IBM Watsonx Code Assistant for AI-Driven Enterprise IT Automation in Red Hat Ansible Lightspeed

Red Hat, Inc., the world’s leading provider of open source solutions announced the general availability of Red Hat Ansible Lightspeed with IBM watsonx Code Assistant, a generative AI service to help enterprises accelerate IT automation across an organization.

 

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leaders will prevent 65% of businesses from achieving full value from cloud, data, and automation investments.”

According to IDC, “through 2024, shortcomings in critical skills creation and training efforts by IT industry leaders will prevent 65% of businesses from achieving full value from cloud, data, and automation investments.”¹ But, “generative AI has the potential to revolutionize the entire software development life cycle. IDC’s survey of developers about their use of generative AI indicates they see great potential for generative AI to increase productivity and automation for these non-coding tasks. Developers recognize the opportunity for DevOps automation to improve key software quality metrics by automating software testing, scoring project risk, and improving threat modeling.”²

Red Hat Ansible Lightspeed generates content recommendations from user prompts, integrating with IBM watsonx Code Assistant to access IBM foundation models and quickly build Ansible content. The service is purpose-built for Ansible, helping users to bridge the gap between automation ideas and Ansible content creation. Not only does this increase automation accessibility across IT personnel, but it also enables content best practices and maintenance organization-wide, resulting in improved, more consistent automation.

Focused automation for real world applications

A purpose-built AI service trained on Ansible data, Ansible Lightspeed with watsonx Code Assistant combines the power of first-hand experience with technical innovation to deliver content recommendations that are more accurate, consistent and specific to business needs. The service also enhances established ways of working as a natural extension of existing Red Hat Ansible Automation Platform workflows and alongside the full suite of Ansible content tools. As part of the Ansible Automation Platform subscription and natively integrated with the Ansible Visual Studio Code extension, developers and operators don’t need to log into or access a separate tool or service to access the potential of Ansible Lightspeed with watsonx Code Assistant.

To create and edit Ansible Playbooks and rules, users can input a straightforward text prompt and receive an output that’s translated into YAML content, streamlining role and playbook creation. Experienced users can significantly boost productivity while novice users have fewer barriers to entry for content creation, helping to expand the aperture of who can create Ansible content while also addressing automation skills gaps across the enterprise.

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An emphasis on quality content

Ansible Lightspeed with watsonx Code Assistant helps translate existing subject matter expertise into more compliant Ansible automation content and best practices that scale across teams and the enterprise. Ansible Lightspeed with watsonx Code Assistant scans existing Ansible content to help standardize and improve quality through its recommendations, as well as adhere to industry-standards. The service also helps safeguard private data through data isolation, so sensitive customer information remains untouched and possible data leaks are minimized.

Generative AI, the open source way

In alignment with Red Hat’s open source values, the Ansible Lightspeed with watsonx Code Assistant experience is built on transparency, collaboration and choice. Content source matching offers users visibility into the potential sources, authors and licenses used to train the data for the content recommendations, so contributors are properly recognized for their work and teams can better trust the AI-generated content. In addition, upstream content contributors have a choice as to whether or not their work contributes to fine-tuning of the model.

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