Scalability is not a problem: you have, you will have, you should plan for, you should build for, nor allow anyone to utter the S word. Simplicity is the correct word to use.
The ridiculous things I was asked to do, and observed other people doing, all because "one day we will gave thousands of clients" while at the same time struggling to push out just a few units.
Nodejs + typescript is superior across almost every dimension other than data science and familiarity.
People think it’s apples and oranges but it’s not. Also don’t forget golang too.
If your app is Python in the beginning then you’re pretty much locked in. It’s doable, but you’re going to be dealing with a lot of Python specific warts.
Python is a perfectly fine choice for a tech stack. Just because you don't like something doesn't make it an anti-pattern. NodeJs + TypeScript have tons of warts of their own that you have to deal with as well. Every language does.
There’s a third type of language: Python. Actual poor choice for a startup, independent of complaints.
You’ll note my complaint here is actually remarkably unique. You will rarely hear a person who is an expert in both TS and Python say definitively TS is better.
Many people who know both stacks well always maintains some kind of apples and oranges opinion about it. It’s like agnosticism.
Nah but the warts are minor compared with other languages. Python is guaranteed to hold you back.
First it’s the worst performing language for the application stack (only among the most languages for that area). Second type checking on Python is raw garbage.
Third you’re going to have to use TS for the frontend anyway. You can’t escape ts. Choosing Python(or any other language) forces you to have redundant code in two languages. Ts is the overall best startup stack and a huge part of it is because the frontend requires ts anyway.
> Third you’re going to have to use TS for the frontend anyway. You can’t escape ts.
This is obviously wrong. Sure you have to use Javascript for the web frontend that has interactivity without round-tripping to the server. Typescript compiles to Javascript, but its hardly the only language that does.
If you're frontend is a mobile app only then you don't even have to use Javascript for it all.
I’m talking about mainstream choices. I’m well aware of alternatives.
Would not recommend alternative choices for a startup. Those offer a larger element of risk. I would choose Python over any other non mainstream alternative.
having built two enterprise data platforms in python, I can't disagree more. for a startup, development velocity matters more than code performance especially for a CRUD app even at medium scale. Frameworks like Django simply enable you to do so much and so quickly. and you can reach world scale, that's what Instagram did!
Having built more than two enterprise apps in Python and many others in many other languages I can say it is certainly possible to build it in Python. But it is one of the worst choices out of all possible languages out of all the other mainstream languages.
Django is fast but has become much less relevant in the age of AI. The issue with Django is you hit issues very early. Within 2 to 3 years of using Django the warts of using Django become apparent. Django is mostly a good tool for the first year, but if the tool survives beyond that, Django becomes more of a liability.
I don't see how it's a bad choice on its own merit. Lang choice will always be a mixture of familiarity (team or individual) and niche problem needs (some edge cases need specific tools).
I personally avoid to touch anything that is nodejs related because I do jot trust its ecosystem (npms).
Wow. I cannot believe in good ‘ol 2026 there are still people who believe a whole successful programming language could be the reason for a failed experiment (startup). If your startup is solving a real problem, choosing the “wrong” language could never be the reason it fails.
Except I never said it’s the whole reason for a failed startup. You’re just making shit up out of thin air.
Choosing a wrong language can be a factor for failure. This is possible but rare. For example choosing Python for a triple A game engine.
Mostly choosing the wrong language results in pain and friction and extra work. These things are enough for me to consider a choice wrong. You don’t need the language to bring down the entire startup for me to consider to to be wrong.
For example if you chose nodejs. One application server instance is enough to serve the website and scale for a couple years. If you chose flask… well… setting that up for the same scale would be complicated. Your choice here is proportional to the amount of pain you feel later.
Such anti patterns are like Nostradamus’s prophecies - you see a company flopping then curve fit a narrative to justify the antipatterns.
How do I, as a founder, know that I am falling into an anti pattern? I don’t believe it is possible to know. You can only “know” in hindsight and that makes these anti patterns useless.
