inventory sources to match the output of a legacy source, you must apply a specific set of configuration values for that source. To ensure backward compatibility, automation controller uses "templates" for each of these sources to force the output of inventory plugins into the legacy format.

For more information about sources and their templates, see Supported inventory plugin templates.

source_vars that contain plugin: foo.bar.baz as a top-level key are replaced with the fully-qualified inventory plugin name at runtime based on the InventorySource source. For example, if you select ec2 for the InventorySource then, at run-time, plugin is set to amazon.aws.aws_ec2.

Adding a new inventory involves the following components:

Use the following procedure to create a inventory:

After saving the new inventory, you can proceed with configuring permissions, groups, hosts, sources, and view completed jobs, if applicable to the type of inventory.

$ awx-manage export_custom_scripts --filename=my_scripts.tar

Dump of old custom inventory scripts at my_scripts.tar

$ mkdir my_scripts
$ tar -xf my_scripts.tar -C my_scripts

$ ls my_scripts
10inventory_script_rawhook _19 _30inventory_script_listenhospital _11inventory_script_upperorder _1inventory_script_commercialinternet45 _4inventory_script_whitestring _12inventory_script_eastplant _22inventory_script_pinexchange _5inventory_script_literaturepossession _13inventory_script_governmentculture _23inventory_script_brainluck _6inventory_script_opportunitytelephone _14inventory_script_bottomguess _25inventory_script_buyerleague _7inventory_script_letjury _15inventory_script_wallisland _26inventory_script_lifesport _8random_inventory_script
16inventory_script_wallisland _27inventory_script_exchangesomewhere _9random_inventory_script _17inventory_script_bidstory            _28inventory_script_boxchild _18p                                    _29__inventory_script_wearstress

$ ./my_scripts/11__inventory_script_upperorder {"group\ud801\udcb0\uc20e\u7b0e\ud81c\udfeb\ub12b\ub4d0\u9ac6\ud81e\udf07\u6ff9\uc17b": {"hosts":
["host_\ud821\udcad\u68b6\u7a51\u93b4\u69cf\uc3c2\ud81f\uddbe\ud820\udc92\u3143\u62c7",
"host_\u6057\u3985\u1f60\ufefb\u1b22\ubd2d\ua90c\ud81a\udc69\u1344\u9d15",
"host_\u78a0\ud820\udef3\u925e\u69da\ua549\ud80c\ude7e\ud81e\udc91\ud808\uddd1\u57d6\ud801\ude57",
"host_\ud83a\udc2d\ud7f7\ua18a\u779a\ud800\udf8b\u7903\ud820\udead\u4154\ud808\ude15\u9711",
"host_\u18a1\u9d6f\u08ac\u74c2\u54e2\u740e\u5f02\ud81d\uddee\ufbd6\u4506"], "vars": {"ansible_host": "127.0.0.1", "ansible_connection":
"local"}}}

$ ansible-inventory -i ./my_scripts/_11__inventory_script_upperorder --list --export

If you use an inventory to run a job, you can view details about those jobs in the Jobs tab of the inventory and click Expanded to view details about each job.

Ad hoc refers to using Ansible to perform a quick command, using /usr/bin/ansible, rather than the orchestration language, which is /usr/bin/ansible-playbook. An example of an ad hoc command might be rebooting 50 machines in your infrastructure. Anything you can do ad hoc can be accomplished by writing a playbook. Playbooks can also glue many other operations together.

