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Rewrite, refactor, knee-deep in legacy - part one

From time-to-time we encounter some legacy projects - or the braver developers even work on them day after day. :) When working on such projects we do come across the exclamation that: “Starting from scratch would be quicker than trying to fix this mess!”. This normally comes from the frustration that legacy projects can cause.

There are already lots of articles out on the interwebs about refactor vs rewrite. Failure and success stories and would encourage those who don’t have experience in deciding this question to read many articles, pro and con. This article includes a few good one:https://medium.com/@herbcaudill/lessons-from-6-software-rewrite-stories-635e4c8f7c22

So where do I stand with this question? Personally I like to work on legacy systems, one can feel like Indiana Jones exploring hidden gems, funny comments and many odd solutions. Apart of this archaeological work when you just correct a small bit on legacy code that can sometimes yield huge performance improvements that makes work on them quite rewarding. So from this you can guess that I’m more towards the refactor end of the scope. In my experience rewrite from scratch doesn’t work on larger systems.

Got two rewrite stories to share. Long-long time ago I had the chance to partake in a full rewrite of a large system that turned out to be the text book example of the struggle and up hill battles. Second is a smaller project but was a good reminder for me why I don’t like rewrites.

The System

The system that I have had the chance to contribute in rewriting was like this: had a legacy code base in python using Django with a MySQL database, then there was a proof-of-concept app written next to it in NodeJS using MongoDB. This PoC app supposed to be temporary. Yes, this is the point where you can already start to laugh, like that ever happens… temporary…, of course it went to production and the temp PoC solution hunted the company for 3+ years.

We tried to fix up the temp solution to get it into shape and avoid throwing ever growing amount of money on CPU/memory/DB and network resources. But the beast always managed to grow another head. This was the point where the lead at that time decided to start over: clean slate.

Lesson #1: when you create a PoC or temp solution it still need to adhere to the highest quality standards. In our case it was a rushed steaming pile of spaghetti, straight from the stow.

Rewrite

Now we have an instable PoC system in production and a stable but painfully slow legacy system. How would you go about the rewrite? One could say divvy up the system and start rewriting small portions of it. Yeah, one could definitely take that path, but that wasn’t the one we picked.

We started to create a parallel system from scratch dreamed up all the microservices ahead of time. Decided to continue to use NodeJS with MongoDB as that was already the hype back then. We created a synchronization service that would actively bring data over from the old python system. The legacy and the PoC was all used in production and we wanted to test early the new microservices as well so we constantly synced data over to the system that nobody used yet.

The development teams were divided along the new and old systems. There was a larger development team supporting the old system that was actively bringing in money for the company and paying all of our salaries. Another smaller team had the marvellous job of learning about new technologies and write the microservices that will be the new system that will save us all.

I’ve had the chance to be in both of those parts (supporting the legacy and help with the rewrite) actually neither side is fun. Supporting the old application had the pressure from the clients that they needed newer and newer features, hunting bugs, dealing with downtimes. Reward part here was that when you have done something you got instant feedback on your job. In the rewrite team you get the pressure that everybody is waiting for this saviour system to come. They expect to get a system that will solve all their problems, it will solve their insomnia, it saves their marriage, they will be better parents and the new system will even make them coffee in the morning. Also there is more developers on the old system cranking out newer and newer features that the new system of course will support! :D

Catching the ever growing features of the system we would like to replace is just like Don Quichotte fighting with the windmills. You have very small chance of winning. We actually tried to push back on the adoption of the new system saying that its just not yet ready. But eventually we all agreed that it will never be fully ready and at one point we need to start using it.

Adaption of the new system

The whole team saw that we won’t be able to reach feature parity. For the adoption we pick a client that had the least need of custom features and set them up with the new system.

There were a lot of hick-ups, we were correcting a lot of bugs and mistakes that came from the fact that the new system was also rushed. It didn’t become spaghetti and thanks god we did write some tests - unlike the mentioned “temp PoC” project that had zero tests. But eventually the new system was working, it started to generate income for the company! To get to this point it took the teams about 2 years!!! Also there was one big challenge still remaining: get all the clients on it.

Migrating the clients was the next stage of the rewrite. Clients shouldn’t need to know about the changes we make in the background. They have a service that they expect to get regardless if the backend is python or nodejs or assembly. Interesting to note here that the service provided by the system relied on historical data. That data was all in the old system! All that data had to be converted and moved into the new system. This task was the one I actually ended up enjoying maybe the most. Luckily the conversion wasn’t too complex and it was interesting to see that we filled up the new databases through weeks of carefully controlled migrations. Had to be careful not to over load the old system. Then after all that: it worked! The system manage to show the same reports to the users just like the old system! 2-3 years and we managed to get to the same point as where we were before! :D

Different way

The temp PoC system was some sort of microservices architecture, sometimes we were joking about it saying its a micro-monolith as 4 services were serving it. The python legacy system was monolith. New system with the planning up front without good experience with microservices was more towards a distributed monolith with ~8 services serving the flow. We managed to change on this over time (without starting from scratch).

Thinking back of the decisions and what happened during the rewrite, frustrations from both development and customer service teams, if I would have to do the whole thing all over again, then would choose a different path.

Starting again with a monolith system would look at the processes and would try to move out small parts of the big service to a new microservice. Breaking down the monolith bit by bit, so that all parts are constantly in use and being validated. When we were doing the rewrite and testing we didn’t test the system with high loads. Of course everything was working on low loads and amazing developer computers, but when it went to production and came the load there were lots of performance issues.

Outro

In the above case rewrite was a bad decision in my opinion, but still we managed to get it working. There are cases where you have no other choice than starting from scratch. In another post I’ll share a story where I did a full rewrite and would do the same again in that situation.

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