Updating a legacy codebase is like renovating an old house—you want shiny new features without the roof collapsing. To keep things stable, I start by using version control (hello, Git!) so I can undo any “oops” moments. It’s like having a time machine for bad code decisions. Next, I make sure to write tests—lots of them. Unit tests and integration tests are my safety net, catching bugs before they cause chaos. Finally, I refactor bit by bit. Instead of tearing down the whole house at once, I fix one room (or function) at a time to keep the rest standing.

Start by identifying and isolating critical areas of the legacy code that must remain stable. Introduce incremental, small changes rather than large overhauls to reduce risk. Implement thorough unit testing and integrate continuous integration to catch issues early. Prioritize refactoring with careful testing and peer reviews to ensure stability.

Here is the biggest secret to keeping stability, deploy small changes and "evolve" your project, not revolutionize it. Small changes over time is much easier to do and improve upon. But it is also great for keeping the features coming out and your marketing and sales teams will have something new to share with customers regularly. Don't be a flash in the pan and try to struggle your way through the rest of the year with no major features after having blown them all in one event.

Start with small and non-critical parts of the system, write thorough and comprehensive tests to each component. Push to prod only if it passes tests.

In my Opinion, the following steps can work: 1. Invest in comprehensive testing to validate functionality and catch regressions. 2. Adopt a gradual, incremental approach to introducing changes with feature flags. 3. Prioritize refactoring and technical debt reduction for better code quality. 4. Implement robust monitoring and observability to quickly detect and troubleshoot issues. 5. Foster collaboration and communication to align stakeholders and end-users. 6. Leverage automated deployment and release processes to minimize human error. 7. Incorporate chaos engineering practices to identify and address potential points of failure.