From my perspective the corporate obsession with microservices is a natural evolution from their ongoing obsession with Agile. One of the biggest consequences of Agile adoption I’ve seen has been the expectation of working prototypes within the first few months of development, even for large projects. For architects this could mean honing in on solutions in weeks that we would have had months to settle on in the past. Microservices are attractive in this context because they buy us flexibility without holding up development. Once we’ve identified the services that we’ll need, we can get scrum teams off and running on those services while working alongside them to figure out how they all fit together. Few other architectures give us that kind of flexibility.
All this is to say that if your current silver bullet introduces a unique set of problems, you shouldn’t be surprised if the solutions to those problems start to also look like silver bullets.
Who at what company is having the conversation “let’s do (generic pattern)” without facing some kind of problem or inherent design need that can be solved by (generic pattern). Do these companies need software developers or did they just notice that all of the other companies have them? Surely some sort of inherent needs are driving their software.
Yeah, I work for one of these companies. Some senior executive quotes some stupid thing Jeff Bezos said about everything being an API and is like “This! We need to do this!”
Nevermind the fact that we’re not AWS and our business has zero overlap with theirs. Nevermind that this mindset turns every service we design into a bloated, unmaintainable nightmare. And, forget the fact that our software division is completely unprofitable due to the checks notes shitty business decisions made by senior management.
No no, we’re going to somehow solve this by latching onto whatever buzzword is all the rage right. Turns out having an MBA doesn’t mean you know shit about running a business.
I was looking up lambda functions for rust because i needed it for something and didn’t know how, what, etc. But searching anything lambda now only shows results for fucking amazon lambda bullshit! Really pisses me off… its fucked 😠
It’s just not worth it until your monolith reaches a certain size and complexity. Micro services always require more maintenance, devops, tooling, artifact registries, version syncing, etc. Monoliths eventually reach a point where they are so complicated that it becomes worth it to split it up and are worth the extra overhead of micro services, but that takes a while to get there, and a company will be pretty successful by the time they reach that scale.
The main reason monoliths get a bad rap is because a lot of those projects are just poorly structured and designed. Following the micro service pattern doesn’t guarantee a cleaner project across the entire stack and IMO a poorly designed micro service architecture is harder to maintain than a poorly designed monolith because you have wildly out of sync projects that are all implemented slightly differently making bugs harder to find and fix and deployments harder to coordinate.
Micro services always require more maintenance, devops, tooling, artifact registries, version syncing, etc.
The initial transition is so huge too. Like, going from 20 to 21 services is no big deal, but going from 1 service to 2 is a big jump in the complexity of your operations.
I still have to find a name for this disease, but it’s somewhat like “you’re neither Google nor Netflix”.
Everything has to be Scalable™ even if a raspberry pi could serve 200 times your highest load.
I’m currently involved with a “micro service system”, that has very clear, legal requirements, so we know exactly, how much load to expect. At most, a few thousand users, never more than 100 working at the same time on very simple business objects. Complex business logic, but technically almost trivial. But we have to use a super distributed architecture for scalability…
I’m guessing you already got an answer for that though when you asked about it.
Could be either “oh you’re right let’s not do that”, or “because we want to design for horizontal scalability rather than vertical in case the demand grows later”, or “the client has requested and it’s paying for this feature” and so on.
It’s because they think it’s what you’re doing for a large project. Simple as that. There’s no future demand, the client doesn’t care, and I’m not right because they said so.
One of our customers recently had tasked us with building a microservices thing. And I already thought that was kind of bullshit, because they had only vague plans for actually scaling it, but you know, let’s just start the project, figure out what the requirements really are and then recommend a more fitting architecture.
Well, that was 3 months ago. We were working on it with 2 people. Then at the end of last month, they suddenly asked us to “pause” work, because their budget situation was dire (I assume, they had to re-allocate budget to other things).
And like, fair enough, they’re free to waste their money as they want. But just why would you start a microservice project, if you can’t even secure funding for it for more than a few months?
In this case, the colleague who had talked to the customers told me, they wanted microservices, because they’d have different target systems which would need differing behavior in places.
