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5 Paths to Legacy Transformation

Matthew Clemente EVP of Global Operations, Lemongrass
Photo by Jametlene Reskp on Unsplash

It's common to talk about legacy-system transformation as if there's just one path available for modernizing systems. But in reality, legacy transformation is like navigating a sprawling interstate highway network; there are many routes that can potentially get your legacy systems to where you want them to be. The challenge organizations face is identifying which tactics will best help them update older technology systems to align with current business needs—while improving performance.

Allow me to explain by discussing five different approaches to legacy-system transformation. As you'll learn, all of these approaches can add value to legacy systems, but they do so in different ways—and it may or may not make sense to try one particular approach or another on your transformation journey.

Platform Upgrade

One of the simplest and most obvious ways to get more value from a legacy system is to update it to a newer version of the system (or to update the platform on which it depends).

For example, if your app is built on top of a legacy ERP platform, migrating to the new version of the platform may well add efficiency, flexibility, and/or scalability to the app—all without requiring you to modify the application itself.

Before taking this approach, it's important to evaluate how much value a platform upgrade would add—and then weigh that against how much time, effort, and money the upgrade requires. Depending on when your last upgrade took place, a major platform upgrade may not create enough value to justify itself. But in other cases—especially if it has been years since you last updated the legacy systems or platforms on which your applications depend—an upgrade is a comparatively fast and easy way to improve application performance and/or manageability. Although upgrading doesn't change the fundamentals of the technology you're using, it is likely to unlock new features and flexibility that help to modernize the application.

Cloud Migration

Another common transformation approach is moving legacy apps to the cloud. Here, again, moving to the cloud doesn't fundamentally change your system. But it makes it easier in many respects to operate and manage the system because you can take advantage of cloud infrastructure that you can consume on demand. It also frees you from having to acquire, deploy, and maintain your own hosting infrastructure.

In many cases, legacy-platform vendors offer both on-premises and cloud-based versions of their systems. Although both types of offerings typically provide the same core features, migrating to the cloud-based version can simplify application management and increase scalability.

Moving to a cloud platform takes time and effort, so it is important to evaluate whether it is worth it before undertaking a cloud migration. In many cases, though, you may find that it is.

Containers and Microservices

Whether you move your legacy system to the cloud or not, you can—if your legacy-application platform supports it—take advantage of microservices architectures and/or container-based deployment.

A microservice implementation involves breaking complex applications into smaller pieces that operate independently from each other; these smaller pieces are called microservices. This makes applications easier to scale because you can allocate more resources to each microservice on an individual basis. It's also faster to deploy or update a microservice than it is to deploy a larger application.

Containers are a deployment technology that organizations commonly use to host microservices. You can run a different microservice inside each container, making it easy to keep track of which microservices you have running and to deploy new microservices by deploying new containers to host them.

There is an added benefit to containers. Containers represent a form of virtualization, but they don't come with one of the big drawbacks of other virtualization technologies. Traditional virtualization requires services to run guest operating systems on top of the host operating system. The more operating systems you have running on a server, the more CPU and memory you have to provide to the operating systems—and the fewer you have available for your applications. This is not a problem in containerization because containers do not rely on traditional virtualization technology.

Thus, by taking advantage of microservices and containers, you can deploy legacy applications in a more scalable and efficient way. You are likely in turn to improve performance and reduce hosting costs relative to operating your application as a monolith.

The catch here is that not every legacy system supports microservices and containers, so be sure to check your legacy-system vendor's documentation before assuming you can take advantage of these technologies.

DevOps Methodologies

In its narrow definition, DevOps represents the integration of software development and IT operations. More broadly, it refers to a wide range of modern operational techniques and practices, such as the continuous deployment of changes and user-centric application management.

You can leverage DevOps methodologies for legacy apps just as well as you can for modern, cloud-native applications. In so doing, you'll gain more operational flexibility and agility, which translates to higher application availability and an enhanced ability to make changes without disrupting functionality.

Embracing DevOps requires changing the way your organization thinks about software delivery and management; it may require adopting some new tools, too. But the effort is almost always worth it.


Thanks especially to the AI revolution heralded by generative-AI tools such as ChatGPTartificial intelligence (AI) and machine learning (ML) are transforming all sectors of the technology industry.

This technology is still maturing, and it's too soon to say exactly how it might support legacy-system transformation. But going forward, efficiency-focused organizations might use AI and ML for tasks such as, for example, parsing the configurations of legacy systems to detect opportunities for improvement. AI could also power chatbots that help to train end users in navigating new systems following a migration or transformation.

I'm being a little speculative here; again, AI tools designed for specific use cases such as these don't yet exist. But they're easy to envision—and they're likely to become another tool in the legacy-transformation arsenal for businesses going forward.

Charting a Legacy-Transformation Road Map

The fact that there are many viable routes toward legacy-system transformation is a great thing. Organizations can choose which approaches and methodologies best align with their needs and resources.

But this also presents challenges. If you embark on a legacy transformation without knowing how best to arrive at your destination—or, worse, without being sure what your destination even is—you'll likely become bogged down in inefficient strategies that yield lackluster results.

That's why it's critical to establish a road map that lays out your legacy-transformation strategy and helps you gain buy-in from stakeholders. Creating the road map may involve conducting a thorough assessment of the existing landscape, identifying areas for improvement and innovation, and prioritizing initiatives based on business value and impact.

To generate a realistic legacy-transformation road map, you'll likely need to evaluate the development resources you have available within your organization—and then decide on that basis (1) how many changes you can feasibly make to your applications and (2) how quickly your developers can implement the changes. You'll also want to think about what your most serious pain points are (Application cost? Scalability? Reliability? Something else?) and prioritize them accordingly.

Along similar lines, it's critical to have a strong team in place to guide your legacy-transformation journey. Your team should have expertise in both the legacy platforms you use and the latest innovations in areas like cloud computing, DevOps, and AI. External partners and consultants may be helpful as well—particularly for organizations that might not have in-house expertise in all the areas needed for a successful legacy transformation.

After all, just as you wouldn't want to set off on a cross-country road trip without knowing anything about the roads you'll be traversing or the pros and cons of different routes, you don't want to start a complex legacy-system transformation without both critical knowledge and guiding insight on hand.

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