Mainframe Application Modernization Beyond Banking

This is part one in a five-part series on mainframe modernization. When you think of the world’s biggest modernization challenges, you immediately think of banking, and for good reason. Banks were among the first to roll out advanced mobile apps some 15 years ago, and they had already started offering online services in the mid-1990s. Well before that, banks were interacting through massive electronic payment gateways and operating mainframe services, many of which remain core to their business to this day even though the platforms themselves have evolved significantly since then. Even if transactional systems that connect to a bank make up much of the mainframe landscape, they are part of a larger wave of transformation that isn’t only about banks. Mainframes are still an essential part of the digital backbone of many other industries, and there are still a lot more digital transformation stories left to be told that aren’t exclusively financially motivated. Let’s explore some highlights of mainframe modernization in other industries, including insurance, automotive and retail.

If there is one common pattern for mainframe modernization shared across all industries, it’s that companies are trying to improve their digital experience for customers without the risk of interrupting critical core systems. The customer can be an end user on an app or website or an employee/partner in an office or in the field. Customers are evaluating the company based on how well the company’s business logic and data serve their experience. Customers don’t care if the back-end is a mainframe talking to a SaaS provider that offers a mobile app UI—they just want the whole system to meet their business needs efficiently and accurately. Even in a machine learning scenario, where mainframe data may be informing an artificial intelligence (AI) model rather than a person, there’s still a customer who will want the resulting AI model to support a business process.

There is no reason why DevOps practices should be reserved only for distributed applications and the cloud. The transformational story of State Farm, one of the world’s largest mutual insurers, offers a great leadoff example of agility. For a mature industry, there’s still a lot of future uncertainty for insurers. New startups appear every day, driving customer demands for features like online price quotes and mobile claims processing apps. State Farm’s dev team was in the midst of its own DevOps transformation, having established a combination of its own homegrown automation and test tools with Jenkins CI/CD and Git for delivery and deployment of new apps. These leverage data from workhorse IBM Z mainframe servers—some of which have been in continuous operation for as long as 50 years. Once changes to customer-facing apps and API-enabled services started rolling in with greater speed, it pointed out a bottleneck. Back-end services could not be modified with enough agility to keep up; and further, there was a shortage of experienced mainframe developers to make the changes. Using the development and debugging environment of IBM® Developer for z/OS, which integrates directly with Git for version control and check-ins, even newer additions to the development team were able to gain leverage and update mainframe applications on IBM Z with an intuitive, familiar workflow. “Our IBM Z systems offer a robust, secure and reliable foundation for growth. We wanted to support Z developers in achieving greater efficiency and speed but also help newer recruits feel comfortable on the platform, so that we can all work together across platforms to deliver rapid innovation,” said Krupal Swami, Technology and Architecture Director for State Farm.

A leading automotive firm depends upon core systems to populate new in-car applications and services with current data. Their existing internal source code management system was starting to affect the stability of mission-critical mainframe applications, and newer developers were having difficulty gaining visibility into the dependencies each change might affect. The firm switched their mainframe teams to development on IBM IDZ (IBM Developer for z/OS) with IBM DBB (which improves the visibility of dependency based builds), and then used IBM UrbanCode Deploy to deliver agile updates to the highly distributed target systems.

A major retail enterprise will naturally accumulate many mainframe applications on the way to creating new customer-ready functionality. After a few years, rationalization of this extended application estate becomes a full-time job for too many skilled people, as interdependencies between apps and mainframes are hard to uncover. Further complicating matters, newer development employees get very little transparency into the architectural and software decisions made by previous generations of developers and IT leaders, creating even more unproductive work. Using IBM ADDI (Application Discovery and Delivery Intelligence), both senior and junior developers can analyze all mainframe applications alongside newer apps and services. Quick discovery and documentation of interdependencies now helps their combined ITOps and software delivery teams understand the impact of any introduced changes.

Interestingly, while these transformational stories happened outside of the financial industry, almost every one of them relies upon one or more critical transaction processes that likely happen on mainframes, bringing the modernization story back to banks, in a way. New hybrid cloud use cases are appearing, offering higher performance and better data protection through selectively co-locating some inference, data processing and security workloads on mainframes, allowing teams to have the elasticity of cloud with the always-on power of the mainframe. In all ­­these cases, unlocking the next frontier in productivity will require modernizing the human developer’s experience of working with the mainframe, so both experienced business developers and new talent can join the modernization effort. To learn more, see the other posts in this series:

• Part 2: “Using collaboration (not migration) to modernize your mainframe applications with the cloud”
• Part 3: “Banking on mainframe-led digital transformation for financial services”
• Part 4: “Mainframe and the cloud? It’s easy with open source“

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