So, I’m guessing, what they really needed is:
a configuration file,
maybe a plugin mechanism, and
a software engineer to look at it and tell them the behavior is actually quite similar.
Microservices can be useful, but yeah working in a codebase where every little function ends up having to make a CAP Theorem trade-off is exhausting, and creates sooo many weird UX situations.
I’m sure tooling will mature over time to ease the pain of representing in-flight, rolling-back, undone, etc. states across an entire system, but right now it feels like doing reactive programming without observables.
And also just… not everything needs to scale like whoa. And they can scale in different ways: queue up-front, data replication afterwards, syncing ledgers of CRDTs… Scaling in-flight operations is often the worst option. But it feels familiar, so it’s often the default choice.
The problem is that all projects start small, and frankly most of them die small. Aiming for microservices architecture right away is a surefire way to get the project killed before anyone would benefit off of the microservices.
I always lump microservices architecture as premature optimization, one that should be used when you’re maxed out of resources or everything is too spaghetti.
I love the idea. And I even pitched it for a specific project. But I had to eat humble pie when the devops nerds threw more servers at the problem and it worked better than I expected.
The other angle is the majority of Devs are just… Not good…
A good Dev in the situation you mention will design the solution needed now not the one you hope for later.
I’m saying this as someone who has been mired in scope creep and over engineering solutions many times in my life because “what if 5000 people need to use it at once?!”
In most cases all you need is a database, a single thread and a simple API. Build it and then as the problems come grow with them. Try to take into account issues of scale but realize you can’t and shouldn’t solve every scenario because there are too many variables which may never exist.
A good Dev in the situation you mention will design the solution needed now not the one you hope for later.
Maintainability is one of the most important if not the most important goal when programming. If a dev only designs a solution that fits for exactly the current situation but doesn’t allow any changes, it’s not a good dev.
But yeah, if you start small, a solution that’s made for that is preferable. You can still refactor things when you get magnitudes larger and have the budget.
The tricky thing about software development is this balance: you don’t want to hobble your system by designing only for today, because that could waste a whole lot of time later when needs change, but you also mustn’t paralyze the project by designing for all possible tomorrows. Finding a middle path is the art, and the only proof that you got it somewhat right is that things get done with relatively few crises.
You evidently haven’t met my colleagues. There are always people who go for the quickest hack despite the trouble it stores up for later, and they’re usually encouraged by management.
Often a simple solution is the most maintainable solution. In my experience, the code that’s most difficult to maintain are often made by devs who tried to plan ahead. The code turns over engineered to allow for stuff that never materialized.
Microarchitecture needs to be broken up into components. Those components need to send messages to each other. Components sending messages to each other is arguably the core of what object oriented design was trying to do all along. If your devs were bad at classifying components in an object oriented design, then they’ll probably be bad at it in a microarchitecture, too. Worse, the actual system is now likely spread amongst many different version control repositories, and teams stake out ownership of their repositories. Now you get more blockers spread amongst several teams.
Where the network layer comes into play is to replace something that used to be running in a single CPU core, or sometimes different cores on the same motherboard. Unless you can exploit parallelization for your use case, the kind where you have more threads than the number of CPU threads a single motherboard can handle (which can be several hundred on current systems), this will always be slower.
Most software developers have no concept of real world limitations and issues like tolerances, failure, probability, latency, hysteresis, ramp-up etc. because they’re not engineers.
Normally they’d be expected to at least account for software-specific aspects like ACID or CAP or some vague awareness of the fact that when you’re dealing with multiple systems the data may not always arrive as you expect it, when you expect it. But even that is a crapshoot.
Typical issue of the corportate programming world being a hivemind. Just because many big tech companies use it you can’t blindly implement it for your 5 developer team.
And it for sure has its usecases - like if you run something with constant load swings that does n’t need to be 100 percent accurate like Youtube it makes sense. You can have a service for searches, comments, transcoding, recommendations, … which all scale independently trading in some accuracy. Like when you post a comment another person doesn’t need to see it within 1 second on another comment service instance.
It’s a tool like any other, appropriate under some circumstances and inappropriate in others.
Blindly rejecting it without considering whether it’s appropriate in the context is honestly just as bad as choosing it without considering whether it’s appropriate in the context, fwiw.
