Developing Advanced Automation with Red Hat Ansible Automation Platform

Advance your Ansible skills and develop automation that scales by applying recommended practices with the new, container focused tools from Red Hat Ansible Automation Platform.

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About the course

Developing Advanced Automation with Red Hat Ansible Automation Platform (DO374) is designed for automation content developers to leverage the new, container focused tools from Red Hat Ansible Automation Platform to efficiently develop automation that can be managed by the automation controller. Learn recommended practices for automation development using reusable code, advanced playbook techniques, shared execution environments, and preparing for scalable automation with the automation content navigator.

This course is based on Red Hat Ansible Automation Platform 2.2.

Certification

The Red Hat Certified Specialist in Developing Automation with Ansible Automation Platform exam tests your ability to create Ansible playbooks to perform common system administration tasks.

Course Content

Developing Playbooks with Ansible Automation Platform 2

Introducing Ansible Automation Platform
Introducing Ansible Content Navigator
Lab: Installing Ansible Navigator
Understanding Changes in Playbook Creation
Lab: Running Playbooks with Ansible Navigator
Using Git for Ansible Project Management
Lab: Installing and Configuring Git
Lab: Managing Playbook Projects from GitHub
Understanding Ansible Best Practices

Managing Content Collections and Execution Environments

Reusing Content from Ansible Content Collections
Lab: Downloading and Using Additonal Ansible Content from Ansible Galaxy
Understanding Ansible Execution Environments
Lab: Downloading Additional Ansible Execution Environments
Lab: Selecting Ansible Execution Environments During Runtime

Working with Ansible Configuration Settings

Understanding Ansible Navigator and Ansible Configuration Differences
Lab: Generating and Configuring ansible.cfg
Lab: Generating and Configuring ansible-navigator.yml

Managing Inventories

Introduction Ansible YAML Inventories
Lab: Creating an Ansible YAML Inventory
Lab: Converting an INI Inventory into YAML
Understanding Ansible Inventory Variables
Understanding Dynamic Inventories
Lab: Creating an Ansible Dynamic Inventory with AWS EC2

Managing Task Execution

Understanding Privilege Escalation Methods
Understanding Task Execution Order
Lab: Testing Task Execution Order
Understanding Ansible Tags in Playbooks
Lab: Using Tags for Selected Task Executon
Optimising Playbook Speed
Lab: Monitoring Playbook Execution Speed

Transforming Data with Filters and Plugins

Understanding Jinja2 Filters
Lab: Using Different Jinja2 Filters in Playbooks
Understanding Lookup in Playbooks
Lab: Using Lookup for Host Data and Information
Understanding Advanced Loop Options
Lab: Creating a Nested Loop in Playbooks
Lab: Using Jinja2 for Network Filter Options

Coordinating Rolling Updates

Understanding Parallelism
Understanding Rolling Updates
Lab: Changing Parallelism Configuration in Ansible

Creating Content Collections and Execution Environments

Lab: Creating an Ansible Content Collection
Lab: Uploading Ansible Content Collections to Automation Hub and Ansible Galaxy
Lab: Creating an Ansible Execution Environment
Lab: Uploading Ansible Execution Environments to Automation Hub and Container Registries

Running Playbooks with Automation Controller

Understanding Automation Controller Architecture
Understanding Components of Ansible Controller Playbook Requirements
Lab: Running Playbooks from Automation Controller

What our students say about us

Frequently Asked Questions

Is this training live or pre-recorded?

The training is live instructor led training which is available in classroom as well as online format. We also record every training session which is then uploaded to our student portal.

How will I join the live online training?

The live online training is conducted via the zoom software, we will be providing you with the zoom meeting link to join the training.

How many students are there in a single batch?

On an average one batch will have a maximum of 18 students. We keep smaller batch sizes to promote interaction between the students and the instructor.