>> How do I, as a founder, know that I am falling into an anti pattern?
The easiest way is to have outside advisors who can and are willingto adversarially challenge the assumptions you're making. If you don't have those, good cofounders can sometimes play the same role (although that is harder since they are likely to share similar biases as you).
Seems like a useful list of things to avoid when running a startup, plus situations where it may not always be a bad thing.
Still, got a few thoughts here:
> if you build it, they will come
This feels like the cause for so many news/media bundling services, akin to Blendle. Loads of people seem to have the thought process "no-one pays for journalism, that's because it's too inconvenient to subscribe seperately, let's bundle it all", but far fewer people actually seem to want such a service.
> Chasing Blue Oceans
This feels like the explanation for the Wii U, despite Nintendo obviously not being a startup of any kind. The Wii was a blue ocean product, and the company clearly thought the same logic could apply to its successor too. Find an idea that didn't have much competition (using a portable screen to control what's going on elsewhere), and use that to attract a new market.
Unfortunately, while the concept worked on a handheld device, it didn't really feel good to use on a larger scale, and the ideas designed for it (usually some sort of asymmetric gameplay experience) just didn't have the appeal that more traditional ones did.
> Boiling the Ocean
This seems really common with crowdfunded products, since if their scope isn't unrealistic as hell beforehand (and if it wants the public's attention and money, it usually is), it certainly is once the stretch goals start being added and the creators start promising everything and the kitchen sink.
Also with video games, as shown by Duke Nukem Forever, Beyond Good & Evil 2, etc.
> This feels like the explanation for the Wii U, despite Nintendo obviously not being a startup of any kind.
This is a particularly interesting example, because they followed up with the Switch, which is, in some ways, the diametric opposite of the Wii U. Arguably, what happened was that they had the right idea that the hybrid TV/handheld format was the right blue ocean play, but the Wii U failed by being TV first and handheld second, instead of handheld first and TV second. You could probably build a whole business strategy course on just this discussion.
I don't think that's the real cause for the Wii U's woes. Consoles from the big players are almost automatic buys for a lot of people, just to get access to the new games. They have to screw up to change that. No one was particularly bothered by what the Wii U offered, even though it wasn't really compelling.
I hold that the Wii U was primarily an advertising problem, with a dash of the Wii itself being an anomaly.
Is there an N=1 anti-pattern on the list? I built an enterprise platform on a low 6 figure annual contract for my first customer. It’s looking like there are no other customers who desire the same type of platform.
FWIW I think it is miscategorized. "Build it and they will come" is a different type of problem: it commonly refers to building something thinking that its value and usefulness are self-evident that it will sell itself, and therefore one needs no sales or marketing.
I worked at a startup that did this and it was... totally fine? Like, we hired a guy who knew how to set Kubernetes up, he spent like a week or two setting it up, and then it was totally solid and the development experience was great. I was building some of the core product-specific logic and it only made my life easier.
Which really just goes to show that the "legible" aspects matter far less than the illegible aspects. It's easy to say "hey, this startup is using boring technology and deploying a monolith, great!" or "Kubernetes and a bunch of services, over-complicated!". It's hard to say "hey, this startup's codebase is awful and it's an unforced error slowing them down" vs "hey, these guys are taking some shortcuts but it makes sense in context".
But a mess built on "boring", simple tech is going to derail you far more than a needlessly complex but well-executed setup.
I remember reading an article years ago about how a company was running rings around its competition because they were releasing features faster and more effectively, due to their choice to use Lisp as their language. Of course a competitor who tried to pivot to Lisp was unlikely to have the same results - the specific language choice was not nearly as important as the fact that the founders were already experts in Lisp.
The point being, Kubernetes is easily the right choice for a start-up if you have a Kubernetes expert on the team (and the rest of the team is willing to put the time in learning the system and not just cargo-culting around it)
The issue with many critiques like this is that “it depends” and that many of these strategies actually work while often they do not - but given that most startups fail even generally successful strategies will have a high rate of failure.
