TL;DR:
- IBM introduces Watsonx Code Assistant for Z, an AI-powered solution for COBOL to Java translation on IBM Z.
- Generative AI enhances developer productivity, aiming to accelerate COBOL app modernization.
- Watsonx.ai code model, with knowledge of 115 coding languages from 1.5 trillion tokens, powers the solution.
- Product portfolio extends to Red Hat Ansible Lightspeed, addressing skills challenges for developers.
- Watsonx Code Assistant optimizes COBOL to Java conversion, enabling faster and more efficient code transformation.
- Collaboration with industry leaders underscores the transformative impact of generative AI.
- Organizations can leverage mainframe assets, bridging skills gaps and achieving robust application modernization.
- The solution aligns with industry trends, promising a 30% reduction in coding task completion times by 2028.
- Trust and transparency principles underpin the approach, safeguarding sensitive data and IP.
Main AI News:
In a strategic move aimed at revolutionizing mainframe application modernization, IBM has unveiled the groundbreaking watsonx Code Assistant for Z. This cutting-edge generative AI-powered tool promises to significantly expedite the translation of COBOL to Java on the IBM Z platform, thereby bolstering developer efficiency and productivity. Slated for release in the fourth quarter of 2023, this product is poised to play a pivotal role in reshaping COBOL application modernization processes. Notably, a sneak peek of the Watsonx Code Assistant for Z is scheduled for the highly anticipated TechXchange event in Las Vegas, taking place from September 11th to 13th.
The Watsonx Code Assistant for Z stands as a pivotal addition to the broader Watsonx Code Assistant product family. This innovative suite also includes the upcoming IBM Watsonx Code Assistant for Red Hat Ansible Lightspeed, set to launch later this year. These solutions harness the remarkable potential of IBM’s watsonx.ai code model, which has harnessed insights from an astonishing 1.5 trillion tokens across a spectrum of 115 coding languages. With an impressive 20 billion parameters, it’s well on track to emerge as one of the most expansive generative AI foundation models for code automation. As the Watsonx Code Assistant portfolio evolves, it is expected to encompass various programming languages, serving to reduce the skills gap among developers while expediting the modernization journey.
The prime directive of the Watsonx Code Assistant for Z is to empower businesses by harnessing generative AI and automated tools to facilitate swift mainframe application modernization. This endeavor is underpinned by the steadfast commitment to preserving the innate performance, security, and resiliency capabilities emblematic of the IBM Z platform.
At the core of this initiative is the COBOL data processing language, which underpins crucial business and operational processes across global organizations. On a grand scale, the integration of Watsonx Code Assistant for Z holds the potential to streamline developers’ ability to selectively and progressively transform COBOL business services into meticulously designed, high-quality Java code. This transformation could impact an estimated billions of lines of COBOL code, representing a massive undertaking in targeted modernization over time. Leveraging generative AI, developers are primed to expedite the assessment, updating, validation, and testing of code, consequently streamlining the modernization of sprawling applications and enabling a sharper focus on high-impact tasks.
IBM’s approach encompasses comprehensive tooling at each phase of the modernization journey. The envisioned solution encompasses the esteemed Application Discovery and Delivery Intelligence (ADDI) inventory and analysis tool. Key milestones in this journey involve the refinement of COBOL business services, the seamless transformation of COBOL code into optimized Java code, and the meticulous validation of outcomes, inclusive of automated testing capabilities. The potential gains for clients are substantial:
• Acceleration of code development and amplification of developer productivity throughout the application modernization lifecycle.
• Effective management of the overall cost, complexity, and risk associated with modernization endeavors, including the in-place translation and optimization of code on the IBM Z platform.
• Enhanced access to a wider pool of IT skills, facilitating swift developer onboarding.
• Attainment of high-quality, easily maintainable code through model customization and the application of best practices.
