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Legacy, but critical: A playbook to evolve core systems

Lessons from a sports tech client modernization journey

Legacy, but critical: A playbook to evolve core systems

 

Modernizing business-critical systems isn't just about "turning them off and rewriting." It's a high-stakes balancing act: maintaining the decades-old engines that power today's revenue while simultaneously engineering the platforms of tomorrow.

 

In sports tech, everyone loves talking about next-gen platforms: low-latency data pipelines, real-time analytics and cloud-native architectures. But for most organizations, the systems that make the money today aren't greenfield. They're long-lived platforms that have been adapted, extended and patched over many years. In sports betting, those legacy platforms are often:

 

  • Always-on and real-time: Markets move and prices fluctuate every second.

  • Directly tied to revenue: Continuous price calculations are mandatory for active betting.

  • Deeply integrated: They serve as the hub for dozens of critical upstream feeds and downstream consumers.


Success requires keeping these systems safe and evolving while the "next-gen" replacement is still on the drawing board. This playbook is about one of those systems, outlining a strategy to make systems visible, changes safe and teams more collaborative, focusing on high-impact "targeted surgery" rather than invasive overhauls.

Four themes for working in legacy:

Theme 1: Make the system visible: product, code and flow.

 

Theme 2: Make change safe: how we run, release and protect critical flows.

 

Theme 3: Build a learning, shared-ownership team.

 

Theme 4: Improve legacy responsibly when a rewrite is around the corner.

 

About the author

Prachi Tyagi

Lead Consultant, Thoughtworks

With 16+ years in software engineering, Prachi has worked on distributed systems and the modernization of complex legacy platforms. Her background spans architecture, continuous delivery, testing, and scalable software design. More recently, she’s been drawn to AI/ML, particularly MLOps and Generative AI, and how they can shape developer workflows, system design, and intelligent software systems.

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