And the people that study these types of lists to apply it to their own case are then engaging in “analysis paralysis” because the list is so long you are bound to be caught up by it.
So while I think it is useful to critique your idea and business the best thing to do is to try and sell it and make money and keep adjusting and trying new things to maximize your income. There is no magic bullet.
Some seem to treat microservices as a sign of good engineering when it's often just premature complexity. You can always split a monolith later, but you're stuck maintaining that complexity from day one
Big companies mostly seem to use the microservice(s) per team model. If your whole company is two founders, one account manager, and an engineer, you only have one team.
It can make sense to have more than one service for purely technical reasons. I once worked on a friend's startup where we built a separate ingress microservice so we could scale it independently from our monolith. There's no organisational benefit to doing so, however. The technical founder and the one engineer are hardly going to block each other.
Been there before - I worked at a company where some geniuses thought that microservices would solve all of our scaling issues. We ended up with four microservices just to send an email (one to template, one to send, one to persist to database and one other which I can't remember now).
This was all on-prem stuff. But it was taken to ridiculous extremes. I've worked on something that was a knot of message queues but there was one email service.
Multiple services using the same database will typically end poorly. When schemas or indexes change, how will that affect all of the different services? How do their read/write patterns differ? When one service needs to scale, will the additional connections starve the other services? And worse, if a service ends up moving to a different team or department, who controls the database?
I prefer a service that fronts the database. Swap the database, scale it, whatever, and clients keep going.
"When schemas or indexes change, how will that affect all of the different services? "
It's absolutely horrible. Now all the services are tightly coupled without the devs really realizing this. And the side effects of database changes can be super subtle and hard to predict.
I think the example I gave is a good counterpoint:
- you have a monolith, and it handles normal API traffic patterns
- you have a workload that involves different hardware needs e.g. extremely high throughput relative to the rest of the system (video streaming would be an example), GPUs, high memory requirements with low CPU or vice versa, etc.
Solution is to deploy a service that only handles the specific workload. Whether or not this is a microservice probably depends on your point of view but I'd argue it's at least close.
I have been building a SaaS for a business. One of the decisions I took is "as monolithic as possible" (though you cannot just use that).
One reason is that microservice architecture requires much more operational overhead. So any server we have (except for the database) should be self-contained as a rule, so that it can be autonomous and horizontally scalable.
So far, it is working quite well. You do not need suddenly a Redis for one thing, a ZooKeeper for the next one, and 3 or 4 things to just run the damn binaries. The binaries will start, do whatever migrations need to be done if it applies, and start running. They only need the database. They land health checks, api calls and all the logic needed, in one binary with zero dependencies that is containerized.
This has saved me a lot of pain compared to other architectures where I worked, but those were massive and it was justified (and there was budget for it). But you just need a bunch of teams to be able to do that.
I think going the microservices way for a small team not only does not pay off. I think it can be a suicide.
At the same time, I keep the servers internally modular (enable/disable feature).
well... no, splitting a monolith once it has grown past the point where services make sense is incredibly difficult. My last employer spent a couple of years doing it and ultimately gave up. There is just way too much interdependency to split it up cleanly.
So the key here is good engineering leadership to recognize when that point arrives, and push the company to start the transition.
And indeed, microservices solve a organization problem not an engineering problem. When I taught the architecture to new hires, I always say: a service is the largest piece of system that stays together in a reorg :)
That's assuming you don't separate concerns in your monolith into modules with clear boundaries and dependencies. If you did that from day one, splitting a module off to a different service is easy.
I don’t agree. The technical device we use for creating clear boundaries, useful abstractions and managing dependencies in monolithic code is the function/method/procedure call.
