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Modernizing COBOL: From Mainframe to API

Key Points

  • Legacy mainframe COBOL systems still power critical business functions but are tangled in monolithic code, 3270 screens, batch jobs, and hidden business logic, making them hard to evolve.
  • The first step to modernization is to map the entire application landscape with tools like ADDI (Application Discovery and Delivery Intelligence) and its Refactoring Assistant, identifying data flows, batch schedules, and the specific logic embedded in screens and transactions.
  • Using that insight, you can extract and re‑implement isolated services that expose the same APIs as the original COBOL code, allowing automated testing and a cleaner, more maintainable code base.
  • Refactoring these services not only reduces technical debt but also opens the door to integrate advanced capabilities—such as AI inference—directly into the processing pipeline, especially when leveraging hardware like the Telum processor for inline AI execution.
  • The overall payoff is a modernized, service‑oriented architecture that delivers faster, more efficient business value while preserving the functional correctness of the existing legacy system.

Full Transcript

# Modernizing COBOL: From Mainframe to API **Source:** [https://www.youtube.com/watch?v=-CI8hb-077E](https://www.youtube.com/watch?v=-CI8hb-077E) **Duration:** 00:05:43 ## Summary - Legacy mainframe COBOL systems still power critical business functions but are tangled in monolithic code, 3270 screens, batch jobs, and hidden business logic, making them hard to evolve. - The first step to modernization is to map the entire application landscape with tools like ADDI (Application Discovery and Delivery Intelligence) and its Refactoring Assistant, identifying data flows, batch schedules, and the specific logic embedded in screens and transactions. - Using that insight, you can extract and re‑implement isolated services that expose the same APIs as the original COBOL code, allowing automated testing and a cleaner, more maintainable code base. - Refactoring these services not only reduces technical debt but also opens the door to integrate advanced capabilities—such as AI inference—directly into the processing pipeline, especially when leveraging hardware like the Telum processor for inline AI execution. - The overall payoff is a modernized, service‑oriented architecture that delivers faster, more efficient business value while preserving the functional correctness of the existing legacy system. ## Sections - [00:00:00](https://www.youtube.com/watch?v=-CI8hb-077E&t=0s) **Transforming Legacy COBOL Systems** - The speaker explains the challenges of massive, interconnected COBOL mainframe applications and outlines a three‑part approach to migrate them into a modern, service‑oriented architecture for greater business value. - [00:03:03](https://www.youtube.com/watch?v=-CI8hb-077E&t=183s) **AI‑Driven Refactoring for Legacy Systems** - The speaker explains how AI tools such as Watsonx Code Assistant, combined with Telum processors, enable inline AI processing and API‑based transaction handling to modernize legacy mainframe applications, reduce technical debt, and streamline batch workloads. ## Full Transcript
0:00Today you have those large mainframe COBOL applications 0:05that are providing you really large critical business value, 0:10but they're locked in this web of interconnectedness and are hard to deal with. 0:16So where do you go with that? 0:18What we want to talk about today is how to take that 0:21millions, if not hundreds of millions of lines of code of COBOL 0:26and bring it into the modern world 0:29and help you have these services aligned for your organization 0:34to drive better business value more efficiently. 0:38So I'm going to explain this to you in three parts. 0:42You're here today. 0:44Where to start, and what the payoff is. 0:48So let's think about our applications today. 0:50We have large application databases. 0:53This is where we store all the data related to this nice monolithic application. 0:58And it's connected to a transaction server. 1:01And you probably still have a whole bunch of those 3270 green screens in that code, 1:06whether or not people are using them today or not, you still have this all in the code. 1:11And then you have a set of batch processes as well. 1:14So today you may have put an API here 1:18and you may be using that API to go through this process to get to this function. 1:23But that API is dependent on all of this logic and all of this code 1:29because you have business logic hidden in these transactions, in this 3270 interface. 1:36And you have this batch processing that could be being fed part of the day over and over again, 1:44and then it batches up and processes at night. 1:47So you've got this process that works. 1:50It's driving your business, but it's not the most effective and efficient. 1:54So where do you start? 1:56You take a look at all of this application. 1:58Use tools like ADDI (Application Discovery and Delivery Intelligence) 2:00to understand how all these pieces fit together. 2:04What is your batch schedule? 2:06What are the applications? 2:08And you look at this data and figure out, 2:11using the refactoring assistant that's part of ADDI, 2:16you can look at this and understand what is the flow that provides this value? 2:23What are the pieces of the business logic that's sitting in the screens, 2:27the transaction, what's that data? 2:30And is there an appropriate piece from this side as well? 2:34And you can take that stream and pull it out of the existing code. 2:40And now I can have a new COBOL application that's exposing this exact same API. 2:49So I can use whatever automated testing I have 2:52to make sure that I'm building the function in a streamlined way. 2:57So that's where we are today, and a little bit about where to start. 3:02But now why? 3:03What's the real reason for doing this? 3:05Yes, this removes technical debt. 3:07This makes it easier to maintain. 3:10But let's think about it. 3:13AI and the AI world that's hitting us today. 3:16This transaction, if I could put AI right here, 3:22right in the middle, effectively and efficiently, 3:24which I can with a Telum processor, I can do inline processing. 3:29With this refactored service it's so much easier 3:32to put the processing in line in that logic rather than, 3:37"Oh, does it really need to go in the business logic that's sitting here in this screen?" 3:42"It's really hard to do." 3:44So thinking about our applications and thinking about the fact we want to modernize. 3:49By using the refactoring assistant, 3:51by working with ADDI and working with a new watsonx Code Assistant for Z, 3:56we can help modernize these transactions, 3:59bring this together to truly provide even better business value 4:04with our existing application logic. 4:09And then we also have to deal with this batch environment, 4:12these files or things that are coming in. 4:15Well, guess what? 4:16I now have this simplified API. 4:18Instead of putting a file on the system and running it through batch, 4:22I can just send it to that API as well and I can do that in line. 4:27Now we still have a need for batch. 4:29We're still going to do our end of day processing with our batch processing, 4:33but we can do many more of the transactions in line as part of this activity. 4:40Getting started and moving in this direction 4:45allows us to truly take advantage of this logic that's been there for years 4:49that's providing key critical business value 4:53- but it's locked in this mess. 4:55It makes it so much easier for us now expose and bring AI into the picture. 5:01So hopefully you see a little bit of that payoff to this modernization effort. 5:07And hopefully you see that by truly looking at our existing applications 5:12and the assets that we have, we can pull out and use those pieces 5:18to drive new business opportunity and new business value. 5:23Check it out. 5:23Take a look at the ADDI and the capabilities of watsonx Code Assistant for Z, 5:28and join me on the journey of modernizing your applications. 5:34Thanks for watching. 5:35For all you mainframe fans out there, 5:38don't forget to click "like" and subscribe 5:41so you won't miss my next video.