Chapter 5. Using the Command Generator

Procedure

1. For the list of available playbooks without details, use the following command.

   $ docker run --rm $IMAGE command_generator_vars | grep Playbook
   
   The current version of the operational playbooks collection contains the following playbooks:
   
   Playbook: aws_add_extension_nodes
   Playbook: aws_backup_stack
   Playbook: aws_deployment_inventory
   Playbook: aws_remove_extension_nodes
   Playbook: aws_restore_stack
   Playbook: aws_upgrade
   Playbook: gcp_aap_health_check
   Playbook: gcp_backup_deployment
   Playbook: gcp_create_external_load_balancer
   Playbook: gcp_delete_external_load_balancer
   Playbook: gcp_deployment_inventory
   Playbook: gcp_health_check
   Playbook: gcp_list_deployments
   Playbook: gcp_nodes_health_check
   Playbook: gcp_restore_deployment
   Playbook: gcp_setup_logging_monitoring
   Playbook: gcp_upgrade

2. To provide a list of all available playbooks, and to use the command generator, use the following command.

   $ docker run --rm $IMAGE command_generator_vars

   This provides a list of playbooks and a command similar to the following:

   ===============================================
   Playbook: gcp_upgrade
   Description: Performs the upgrade of the Ansible Automation Platform from GCP Marketplace components to the latest version.
   -----------------------------------------------
   Performs the upgrade of the Ansible Automation Platform from GCP Marketplace components to the latest version.
   
   -----------------------------------------------
   Command generator template:
   
   docker run --rm $IMAGE command_generator gcp_upgrade [--ansible-config ansible_config_path>] \
   -d <deployment_name> -c <cloud_credentials_path> --extra-vars 'gcp_compute_region=<gcp_compute_region> gcp_compute_zone=<gcp_compute_zone> gcp_backup_taken=<true|false>'
   ===============================================

Procedure

1. Run the command generator.

   $ docker run --rm -v <local_directory_data_file>:/data $IMAGE command_generator_vars <playbook_name> --output-data-file /data/<data-file>.yml

   The outputs of this command are the command to run and the data file template. The data file is also saved in your <local_data_file_directory>. This is the template which you populate with your data.

   The following example uses the gcp_backup_deployment playbook.

   $ docker run --rm -v <local_data_file_directory>:/data $IMAGE command_generator_vars gcp_backup_deployment \
   --output-data-file /data/backup.yml

2. Producing the following output.

   ===============================================
   Playbook: gcp_backup_deployment
   Description: This playbook is used to backup the AoC Self-managed GCP environment.
   -----------------------------------------------
   This playbook is used to backup the AoC Self-managed GCP environment.
   For more information regarding backup and restore, visit our official documentation -
   
   -----------------------------------------------
   Command generator template:
   
   docker run --rm -v /tmp:/data $IMAGE command_generator gcp_backup_deployment --data-file /data/backup.yml
   
   Data template:
   
   gcp_backup_deployment:
     cloud_credentials_path:
     deployment_name:
     extra_vars:
       gcp_bucket_backup_name:
       gcp_compute_region:
       gcp_compute_zone:
   
   ===============================================

Procedure

1. Ensure that the mounted volume points to the directory where the data file is.

   For the gcp_backup_deployment playbook example, this is:

   $ docker run --rm -v /tmp:/data $IMAGE command_generator gcp_backup_deployment --data-file /data/backup.yml

   Which generates the following output:

   Command to run playbook:
   
   $ docker run --rm --env PLATFORM=GCP -v /path/to/credentials:/home/runner/.gcp/credentials:ro \
   --env ANSIBLE_CONFIG=../gcp-ansible.cfg  $IMAGE\ redhat.ansible_on_clouds.gcp_backup_deployment \
   -e 'gcp_service_account_credentials_json_path=/home/runner/.gcp/credentials  \
   gcp_deployment_name=my-deployment gcp_compute_region=us-east1 gcp_compute_zone=us-east1-b'

   This new command has the required parameters, environment variables and mounted volumes to run the playbook.

2. Run the generated command. You can save this command to rerun it later if required.