The history of distributed software is littered with the corpses of attempts to make the RPC look like a function/method call (I worked for a CORBA vendor decades ago). But these two techniques are so different on a fundamental level they are not substitutable except in the most trivial cases. The compute and elapsed time RPC overhead which makes perfectly good local abstractions completely impractical across a network. And then there are the differences in terms of failure modes, concurrency and synchronicity.
So even a beautifully designed and layered piece of “monolithic” software with a code base costing of coherent and clean abstractions will not be easy to port to a microservices/distributed architecture.
If you can manage that then there's no real benefit to microservices though. The reason for splitting is to solve the problem of failing to separate concerns, so a team that can't do that well is better off building microservices from the start because the alternative for them is building a monolith that will be hard to split.
I worked at a startup where a new architect decided everything needed to be split into micro services for “scaling”.
Thing is we were in an illiquid market that didn’t require the kind of scale he envisioned.
Long story short we burnt a hell of a lot of runway building something that was painful to work with compared to the monolith. It did not end well.
Micro services are something that sounds good to the inexperienced but are almost never right for an immature business looking for market fit.
If you really know you can’t scale with just a big box from the outset use something like Elixir or Erlang. Otherwise stick to a modular monolith for as long as you can.
Yes. One of the better startups I worked for did it that way. There was a single, mono-repo style code base with multiple services. Some were more micro than others. They shared common code like model definitions.
Everything was built/deployed in a single release (unless there was a hot patch, emergency bug fix, in which case we "could" work around it if needed.)
With microservices they're obviously complicated, and that's better. There's a complexity in monoliths as well, but it's hidden complexity. That gives developers a false impression that things are simpler.
For example, in microservices if you want some data that another service owns you have to define what it is, write an API, and handle all the fun of network problems. But once it's done you have a nice contract for getting that data.
In a monolith you can just reach over and take what you want. If you know there's a function for getting something you can use it. If you know the instantiated db connection has permission to view a row, just query the db directly. If you want to pipe some data somewhere just add it to the session object and it magically appears where you need it. And so on. You can go so fast! But then someone else does the same thing, and over time your monolith gets slower and slower, and needs more memory, and you find yourself having things on a god object that really shouldn't be there but it's hard to change because the behavior is threaded through everything.
Both of these problems are relatively simpler architectural issues, but it's always preferable to have well-defined complexity over accidental complexity. If you can define how code goes into a monolith and stick with those rules then a monolith is great. Most people can't, and I've never seen a company with multiple teams manage it.
That's a modular monolith, not microservices. It's a nice architecture for dev but it comes with a downside that you need to deploy everything whenever there's a change. You usually end up with a complex release train process. Again, the complexity is still there, but it moves. Where your complexity lives is a choice.
Validation is shorthand for saying "I don't have deterministic skills or knowledge hence I will rely on user behaviour to drive the product".
Works out for many people and usually ideal for beginners. But post a couple of years, if validation is still your primary model, your model tells you how clueless you are in your domain.
Make logical derivations. Build. Determinism is a luxury only affordable for the ones who put in the effort. Others are doomed to chase validation for eternity.
I have done the startup thing as a failed founder and I myself call these startup patterns or antipatten mostly useless. One who enjoyed them (myself included) are destined to fail and then would concluded the same.
The so-called pattern and antipatten are useless for startup, is just like parenting guides are useless for new parents. The complexity and novel problems are so large in volume that only basic instinct function. And if you are the successful one, you would guide by whatever success brings you, if you are the failed one, well, you can fail and learned that these patterns are useless and rant here like myself.
Sorry but I don't think you read any of the linked articles. Just one example of an anti-pattern that is very common and is undeniably harmful: Bad Revenue.
It comes down to deceiving or annoying your customers. E.g. making cancellation difficult or confusing, tricking the users into buying yearly subscription by showing them the monthly price of the yearly subscription (explicitly prohibited by Apple in mobile apps btw) and many others which can boost your revenue short-term but do a lot more harm in the long term, or eventually even kill your company.
