Re-platforming is the process of moving a system to a new platform. Imagine taking an ASP.NET/SQL Server website and moving to Azure Functions on Azure SQL Database. Or maybe taking a Java client/server app with Oracle and moving it to a series of microservices against MongoDB. Those changes could be a net benefit to your organization in the end, but they aren't quick or easy. They're often fraught with various challenges that can cause a lot of stress while creeping over budget.

There's a post that talks about some of the things you might think about if you embark upon a re-platform. Often this takes place when an organization is looking to modernize their tech stack. Quite a few of the technology DevOps success stories take place when the older structures are not maintainable, but also not able to handle increased workloads or performance requirements.

It's often said that a complete rewrite rarely makes sense. I think that's likely true, but that doesn't mean it isn't something you should do. It says that you should rarely do it, and you need to pick a good time when your old application, database, network, or some combination of these can no longer meet your anticipated future growth demands. This is likely a debate that your organization should have every year or two and ensure that continued investment in the current platform makes more sense than a new one.

Once you decide to move forward, it will be a journey, which means understanding how new and old systems will interact becomes important. Compatibility, at least for some time, is very important. I'd say this is especially critical for how your data systems will work together and what options you have to replicate/ETL/etc. the data between systems.

Even if you plan to make a cutover from one system to another, data migration is fraught with issues. Anyone trying to ensure data moves cleanly from one place to the next should have strong checks, usually with automated tests, that evaluate if your data is moving correctly. Row counts aren't enough, or not the only metric. Random checks of individual rows, as well as checks for outliers, should be a regular part of any project that will migrate data. Learn where you struggle to correctly transform data because there will be places where this happens.

I don't believe that wholesale re-platforming often makes sense. Leaving SQL Server to go to another database platform, or even when you might try to change the paradigm with NoSQL or a Data Lakehouse, often costs a lot. Getting a return after staff training, migration costs, and even delays from inefficiencies during the process often equals many years of licensing. I think slow migrations are a better idea, perhaps adding something like ElasticSearch or Redis, experimenting with a small data lakehouse for a particular purpose, and replicating some data to Neo4J for complex hierarchy queries. These evolving mechanisms give you the chance to experiment and learn about the process. It will help you understand if there is a positive ROI if you continue.

In many ways the world of technology changes slowly. We have lots of new shiny toys, but many of them don't magically solve your problems. There are always tradeoffs and without strong domain knowledge, you may have more unknown unknowns that reduce your chances of success. Re-platforming can work, but make the decision carefully and proceed methodically, not with haste.