The problem is that they become a buzz word for at scale companies that need them because they have huge complex architects, but then non at scale companies blindly follow the hype when they were created out of necessity for giant tech stacks that are a totally different use case.
They add a lot of overhead and require extra tooling to stay up to date in a maintainable way. At a certain scale that overhead becomes worth it, but it takes a long time to reach that scale. Lots of new companies will debate which architecture to adopt to start a project, but if you’re starting a brand new project it’s probably too early to benefit from the extra overhead of micro architectures.
Of course there are pros and cons to everything, don’t rely on memes for making architecture decisions.
I guess I’m not sure how others build with micro services, but using AWS SAM is stupid simple, and the only maintenance we’ve ever had to do is update a Node version. 🤷
Problem is that companies are using them for all scenarios. It’s often their entire tech stack now, with kubernetes.
It’s similar to the object oriented hype that came before it, where developers had to write all their programs in a way so they could be extended and prepared for any future changes.
Everything became complex and difficult to work with. And almost none of those programs were ever extended in any significant way where object oriented design made it easier. On the contrary, it made it far more difficult to understand the program since you had to know which method was called in which object due to polymorphism when you looked at the code. You had to jump around like crazy to see what code was actually running.
Now with kubernetes, it’s all about making the programs easier to scale and easier to develop for the developers, but it shifts the complexity to the infrastructure needed to support the networking requirements.
All these programs now need to talk over the network instead of simply communicating in the same process. And with that you have to think about failure scenarios, out of order communication, missing messages, separate databases and data storage for different services etc.
If object oriented design is fundamentally about components sending messages to each other, then microservices are a different route to OO design. If people are bad at OO design, then they’re likely bad at designing microservices, as well. The two aren’t so separate.
All these programs now need to talk over the network instead of simply communicating in the same process.
This is where things go really wrong. Separating components over the network can be useful, but needs careful consideration. The end result can easily be noticeably slower than the original, and I’m surprised anybody thought otherwise.
I don’t disagree with there being tradeoffs in terms of speed, like function vs network requests. But eventually your whole monolith gets so fuckin damn big that everything else slows down.
The whole stack sits in a huge expensive VM, attached to maybe 3 or 4 large database instances, and dev changes take forever to merge in or back out.
Every time a dev wants to locally test their build, they type a command and have to wait for 15-30 minutes. Then troubleshoot any conflicts. Then run over 1000 unit tests. Then check that they didn’t break coverage requirements. Then make a PR. Which triggers the whole damn process all over again except it has to redownload the docker images, reinstall dependencies, rerun 1000+ unit tests, run 1000+ integration tests, rebuild the frontend, which has to happen before running end to end UI tests, pray nothing breaks, merge to main, do it ALL OVER AGAIN FOR THE STAGING ENVIRONMENT, QA has to plan for and execute hundreds of manual tests, and we’re not even at prod yet. The whole way begging for approvals from whoever gets impacted by anything from a one line code change to thousands.
When this process gets so large that any change takes hours to days, no matter how small the change is, then you’re fucked. Because unfucking this once it gets too big becomes such a monstrous effort that it’s equivalent to rebuilding the whole thing from scratch.
I’ve done this song and dance so many times. If you want your shit to be speedy on request, great, just expect literally everything else to drag down. When companies were still releasing software like once a quarter this made sense. It doesn’t anymore.
On the contrary, it made it far more difficult to understand the program since you had to know which method was called in which object due to polymorphism when you looked at the code. You had to jump around like crazy to see what code was actually running.
I agree with this point, but polymorphism is often the better alternative.
Using switch statements for the same thing still have the problem that you need to jump around like crazy just to find where the variable was once set. It also tends to make the code more bloated.
Same with using function references, except this time it can be any function in the entire program.
The solution is to only use polymorphism when it’s absolutely needed. In my experience, those cases are actually quite rare. You don’t need to use it everywhere.
Yeah I agree. With experience you know where to use it and where it really shines, and when not to use it because it will just make everything harder to reason about.
But a lot of devs are not that experienced when they make these decisions. All of us learn from mistakes, and those mistakes stay in the code base. :)
Add comment