It’s commonly accepted that in order to prioritize application delivery, there is an implicit cost of accruing technical debt in the form of leaving legacy code in apps for 5, 10 or 20 years. But what if you could eliminate that technical debt quickly and efficiently, upgrading from old to new language and dependency versions (skip the incremental upgrades) with just a few clicks?

The problem is that updating an entire application can introduce breaking changes, especially when your in-house expert who built the original has left the building. And what else could that time be spent on? Estimates show developers already spend 20-30% of their time on pure maintenance. It usually isn’t worth it to spend more time on updating an application that still works, even if it’s older than dirt.

Yet open source software supply chain risks are at an all-time high, and with the power of automatic upgrades, now is the time to upgrade your thinking from all the “why nots” to the “why not now”. Push-button migration, you’re our only hope!

In this webinar, we discuss how you can get your legacy codebase current, and stay current with up-to-date open source language versions, using as an example Python users looking to get off 2.x and move to 3.8 and later.

We’ll cover:

• Causes of tech debt: Starting with unsecured codebases, getting out of date, and downloading prebuilt binaries
• Change drivers: Software supply chain risks, the nature of modern apps, and EOL languages like Python 2/3.7
• Future-proofing: How automatically refactoring your code with foresight of any breaking changes is now possible 
• Automating maintenance: Building dependencies from source and integrating them into your CI/CD pipelines, and creating consistent environments across your team, with full observability of what open source is deployed and where

Don’t let the hidden costs of maintaining open source stop you from going back to the future. Get rid of technical debt so your team can focus on innovation!

Key Takeaways:

• Understand the costs and risks of open source tech debt, i.e. supply chain security, open source dependencies and EOL languages like Python 2/3.7
• Ways you can automatically build dependencies from source and refactor your code with foresight of breaking changes, while providing observability and scalable consistency of your open source environments