Use the following procedure to run an ad hoc command:

compose:
  ansible_host: public_ip_address
  ec2_account_id: owner_id
  ec2_ami_launch_index: ami_launch_index | string
  ec2_architecture: architecture
  ec2_block_devices: dict(block_device_mappings | map(attribute='device_name') | list | zip(block_device_mappings | map(attribute='ebs.volume_id') | list))
  ec2_client_token: client_token
  ec2_dns_name: public_dns_name
  ec2_ebs_optimized: ebs_optimized
  ec2_eventsSet: events | default("")
  ec2_group_name: placement.group_name
  ec2_hypervisor: hypervisor
  ec2_id: instance_id
  ec2_image_id: image_id
  ec2_instance_profile: iam_instance_profile | default("")
  ec2_instance_type: instance_type
  ec2_ip_address: public_ip_address
  ec2_kernel: kernel_id | default("")
  ec2_key_name: key_name
  ec2_launch_time: launch_time | regex_replace(" ", "T") | regex_replace("(\+)(\d\d):(\d)(\d)$", ".\g<2>\g<3>Z")
  ec2_monitored: monitoring.state in ['enabled', 'pending']
  ec2_monitoring_state: monitoring.state
  ec2_persistent: persistent | default(false)
  ec2_placement: placement.availability_zone
  ec2_platform: platform | default("")
  ec2_private_dns_name: private_dns_name
  ec2_private_ip_address: private_ip_address
  ec2_public_dns_name: public_dns_name
  ec2_ramdisk: ramdisk_id | default("")
  ec2_reason: state_transition_reason
  ec2_region: placement.region
  ec2_requester_id: requester_id | default("")
  ec2_root_device_name: root_device_name
  ec2_root_device_type: root_device_type
  ec2_security_group_ids: security_groups | map(attribute='group_id') | list |  join(',')
  ec2_security_group_names: security_groups | map(attribute='group_name') | list |  join(',')
  ec2_sourceDestCheck: source_dest_check | default(false) | lower | string
  ec2_spot_instance_request_id: spot_instance_request_id | default("")
  ec2_state: state.name
  ec2_state_code: state.code
  ec2_state_reason: state_reason.message if state_reason is defined else ""
  ec2_subnet_id: subnet_id | default("")
  ec2_tag_Name: tags.Name
  ec2_virtualization_type: virtualization_type
  ec2_vpc_id: vpc_id | default("")
filters:
  instance-state-name:
  - running
groups:
  ec2: true
hostnames:
  - network-interface.addresses.association.public-ip
  - dns-name
  - private-dns-name
keyed_groups:
  - key: image_id | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: images
    prefix: ''
    separator: ''
  - key: placement.availability_zone
    parent_group: zones
    prefix: ''
    separator: ''
  - key: ec2_account_id | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: accounts
    prefix: ''
    separator: ''
  - key: ec2_state | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: instance_states
    prefix: instance_state
  - key: platform | default("undefined") | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: platforms
    prefix: platform
  - key: instance_type | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: types
    prefix: type
  - key: key_name | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: keys
    prefix: key
  - key: placement.region
    parent_group: regions
    prefix: ''
    separator: ''
  - key: security_groups | map(attribute="group_name") | map("regex_replace", "[^A-Za-z0-9\_]", "_") | list
    parent_group: security_groups
    prefix: security_group
  - key: dict(tags.keys() | map("regex_replace", "[^A-Za-z0-9\_]", "_") | list | zip(tags.values()
      | map("regex_replace", "[^A-Za-z0-9\_]", "_") | list))
    parent_group: tags
    prefix: tag
  - key: tags.keys() | map("regex_replace", "[^A-Za-z0-9\_]", "_") | list
    parent_group: tags
    prefix: tag
  - key: vpc_id | regex_replace("[^A-Za-z0-9\_]", "_")
    parent_group: vpcs
    prefix: vpc_id
  - key: placement.availability_zone
    parent_group: '{{ placement.region }}'
    prefix: ''
    separator: ''
plugin: amazon.aws.aws_ec2
use_contrib_script_compatible_sanitization: true

