Government agencies facing an increasing mandate to move from legacy mainframe systems. The solution, generative AI. Now, agencies no longer need to fear the tradeoff between migration risk and the opportunity available in the cloud. In this case study featured on the AWS Public Sector Blog, our Karsun experts share their experience accelerating modernization with AI.
This case study features Karsun Solutions’ ReDuX AI powered migration and modernization platform. It offers a compelling approach for enterprises considering mainframe migration. Sharing their experience modernizing legacy applications for one of our government customers, this case study demonstrates what happens when modern AI tools meet modern software development practices.
Deep Insights Using Amazon Bedrock
ReDuX is designed to tackle typical obstacles in mainframe modernization, such as undocumented business rules, technical complexities, and regulatory compliance. Its approach is inspired by Karsun’s decade and a half modernizing complex enterprise systems for the federal government. ReDuX utilizes generative artificial intelligence (GenAI) powered by Amazon Bedrock to analyze and understand legacy systems.
Using Bedrock the Karsun team accessed high-performing foundation models from leading AI companies via a single API. Building their ReDuX platform on top of the resources provided by Bedrock, our team created an AI powered toolkit for identifying and mapping the complex business rules and processes embedded within mainframe applications. This facilitates a smoother transition to modern architectures. Further, by providing a structured approach, ReDuX reduces risks associated with legacy system modernization.
Matching AI with Modern Microservices Architecture
In the case study, we share how using our AI powered platform, we enabled our government customer to migrate from monolithic mainframe systems to microservices-based architectures on AWS. This shift enhances scalability, flexibility, and maintainability of applications, aligning with modern IT strategies.
It also allowed our team to focus on security and privacy. Recognizing the importance of enterprise-grade security and privacy, especially in government and regulated industries, the platform incorporates robust measures to protect sensitive data during and after the migration process.
Furthermore, migration to the cloud enables secure-by-design architecture. Using AI powered tools, like those available on the ReDuX AI platform, lets our agency customers access the benefits of the cloud while reducing migration risks. Written in a modern language, it alleviates workforce concerns and eliminates long-term maintenance issues arising from the aging, dwindling population familiar with COBOL and other outdated languages.
By demonstrating a successful implementation of generative advanced AI technologies and cloud services to migrate and modernize legacy systems, this case study from our team offers valuable insights. It presents a potential roadmap for organizations seeking to undertake similar modernization initiatives. Head over to the AWS Public Sector blog for deeper insights on AI-driven modernization and a technical breakdown of our solution.
Whether a state or local government, or a U.S. government agency, a major problem facing government and industry alike is their aging mainframe systems. A shrinking workforce with experience in older languages such as COBOL, limits the ability of organizations to maintain these legacy systems and prepare for the future. This was apparent as states like New Jersey, facing strain on their systems during the early days battling COVID, called for assistance with their COBOL systems.
Now as federal agencies seek new opportunities to introduce efficiencies via artificial intelligence (AI), these systems provide an easy target for modernization. AI with its ability to tackle complex, repetitive tasks accurately provides one solution to the government mainframe modernization challenge.
To this end, our Karsun Innovation Center experts devoted their time to producing a complete suite of AI solutions dedicated to tackling the mainframe modernization challenge.
The COBOL Modernization Challenge
With their decades-old interconnected applications and systems, these legacy mainframe systems are complex, expensive to maintain, difficult to change, and vulnerable to attacks. At the same time, the cloud presents the opportunity to build secure, resilient systems that adapt to the changing needs of its users.
Past modernization and migration attempts appeared out of reach for these systems. Stymied by both the cost and time required to transform these systems. These high-value assets handling mission-critical workloads present a high stakes challenge for modernization teams. Often core to the business with large customer bases, they have vast complex functionality that must be broken down into smaller parts before proceeding.
Karsun applied AI, speeding up this tedious task while ensuring modernization teams had a complete map of the legacy system. Using its ReDuX platform, Karsun limited the impact of poorly documented systems and unanticipated relationships between components. When integrated with the other tools available in the ReDuX platform, AI-assisted teams generated production ready code two times faster than when they used humans alone.
Further given this complexity, some organizations may decide to simply replatform the system. But AI gives us the opportunity to do more than lifting and shifting the application to the cloud. It empowers us to optimize with a product mindset. With this in mind we can build human centered systems that scale and adapt to a changing environment.
The Solution: AI for Mainframe Modernization
Enter ReDuX, Karsun’s AI-powered digital transformation platform. We built our platform using AI to accelerate modernization while reducing risk. Using Amazon Bedrock, a platform that provides access to AI tools via an API, Karsun built a comprehensive digital transformation platform. Karsun’s ReDuX provides AI-enhanced tools for modernization team members from designers to developers in a single platform.