Roger Burkhardt, CTO of Capital Markets and AI at Broadridge Financial, underscores the significance of IBM’s collaboration in advancing generative AI interfaces to usher in substantial productivity enhancements. Burkhardt remarks, “We have had excellent client response to our generative AI investments and we are intrigued by the opportunity to further our efforts by leveraging IBM watsonx Code Assistant for Z to address a broader range of platforms.”
The Imperative of AI-Powered Modernization
Fresh insights from the IBM Institute for Business Value underscore the prevailing trend wherein organizations are 12 times more inclined to leverage their existing mainframe assets rather than embarking on a complete overhaul of their application landscapes. However, this approach comes with its own set of challenges, with a lack of resources and skills emerging as the foremost hurdle for these organizations.
Kareem Yusuf, Senior Vice President of Product Management and Growth at IBM Software, highlights the transformative potential of bringing generative AI capabilities to new use cases. He emphasizes the precision with which IBM engineers the Watsonx Code Assistant for Z to adopt a targeted and optimized approach. This approach aims to rapidly and accurately convert code into a format optimized for the IBM Z platform, thereby expediting time-to-market while broadening the skills pool. This concerted effort serves to enhance applications and introduce novel capabilities while retaining the performance, resiliency, and security attributes intrinsic to IBM Z.
In the realm of application modernization, a myriad of approaches exists. From rewriting all application code in Java to migrating to public clouds, the landscape is diverse. However, these methods may inadvertently compromise integral IBM Z capabilities, failing to yield the anticipated cost reductions. Converting COBOL applications to Java syntax using conventional tools can yield convoluted and challenging-to-maintain code that might bewilder Java developers. Generative AI offers promise, yet current AI-assisted partial rewrite technologies lack support for COBOL and often fall short in optimizing the resultant Java code for its intended purpose.
The Java code produced through Watsonx Code Assistant for Z is anticipated to be object-oriented, aligning seamlessly with the broader COBOL application landscape and key runtimes such as CICS, IMS, DB2, and other z/OS environments. Notably, Java on Z is meticulously designed for optimal performance, outshining its x86 counterparts.
A Vision Grounded in Governance and Innovation
In accordance with insights from a 2023 Gartner report, the collaboration between humans and AI assistants holds the promise of slashing coding task completion times by a remarkable 30% by 2028. The report underscores the symbiotic relationship between AI code generation tools and the indispensable quality assurance and security controls that developers rely on for robust and secure product development.
When it comes to implementing generative AI, the protection of sensitive data and intellectual property stands paramount. IBM’s watsonx platform adheres to a time-tested foundation rooted in Trust and Transparency principles. This approach enables enterprises to harness their proprietary data and intellectual property to construct tailor-made AI solutions that can be seamlessly integrated across operational landscapes.
IBM Consulting, renowned for its domain expertise in IBM Z application modernization, plays a pivotal role in guiding clients across key industries, including banking, insurance, healthcare, and government. The dedicated consultants in this domain assist clients in identifying optimal application areas for modernization, thereby maximizing the potential benefits of the Watsonx Code Assistant for Z.
For those seeking to embark on AI-assisted mainframe application modernization, IBM’s specialized, targeted approach stands ready to deliver optimal outcomes. To delve deeper into this transformative landscape, visit our website and register for the enlightening Watsonx Code Assistant for Z webinar, scheduled for September 21st at 11 am ET. Here, you can witness firsthand how IBM is weaving the fabric of Generative AI into the realm of mainframe application modernization. Additionally, you can schedule a live demo with our team to explore the vast potential that lies ahead.
Conclusion:
IBM’s AI-powered Watsonx Code Assistant for Z marks a milestone in mainframe app modernization. Leveraging generative AI, not only accelerates COBOL-to-Java conversion but also addresses skills challenges, augments developer productivity, and preserves platform capabilities. This transformative step aligns with evolving market needs and positions IBM as a driving force in the AI-powered app modernization landscape.
