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Transforming the way developers learn and work
How IBM Consulting achieved a 30% reduction in Ansible Playbook development effort while maintaining quality, compliance and resiliency
Is it time to rewrite the model for software development?
All over the world, demand for software developers is growing. In fact, the US Labor Department expects job opportunities for software developers will grow by 25% by 2031. At the same time, it estimates that the global shortage of software engineers may reach 85.2 million by 2030. This imbalance between the supply and demand of software developers will continue to deepen over time if it remains unaddressed.
“To be proactive in helping our clients address this trend, we have begun exploring generative AI-enabled pair programming,” explains Gerry Leitão, Partner and Global Hybrid Cloud Automation Leader for IBM Consulting®. “In our early testing, we have seen firsthand that generative AI can act as a force multiplier for developers. There’s so much legacy code that needs to be refactored and modernized, not to mention net new code being developed. Generative AI has an important role to play in balancing those priorities,” says Leitão. In fact, Gartner estimates that “by 2025, 80% of the product development life cycle will make use of generative AI code generation, with developers acting as validators and orchestrators of back-end and front-end components and integrations.”*
“We began our mission to help clients increase developer productivity using generative AI by bringing together IBM Research, IBM Technology and Red Hat. There are so many possible use cases to explore. We chose to start with Ansible,” notes Leitão. Ansible Automation Platform is the leading IT automation platform that helps thousands of companies across the globe drive complexity out of their IT environments and automate their IT Operations.
“We asked, ‘How can we help shorten the Ansible learning curve and amplify the impact of each individual who develops Ansible automation?’” says Leitão. This led to the technical preview of IBM® watsonx™ Code Assistant for Red Hat® Ansible® Lightspeed.
* Gartner, Emerging Tech: Generative AI Code Assistants Are Becoming Essential to Developer Experience, May 11, 2023. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
Through AI-generated recommendations that are based on natural language inputs, developers can use watsonx Code Assistant for Red Hat Ansible Lightspeed to modernize and build Ansible Playbook content faster: content that is of high quality and resiliency, as it is deployed into production.
During the technical preview for watsonx Code Assistant for Red Hat Ansible Lightspeed, Leitão’s team tested the solution and built Ansible Playbooks that were intended to support a range of use cases, including: automating the installation of SAP databases and applications in Amazon Web Services (AWS); and, in a single click, providing end-to-end installation of SQL database and server components along with Primary Application Server (PAS) installation of SAP of JAVA/ABAP systems. The team also used it to test refactoring and modernization of legacy playbooks supporting use cases such as user access management, security policy enforcement, and system (IBM WebSphere®/MQ/DB2®) setup, monitoring and upgrades.
“The tool is designed to increase the velocity and volume of Ansible content that we can build and/or modernize for our clients. I believe the quality of those Ansible Playbooks should be higher because watsonx Code Assistant will find and recommend the best components that the developer can use to build each playbook,” explains Leitão. In the case of watsonx Code Assistant for Red Hat Ansible Lightspeed, it will allow more developers, with a broader range of backgrounds, to build and refactor Ansible automations. “We’re not looking to replace developers. Generative AI is not going to build every piece of code out there. It’s intended to be a force multiplier when it’s paired with a human,” adds Leitão.
The Granite foundation model underlying watsonx Code Assistant for Red Hat Ansible Lightspeed was trained and tested by experts across IBM and Red Hat. “We helped tune the model using best practices we gained from years of development work with clients,” says Leitão. When offering recommendations, watsonx Code Assistant shares the most-likely training matches for maximum trust and transparency. Each suggestion will include the three closest matched sources of content, their author and license.
“During the technical preview for watsonx Code Assistant for Red Hat Ansible Lightspeed, we observed initial build productivity improvements in the range of 20%–45%. As we move to GA, even more gains in productivity are expected. We also believe there’s additional downstream productivity that has not been fully quantified yet,” explains Leitão. “Not only are we aiming to accelerate the development phase for Ansible automations and shorten time-to-value for our clients after GA, but we intend for the quality of the content to be higher.”
Since watsonx Code Assistant for Red Hat Ansible Lightspeed empowers developers to create Ansible tasks using natural language inputs, developers are positioned to quickly expand their skill set and increase their impact on their organizations. “Watsonx Code Assistant is expected to both expand the number of people who can develop Ansible automations and reduce their time-to-proficiency because they have generative AI assisting them,” notes Leitão.
As they work with watsonx Code Assistant for Red Hat Ansible Lightspeed, teams will be able to uncover different ways to create value with Ansible. “We believe watsonx Code Assistant for Red Hat Ansible Lightspeed will broaden the aperture of what can be built on Ansible. A developer might be biased toward building content using one approach, or they may be entirely new to Ansible,” argues Leitão. “Watsonx Code Assistant for Red Hat Ansible Lightspeed is designed to empower people to explore more, so they’ll discover more of what can be built. What is possible on the platform should increase, as developers work more with generative AI.”
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Produced in United States, October 2023.
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