Rearchitecture is a sign of success not failure

An important lesson for a software architect is to design the system for the requirements you have today not for what a possible future could look like.

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A lot of systems are built with accidental complexity that could have been avoided. I’ve seen really complex high performant code for a system that is used by 10 users, a microservices solution containing 40+ services all maintained by one small team, a real-time event source setup for a system that is mostly CRUD and I can keep going…

There is a reason that Martin Fowler talks about a monolith first approach.

So if you need to built a system that should support 50 customers, don’t build one that can support 50.000 customers. Start small and wait until you have that many customers that they start to overload your system. And that is great news because it means that you are successful!

The truth is the majority of applications are never going to reach that stage. And even if you do start to get overloaded it’s usually not an all-or-nothing issue. You’ll have time to adjust and respond to the problem. Plus, you’ll have more real-world data and benchmarks after you launch which you can use to figure out the areas that need to be addressed.

The fact is that everyone has scalability issues, no one can deal with their service going from zero to a few million users without revisiting almost every aspect of their design and architecture.

—Dare Obasanjo, Microsoft (from Scaling Up and Startups)

So if your application becomes successful, you’ll certainly have to rearchitect (parts of) your system. And if your system doesn’t have to change for scalability reasons, it will certainly have to change because these new customers will come with their own list of requirements that require your application to evolve.

Still not convinced? Have a look at the presentation about Minimum Viable Architecture by Randy Shoup. In all examples he is mentioning, the architecture went through multiple iterations.

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME ...

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...

A complex system designed from scratch never works

A few years ago, I worked as an architect on a big mainframe rewrite. I still count it as one of my failures. Not because the technology was wrong, but because I couldn't convince the management team to simplify the approach. Years later, the organization is still struggling to get the new system up and running. I left the project at the time, because I couldn't put my name behind an approach that would take very long and cost a lot of money without a working system to show for it along the way. Gall’s Law That memory keeps coming back to me, because it's a textbook case of Gall's Law playing out in real life. Gall's Law , from John Gall's Systemantics , states it plainly: A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works, and it cannot be patched to make it work. You have to start over with a simple system that works. What does that mean in practice,...

The art of simplicity

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