2 min Devops

Red Hat announces updates to the Ansible Automation Platform

Red Hat announces updates to the Ansible Automation Platform

Red Hat has updated its DevOps Ansible Automation Platform. The added functionality includes a new way to manage automation resources and there is more certified automation content available. In addition, new analytics applications have been added.

Red Hat is providing many of its products with an annual update. Recently, the company presented version 8.2 of Red Hat Enterprise Linux (RHEL). This time the company updated the Red Hat Ansible Automation Platform. The platform was released last year and allows customers to set up and share resources to automate the rollout of application infrastructures. The platform aims to bring scale automation to business projects and teams that execute or manage these projects.

New functionality

The upcoming update, in May, will add an Automation Services Catalog. This catalogue will help customers manage the control and compliance requirements that must be met to achieve automation across the entire company. The Catalog will provide lifecycle management for all automation resources, among other things.

In addition, more certified content is added to the Ansible Content Collections. This additional content makes it easier to use and share content, including modules, plugins, roles and playbooks. These collections have more than 1,200 certified Ansible Modules at their disposal. These modules are available in the centralized content repository for Red Hat and partner Automation Hub.

Extensive analytics capabilities

Besides, new analytics features and capabilities have been added to the latest version of Red Hat Ansible Automation Platform. These additions should help users gain a better understanding of how their automation actions are performing.

For example, functionality has been added such as better filtering capabilities that let users filter up to the individual Red Hat Ansible Tower clusters and by date. The analytics provide information on job stats such as the total number of runs, total time, average time, success factor and most failed tasks. Other analytics tools can compare all this information with the adoption of automation within different organizations.