Organizations often choose to leave sleeping legacy apps lie

DevOps teams may not always have deep knowledge about the legacy systems that are running their business. They understand that moving one or more components of an application from a multi-stack application architecture can sometimes have far reaching and unintended consequences. So, the lack of solid information coupled with unintended consequences often result in organizations choosing to leave sleeping legacy apps lie. As a result, it’s common for organizations to still be running 20-year-old applications on unsupported and unsecured operating systems. 

Artificial Intelligence (AI) has been around for decades, but perhaps has never been more in the press than now. Recent breakthroughs in the field show that we can use AI to move legacy Windows Server applications to modern, faster, and secure servers. For example, AI can learn, analyze, and move legacy apps to modern Microsoft OS versions. 

The burden and cost of legacy applications

Moving a business-critical legacy application understandably seems fraught with risk to a DevOps team; the app might break if you move it or moving it might impact dependent systems. Business could be disrupted. 

Moving applications appears challenging and onerous. DevOps teams likely don’t have accurate runbooks, source code, or install scripts for many of the legacy applications the company relies on. Learning about legacy applications centres on shared tribal knowledge and application archaeology. App owners are often not sure how legacy apps work nor know all of their external dependencies. Moving applications to new servers by hand is slow, painstaking work, which developers and DevOps teams prefer not to get mired in. And who can blame them?

DevOps is often between a rock and hard place: at the end of the day, they’re being asked to choose between the possible and significant security exposures inherent in an unsupported environment or risk breaking the system by moving legacy apps. 

It’s important to remember, however, that choosing to NOT move legacy apps is NOT equal to freedom from risk and expenditure. There’s a hidden cost to doing nothing. Legacy applications create financial and security exposures for businesses. Because legacy applications are viewed as unmovable, they prevent businesses from:

  • using modern DevOps tools to manage applications on modern servers
  • embracing new, lower cost Cloud platforms and other innovations

AI unlocks application discovery and migration

If we take advantage of AI, we don’t need runbooks, original source code, install scripts, or even human knowledge. When AI software is applied to legacy applications, it can dynamically discover, in real time, application components that are required to move legacy apps to a new OS. The software can traverse the entire directory, file, and component structure to discover which elements are required to run an application on a modern OS. AI can also dynamically determine where those components should go on a modern operating system, to ensure that the moved application functions correctly on a new server. 

AI can learn about and analyze an application in a fraction of the time that it would take a skilled person to perform the same tasks. AI has been proven to move legacy applications to new server environments, both in-house and to the Cloud, with at least a 10 times improvement in productivity compared to manual efforts. Moving a complete application state (all historical configuration information, patches, etc.) to a new OS without AI might might well be viewed as insurmountably challenging. Theoretically, you could empty an Olympic pool with a tablespoon, but would you really want to?

Leveraging AI to move legacy applications to fast, secure, modern servers is arguably the best first move for a DevOps team. This holds true even if you’re planning application redevelopment in the future, because when that time comes you’ll be able to build the new app using modern tools available on a modern OS. Better tools and performance will yield better results for your future redevelopment project. 

AI is here to stay. As Towards Data Science says, “Artificial intelligence is moving forward, and whether we like it or not, machine learning will play an essential role in our technological future. The largest and best companies in the world already know this, and they are investing heavily in AI.”

Thanks to AI, we finally have help to move the backlog of legacy apps

There’s still a huge backlog of legacy applications running on old unsupported servers. An estimated 10 million WS2000 and WS2003 servers still run production applications, and more than 50 million WS2008 servers are in production worldwide. Let’s not forget that WS2008 comes to End-of-Support on January 14, 2020. Thanks to AI, we finally have the automated help we need to re-install the production state of legacy applications on modern, fast, and secure servers. 

When it comes to legacy systems, AI lets a DevOps team address the cost and risks of running applications on unsupported servers. It not only saves us time – it buys us time. It lets a DevOps team plan for proper application redevelopment, when the time is right, leveraging all the benefits of a modern server environment.

AI is the magic at the heart of the VirtaMove toolset. It helps us dynamically discover applications, learn legacy applications and their dependencies, build libraries of migration  templates, and more. If you’re ready to move your legacy apps with the help of AI and machine learning, don’t hesitate to email us or give us a call. We modernize applications and move them to new secure Windows operating systems every day with our patented migration technology and are pleased to share what we know.