auth_kind: serviceaccount
compose:
  ansible_ssh_host: networkInterfaces[0].accessConfigs[0].natIP | default(networkInterfaces[0].networkIP)
  gce_description: description if description else None
  gce_id: id
  gce_image: image
  gce_machine_type: machineType
  gce_metadata: metadata.get("items", []) | items2dict(key_name="key", value_name="value")
  gce_name: name
  gce_network: networkInterfaces[0].network.name
  gce_private_ip: networkInterfaces[0].networkIP
  gce_public_ip: networkInterfaces[0].accessConfigs[0].natIP | default(None)
  gce_status: status
  gce_subnetwork: networkInterfaces[0].subnetwork.name
  gce_tags: tags.get("items", [])
  gce_zone: zone
hostnames:
- name
- public_ip
- private_ip
keyed_groups:
- key: gce_subnetwork
  prefix: network
- key: gce_private_ip
  prefix: ''
  separator: ''
- key: gce_public_ip
  prefix: ''
  separator: ''
- key: machineType
  prefix: ''
  separator: ''
- key: zone
  prefix: ''
  separator: ''
- key: gce_tags
  prefix: tag
- key: status | lower
  prefix: status
- key: image
  prefix: ''
  separator: ''
plugin: google.cloud.gcp_compute
retrieve_image_info: true
use_contrib_script_compatible_sanitization: true

conditional_groups:
  azure: true
default_host_filters: []
fail_on_template_errors: false
hostvar_expressions:
  computer_name: name
  private_ip: private_ipv4_addresses[0] if private_ipv4_addresses else None
  provisioning_state: provisioning_state | title
  public_ip: public_ipv4_addresses[0] if public_ipv4_addresses else None
  public_ip_id: public_ip_id if public_ip_id is defined else None
  public_ip_name: public_ip_name if public_ip_name is defined else None
  tags: tags if tags else None
  type: resource_type
keyed_groups:
- key: location
  prefix: ''
  separator: ''
- key: tags.keys() | list if tags else []
  prefix: ''
  separator: ''
- key: security_group
  prefix: ''
  separator: ''
- key: resource_group
  prefix: ''
  separator: ''
- key: os_disk.operating_system_type
  prefix: ''
  separator: ''
- key: dict(tags.keys() | map("regex_replace", "^(.*)$", "\1_") | list | zip(tags.values() | list)) if tags else []
  prefix: ''
  separator: ''
plain_host_names: true
plugin: azure.azcollection.azure_rm
use_contrib_script_compatible_sanitization: true

compose:
  ansible_host: guest.ipAddress
  ansible_ssh_host: guest.ipAddress
  ansible_uuid: 99999999 | random | to_uuid
  availablefield: availableField
  configissue: configIssue
  configstatus: configStatus
  customvalue: customValue
  effectiverole: effectiveRole
  guestheartbeatstatus: guestHeartbeatStatus
  layoutex: layoutEx
  overallstatus: overallStatus
  parentvapp: parentVApp
  recenttask: recentTask
  resourcepool: resourcePool
  rootsnapshot: rootSnapshot
  triggeredalarmstate: triggeredAlarmState
filters:
- runtime.powerState == "poweredOn"
keyed_groups:
- key: config.guestId
  prefix: ''
  separator: ''
- key: '"templates" if config.template else "guests"'
  prefix: ''
  separator: ''
plugin: community.vmware.vmware_vm_inventory
properties:
- availableField
- configIssue
- configStatus
- customValue
- datastore
- effectiveRole
- guestHeartbeatStatus
- layout
- layoutEx
- name
- network
- overallStatus
- parentVApp
- permission
- recentTask
- resourcePool
- rootSnapshot
- snapshot
- triggeredAlarmState
- value
- capability
- config
- guest
- runtime
- storage
- summary
strict: false
with_nested_properties: true