Using generative AI, the platform creates a complete blueprint of a legacy system, reducing risk, and generates behavioral insights. Using this information business analysts, designers, and others do more than rewrite these legacy systems, they reimagine an optimized system designed to match the needs of its users.
This product oriented process is enhanced throughout the modernization effort via the platform’s digital transformation agents. Using agentic AI, the modernization team can chat with their code for deeper understanding and apply reusable templates using automations to rapidly scale their work while reducing risk.
ReDux is already in use by the Karsun teams delivering large-scaled complex modernization solutions to our federal agency customers. We recently shared our experience on the AWS Public Sector Blog. To learn more about AI Solutions for government modernization visit us here: https://karsun-llc.com/solutions/artificial-intelligence-ai-solutions/
Stuck with a difficult modernization challenge? Check out GoReDuX.AI and get unstuck today!
Recording live from the AWS Summit Washington, D.C., Karsun’s Badri Sriraman sits down with John Gilroy and the Federal Tech Podcast to discuss all things AI, accelerating legacy systems modernization and hyperlocal contextualization. Badri is the Vice President of the Karsun Innovation Center. Here, teams work to eliminate or reduce friction for the agencies modernizing their legacy systems. As part of that work, they developed ReDuX AI, a toolkit using AI resources to address common issues related to modernizing these older, more complex legacy systems. Throughout the interview, Badri and John discuss the costs and security risks associated with staying on current systems and the opportunity for AI to provide insight through hyperlocal contextualization to tackle these challenges.
Addressing the O&M Problem
The interview begins by acknowledging the drag aging infrastructure has on these agencies’ enterprise systems. The issue becomes intractable when operations and maintenance (O&M) costs become so high they take up the budget that would otherwise be used for modernization and systems enhancements. A 2023 Government Accountability Office (GAO) report examined the 10 critical systems it identified most in need of modernization. Some of those systems were over 50 years old and, in total, cost the government upwards of $337 million annually to operate and maintain.
In addition to the O&M costs, complex relationships between different systems components, older programming languages like COBOL, and outdated documentation all contribute to the difficulty of modernizing mission-critical legacy systems like those studied. As Badri reveals in the interview, artificial intelligence (AI) can be used to address many of those concerns. Moreover, those same AI tools may accelerate the transition, further reducing O&M costs as agencies move away from these legacy systems.
Eating the Elephant
In the interview, Badri shares a key component of Karsun’s AI-accelerated modernization methodology, hyperlocal contextualization. In a traditional modernization project, teams typically take an incremental approach. To “eat the elephant,” teams go one step at a time, optimizing as they modernize to reduce costs. The analysis required to peel away each part of the legacy system could slow down modernization to a yearslong process in highly complex systems. Throughout the process, these teams must untangle how different parts of the system integrate and work together.
Alternatively, using AI teams still move incrementally, avoiding the pitfalls of Big Bang Modernization. However, they also use AI to identify and map these relationships within legacy systems. This AI assistance helps those teams move at a rapid pace. Working together with the human team and stakeholders, the AI can quickly create a fuller understanding of the system, its impact on the mission and provide new insights into optimization opportunities during the modernization process. This analysis is the first step in using AI for hyperlocal contextualization.
The Security Imperative
An equally pressing concern is rising security threats. The 2023 GAO report found among the chief concerns for these aging systems were outdated hardware and security vulnerabilities. The same processes that help modernization teams optimize to reduce O&M costs can also be used to move from less secure systems to more secure systems based on industry standards and best practices.
Jumping in with Hyperlocal Contextualization
With more advanced large language models (LLMs), AI tools cannot only write the code but also review, debug, and make recommendations. Powered by AWS Bedrock, ReDuX AI not only takes the insights from its eat the elephant analysis but also makes recommendations to Karsun developers using the context generated from those insights. Plus it can then incorporate best practices and security policies into those recommendations. Using a tool like ReDuX AI, the security optimization recommendations are customized to the complexities found in that legacy system, resulting in a modernization process designed to optimize costs and security. Badri discusses this hyperlocal contextualization in greater depth in the interview.
The future is bright. In a 2019 report, the GAO shared agencies provided 94 examples of successful modernization initiatives over the five years studied. While some of the most challenging projects remain, AI tools, like those used by ReDuX, create a future where the remaining mission-critical systems modernize a possibility. Check out the full interview at www.theoakmontgroupllc.com/ep-161-how-to-overcome-the-challenge-of-legacy-systems/ or visit GoRedux.AI to learn more.