These sales anti-patterns can work for bigger companies that are long past their growth stage and are now looking for ways to squeeze pennies out of every customer. Early stage or growth stage startups should not copy these practices: growth is a very fragile thing that can be destroyed by negative word of mouth easily.
That entry isn’t published yet, but… this can be a viable tactic as part of a larger strategy. I’ve seen people raise significant money by designing for investors, and it got them to where they wanted to be.
Platform risk is real. long back we decided to build a review management platform with Google as main. After building and getting early customers, we changed our office location that triggered to re apply for google business reviews account that ultimately blocked access to the API. They just sent an email saying we are not eligible for accessing Google Business profile API access.
In a startup I worked in we were less than 100 people in total (including product, sales, support etc.). I had to report to my tech lead, who reported to the team lead, who needed approval of the product owner who reported to the CPO
The justification was that we had to be prepared for the scale-up phase. The problem was that we never saw that scale in practice, becausee company had to downsize a year later because we had failed to deliver.
Useful list. Going through this list, I felt it would difficult to not fall for many of them. For example, you want to build enough to go to market early and gain customer validation and confidence but at the same time not build too much!!
Having a good experienced team generally helps in mitigating some of them, especially in tough situations.
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[ 0.24 ms ] story [ 60.7 ms ] threadScalability is not a problem: you have, you will have, you should plan for, you should build for, nor allow anyone to utter the S word. Simplicity is the correct word to use.
Nodejs + typescript is superior across almost every dimension other than data science and familiarity.
People think it’s apples and oranges but it’s not. Also don’t forget golang too.
If your app is Python in the beginning then you’re pretty much locked in. It’s doable, but you’re going to be dealing with a lot of Python specific warts.
You’ll note my complaint here is actually remarkably unique. You will rarely hear a person who is an expert in both TS and Python say definitively TS is better.
Many people who know both stacks well always maintains some kind of apples and oranges opinion about it. It’s like agnosticism.
First it’s the worst performing language for the application stack (only among the most languages for that area). Second type checking on Python is raw garbage.
Third you’re going to have to use TS for the frontend anyway. You can’t escape ts. Choosing Python(or any other language) forces you to have redundant code in two languages. Ts is the overall best startup stack and a huge part of it is because the frontend requires ts anyway.
Also sqlalchemy is pretty garbage.
This is obviously wrong. Sure you have to use Javascript for the web frontend that has interactivity without round-tripping to the server. Typescript compiles to Javascript, but its hardly the only language that does.
If you're frontend is a mobile app only then you don't even have to use Javascript for it all.
Would not recommend alternative choices for a startup. Those offer a larger element of risk. I would choose Python over any other non mainstream alternative.
The only benefit is familiarity and data science. That’s literally it. No one in this thread has stated any benefit in top of node or golang.
Django is fast but has become much less relevant in the age of AI. The issue with Django is you hit issues very early. Within 2 to 3 years of using Django the warts of using Django become apparent. Django is mostly a good tool for the first year, but if the tool survives beyond that, Django becomes more of a liability.
I personally avoid to touch anything that is nodejs related because I do jot trust its ecosystem (npms).
Go use Python for your triple A next gen game rendering engine.
All in all we’re mostly talking about the web stack.
Every tech choice is a lock in.
It’s like php. Facebook got locked into php and had to develop a whole new language around it.
That's the most flattering thing I can think of to say about statements that are so confidently wrong.
Choosing a wrong language can be a factor for failure. This is possible but rare. For example choosing Python for a triple A game engine.
Mostly choosing the wrong language results in pain and friction and extra work. These things are enough for me to consider a choice wrong. You don’t need the language to bring down the entire startup for me to consider to to be wrong.
For example if you chose nodejs. One application server instance is enough to serve the website and scale for a couple years. If you chose flask… well… setting that up for the same scale would be complicated. Your choice here is proportional to the amount of pain you feel later.