group_prefix: foreman_
keyed_groups:
- key: foreman['environment_name'] | lower | regex_replace(' ', '') | regex_replace('[^A-Za-z0-9_]', '_') | regex_replace('none', '')
  prefix: foreman_environment_
  separator: ''
- key: foreman['location_name'] | lower | regex_replace(' ', '') | regex_replace('[^A-Za-z0-9_]', '_')
  prefix: foreman_location_
  separator: ''
- key: foreman['organization_name'] | lower | regex_replace(' ', '') | regex_replace('[^A-Za-z0-9_]', '_')
  prefix: foreman_organization_
  separator: ''
- key: foreman['content_facet_attributes']['lifecycle_environment_name'] | lower | regex_replace(' ', '') | regex_replace('[^A-Za-z0-9_]', '_')
  prefix: foreman_lifecycle_environment_
  separator: ''
- key: foreman['content_facet_attributes']['content_view_name'] | lower | regex_replace(' ', '') | regex_replace('[^A-Za-z0-9_]', '_')
  prefix: foreman_content_view_
  separator: ''
legacy_hostvars: true
plugin: theforeman.foreman.foreman
validate_certs: false
want_facts: true
want_hostcollections: false
want_params: true

expand_hostvars: true
fail_on_errors: true
inventory_hostname: uuid
plugin: openstack.cloud.openstack

compose:
  ansible_host: (devices.values() | list)[0][0] if devices else None
keyed_groups:
- key: cluster
  prefix: cluster
  separator: _
- key: status
  prefix: status
  separator: _
- key: tags
  prefix: tag
  separator: _
ovirt_hostname_preference:
- name
- fqdn
ovirt_insecure: false
plugin: ovirt.ovirt.ovirt

include_metadata: true
inventory_id: <inventory_id or url_quoted_named_url>
plugin: awx.awx.tower
validate_certs: <true or false>

To create a new host.

To view the Host details for a job run.

Use the following procedure to create a new instance group.

When you have successfully created the instance group the Details tab of the newly created instance group enables you to review and edit your instance group information.

You can also edit Instances and review Jobs associated with this instance group:

Instances can be grouped into one or more instance groups. Instance groups can be assigned to one or more of the following listed resources:

When a job associated with one of the resources executes, it is assigned to the instance group associated with the resource. During the execution process, instance groups associated with job templates are checked before those associated with inventories. Instance groups associated with inventories are checked before those associated with organizations. Therefore, instance group assignments for the three resources form the hierarchy:

Job Template > Inventory > Organization

Consider the following when working with instance groups:

[automationcontroller]
126-addr.tatu.home ansible_host=192.168.111.126  node_type=control

[automationcontroller:vars]
peers=execution_nodes

[execution_nodes]

[instance_group_test]
110-addr.tatu.home ansible_host=192.168.111.110 receptor_listener_port=8928

TASK [ansible.automation_platform_installer.check_config_static : Validate mesh topology] ***
fatal: [126-addr.tatu.home -> localhost]: FAILED! => {"msg": "The host '110-addr.tatu.home' is not present in either [automationcontroller] or [execution_nodes]"}

[automationcontroller]
126-addr.tatu.home ansible_host=192.168.111.126  node_type=control

[automationcontroller:vars]
peers=execution_nodes

[execution_nodes]
110-addr.tatu.home ansible_host=192.168.111.110 receptor_listener_port=8928

[instance_group_test]
110-addr.tatu.home

TASK [ansible.automation_platform_installer.check_config_static : Validate mesh topology] ***
ok: [126-addr.tatu.home -> localhost] => {"changed": false, "mesh": {"110-addr.tatu.home": {"node_type": "execution", "peers": [], "receptor_control_filename": "receptor.sock", "receptor_control_service_name": "control", "receptor_listener": true, "receptor_listener_port": 8928, "receptor_listener_protocol": "tcp", "receptor_log_level": "info"}, "126-addr.tatu.home": {"node_type": "control", "peers": ["110-addr.tatu.home"], "receptor_control_filename": "receptor.sock", "receptor_control_service_name": "control", "receptor_listener": false, "receptor_listener_port": 27199, "receptor_listener_protocol": "tcp", "receptor_log_level": "info"}}}

HTTP POST /api/v2/instance_groups/x/instances/ {'id': y}`

18.1.3. Instance group policies

You can configure automation controller instances to automatically join instance groups when they come online by defining a policy. These policies are evaluated for every new instance that comes online.

