Red Hat this week made available a managed instance of the Ansible automation framework on the Amazon Web Services (AWS) cloud.

Announced at the AWS re:Invent 2024 conference, Red Hat and AWS also revealed they have formally struck a strategic collaboration agreement under which additional offerings such as Red Hat OpenShift Virtualization and multiple artificial intelligence (AI) offerings will be added to the AWS Marketplace.

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How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

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Respond to issues as they arise, using manual processes and troubleshooting techniques

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What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

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As part of that effort, Red Hat is pledging to bolster support for Red Hat OpenShift Service on AWS, a managed instance of a cloud-native application development and deployment platform based on Kubernetes and make it simpler to migrate legacy applications running on virtual machines to that platform.

Matthew Packer, principal product marketing manager for Ansible, said as more organizations opt to rely on managed services it’s become apparent there is a significant number of organizations that would prefer to rely on Red Hat and AWS to manage Ansible and other Red Hat platforms on their behalf. That approach then enables those organizations to reallocate more of their internal resources to building and deploying software, he added.

Each organization will need to determine for itself to what degree it wants to manage platforms such as Ansible themselves, however, in the age of AI the pace at which IT workflows are being automated is starting to accelerate. Many organizations will soon have to determine when it might make sense to rely on a generative AI tool to automate a task versus a framework such as Ansible.

In theory, a generative AI tool makes it simpler to use natural language to automate a task, but the output created is probabilistic, which means it needs to be reviewed by an IT professional before being applied. In contrast, playbooks created using Ansible are deterministic in that they run the same way every time. On the pulse side, Red Hat via a Lightspeed initiative launched in collaboration with IBM has made it possible to use a generative AI tool to make it simpler to create playbooks that are implemented using the Ansible framework.

Regardless of approach, the level of expertise required to automate an IT workflow continues to decline. Historically, creating a playbook using a framework such as Ansible required an IT professional who in addition to having a deep understanding of the workflow to be automated also possessed the programming skills required to invoke Ansible. With the rise of generative AI, much of the code required to automate a workflow can now be automatically generated.

Hopefully, the overall amount of toil that IT teams typically experience will continue to be reduced as more processes are automated. In fact, many of the routine tasks that today require a lot of time to perform may soon be eliminated. IT teams will then need to determine what tasks are best left to a machine to perform while focusing more of their efforts on orchestrating workflows across IT environments that are only becoming increasingly complex to manage.