The Common Thread
What do the first Maserati, Ferrari, Porsche, and Land Rover have in common? Despite each being introduced in the early 1940s, they have all continually evolved over the years, embracing modern engineering, cutting-edge technology, and innovation while maintaining their efficiency, performance, reliability, and excellence.
- The Maserati, Ferrari, Porsche, and Land Rover have all remained popular for decades, with no signs of slowing down.
- They have each undergone numerous design changes, with varying degrees of success, but they continue to be beloved by car enthusiasts.
The Mainframe Myth
Despite decades of continuous transformation, some critics still cling to the myth that mainframes are outdated, inefficient, and unable to integrate with modern IT systems. However, this couldn’t be further from the truth.
| Mainframe Transformation | IBM’s z16 | IBM’s z17 |
| Introduced in | 2023 | 2024 |
| Key Features | Built for AI | Handles new workloads with unparalleled security, scalability, and efficiency |
The Problem
The problem isn’t the mainframe—it’s how we’ve managed and transformed the applications running on it. Instead of walking away from the most reliable, secure, and high-performing computing platform in history, we should focus on how it’s evolving to support new workloads, AI-driven insights, and hybrid cloud integration.
A Rapidly Modernizing Space
The mainframe isn’t standing still. It’s taking on more mission-critical workloads than ever, supporting everything from AI-powered fraud detection to high-speed financial transactions. In fact, a whopping 72 percent of the world’s compute runs on mainframes while the platform makes up just 8 percent of IT costs.
Mainframe Transformation
Mainframe transformation involves two things. First, development teams need to harness mainframes’ computing power, scale, and data storage capabilities. Second, they need those mainframe systems to align with the automation capabilities that their cousins in the cloud have adopted, making the mainframe software development life cycle more efficient, eliminating manual processes, and increasing the quality and velocity of legacy applications.
DevOps Workflows
DevOps workflows alone won’t get us there, but tools are bridging the gap. When it comes to tools, shops need mainframe code to be managed just like cloud or distributed applications, enabling continuous integration/continuous development pipelines, automated testing, and version control while maintaining compatibility with legacy environments.
Culture and the Developer Experience
Culture and the developer experience also play an important role in mainframe transformation. If the developer experience for engineers is subpar, a boost to efficiency is unlikely to emerge. Removing manual bottlenecks, reducing or eliminating context switching, streamlining archaic development processes, and adopting an agile culture are all easy ways to improve the developer experience.
Fine-Tuning the Mainframe for Government Efficiency
Customers I talk to often describe three very different—but equally valid—paths for fine-tuning their mainframe strategy. Some government agencies choose a slow-and-steady approach, expanding their mainframe footprint over time as needs evolve. “Our workloads are growing as our population grows,” one CIO told me. “We’re not moving off the mainframe—we’re growing with it.”
- Others are leaning into modernization by refactoring the code itself. With the help of Generative AI-powered code assistants, customers are telling me they’re finally able to tackle decades-old applications with confidence.
- And then there are the agencies doubling down—reinvesting in the mainframe by upgrading to the latest zSystems and embracing DevOps practices across the board.
The Developers’ Perspective
The developers working with mainframes are also excited about their future. A 2024 Forrester Report found that “among global infrastructure hardware decision-makers, 61% said that their firm uses a mainframe. Of those that use mainframes, 54% indicated that their organization would increase its use of a mainframe over the next two years.”
There’s also a wide ecosystem of vendors building tools to modernize the mainframes. That is why you see more and more talk about artificial intelligence, graphical scanning, and mapping tools to parse, map, and refactor legacy code bases and monolithic code into more manageable assets. AI also gives organizations the ability to quickly onboard new resources and get them familiar with their code base faster to become more productive. Developers can pinpoint necessary changes faster, reducing planning time and accelerating updates.
These trends are promising, and I do not doubt that they would allow government services to harness the mainframe’s data storage and processing power while also adopting the agility that has been the hallmark of Silicon Valley. The mainframe is not only a reliable and secure platform but also a highly efficient one. By embracing its evolution and supporting its continued growth, we can ensure that it remains a vital part of our IT infrastructure for years to come.