Instance group policies are controlled by the following three optional fields on an Instance Group:

• policy_instance_percentage: This is a number between 0 - 100. It guarantees that this percentage of active automation controller instances are added to this instance group. As new instances come online, if the number of instances in this group relative to the total number of instances is less than the given percentage, then new ones are added until the percentage condition is satisfied.
• policy_instance_minimum: This policy attempts to keep at least this many instances in the instance group. If the number of available instances is lower than this minimum, then all instances are placed in this instance group.
• policy_instance_list: This is a fixed list of instance names to always include in this instance group.

The Instance Groups list view from the automation controller user interface (UI) provides a summary of the capacity levels for each instance group according to instance group policies:

Additional resources

For more information, see the Managing Instance Groups section.

HTTP PATCH /api/v2/instance_groups/N/
{
"policy_instance_list": ["special-instance"]
}
HTTP PATCH /api/v2/instances/X/
{
"managed_by_policy": False
}

18.1.7. Control where a job runs

If you associate instance groups with a job template, inventory, or organization, a job run from that job template is not eligible for the default behavior. This means that if all of the instances inside of the instance groups associated with these three resources are out of capacity, the job remains in the pending state until capacity becomes available.

The order of preference in determining which instance group to submit the job to is as follows:

1. Job template
2. Inventory
3. Organization (by way of project)

If you associate instance groups with the job template, and all of these are at capacity, then the job is submitted to instance groups specified on the inventory, and then the organization. Jobs must execute in those groups in preferential order as resources are available.

You can still associate the global default group with a resource, such as any of the custom instance groups defined in the playbook. You can use this to specify a preferred instance group on the job template or inventory, but still enable the job to be submitted to any instance if those are out of capacity.

Examples

• If you associate group_a with a job template and also associate the default group with its inventory, you enable the default group to be used as a fallback in case group_a gets out of capacity.
• In addition, it is possible to not associate an instance group with one resource but choose another resource as the fallback. For example, not associating an instance group with a job template and having it fall back to the inventory or the organization’s instance group.

This presents the following two examples:

1. Associating instance groups with an inventory (omitting assigning the job template to an instance group) ensures that any playbook run against a specific inventory runs only on the group associated with it. This is useful in the situation where only those instances have a direct link to the managed nodes.

2. An administrator can assign instance groups to organizations. This enables the administrator to segment out the entire infrastructure and guarantee that each organization has capacity to run jobs without interfering with any other organization’s ability to run jobs.

   An administrator can assign multiple groups to each organization, similar to the following scenario:

   • There are three instance groups: A, B, and C. There are two organizations: Org1 and Org2.
   • The administrator assigns group A to Org1, group B to Org2 and then assigns group C to both Org1 and Org2 as an overflow for any extra capacity that might be needed.
   • The organization administrators are then free to assign inventory or job templates to whichever group they want, or let them inherit the default order from the organization.

Arranging resources this way offers you flexibility. You can also create instance groups with only one instance, enabling you to direct work towards a very specific Host in the automation controller cluster.

max_concurrent_jobs: 10
max_forks: 50

awx-manage unregister_queue --queuename=<name>

Ansible Automation Platform supports container groups, which enable you to execute jobs in automation controller regardless of whether automation controller is installed as a standalone, in a virtual environment, or in a container. Container groups act as a pool of resources within a virtual environment. You can create instance groups to point to an OpenShift container. These are job environments that are provisioned on-demand as a pod that exists only for the duration of the playbook run. This is known as the ephemeral execution model and ensures a clean environment for every job run.

In some cases, you might want to set container groups to be "always-on", which you can configure through the creation of an instance.

Container groups are different from execution environments in that execution environments are container images and do not use a virtual environment. For more information, see Execution environments.