How do I, as a founder, know that I am falling into an anti pattern? I don’t believe it is possible to know. You can only “know” in hindsight and that makes these anti patterns useless.
The easiest way is to have outside advisors who can and are willingto adversarially challenge the assumptions you're making. If you don't have those, good cofounders can sometimes play the same role (although that is harder since they are likely to share similar biases as you).
Its a bit like cooking advice
- Products should be fresh
- Use the best ingredients
- Salt early and correctly
- Cook by temperature, not time
And so on but then you cook side by side with a pro chef...and does not taste the same...
Still, got a few thoughts here:
> if you build it, they will come
This feels like the cause for so many news/media bundling services, akin to Blendle. Loads of people seem to have the thought process "no-one pays for journalism, that's because it's too inconvenient to subscribe seperately, let's bundle it all", but far fewer people actually seem to want such a service.
> Chasing Blue Oceans
This feels like the explanation for the Wii U, despite Nintendo obviously not being a startup of any kind. The Wii was a blue ocean product, and the company clearly thought the same logic could apply to its successor too. Find an idea that didn't have much competition (using a portable screen to control what's going on elsewhere), and use that to attract a new market.
Unfortunately, while the concept worked on a handheld device, it didn't really feel good to use on a larger scale, and the ideas designed for it (usually some sort of asymmetric gameplay experience) just didn't have the appeal that more traditional ones did.
> Boiling the Ocean
This seems really common with crowdfunded products, since if their scope isn't unrealistic as hell beforehand (and if it wants the public's attention and money, it usually is), it certainly is once the stretch goals start being added and the creators start promising everything and the kitchen sink.
Also with video games, as shown by Duke Nukem Forever, Beyond Good & Evil 2, etc.
This is a particularly interesting example, because they followed up with the Switch, which is, in some ways, the diametric opposite of the Wii U. Arguably, what happened was that they had the right idea that the hybrid TV/handheld format was the right blue ocean play, but the Wii U failed by being TV first and handheld second, instead of handheld first and TV second. You could probably build a whole business strategy course on just this discussion.
I hold that the Wii U was primarily an advertising problem, with a dash of the Wii itself being an anomaly.
> The founders automatically assumed that if they had the vision and one customer wanted it, many others would
https://www.itamarnovick.com/startup-anti-pattern-4-if-you-b...
Which really just goes to show that the "legible" aspects matter far less than the illegible aspects. It's easy to say "hey, this startup is using boring technology and deploying a monolith, great!" or "Kubernetes and a bunch of services, over-complicated!". It's hard to say "hey, this startup's codebase is awful and it's an unforced error slowing them down" vs "hey, these guys are taking some shortcuts but it makes sense in context".
But a mess built on "boring", simple tech is going to derail you far more than a needlessly complex but well-executed setup.
The point being, Kubernetes is easily the right choice for a start-up if you have a Kubernetes expert on the team (and the rest of the team is willing to put the time in learning the system and not just cargo-culting around it)
And the people that study these types of lists to apply it to their own case are then engaging in “analysis paralysis” because the list is so long you are bound to be caught up by it.
So while I think it is useful to critique your idea and business the best thing to do is to try and sell it and make money and keep adjusting and trying new things to maximize your income. There is no magic bullet.
It can make sense to have more than one service for purely technical reasons. I once worked on a friend's startup where we built a separate ingress microservice so we could scale it independently from our monolith. There's no organisational benefit to doing so, however. The technical founder and the one engineer are hardly going to block each other.
The team was stuck in a mindset that they just hadn't split things up enough to arrive at nirvana.
I prefer a service that fronts the database. Swap the database, scale it, whatever, and clients keep going.
It's absolutely horrible. Now all the services are tightly coupled without the devs really realizing this. And the side effects of database changes can be super subtle and hard to predict.
- you have a monolith, and it handles normal API traffic patterns
- you have a workload that involves different hardware needs e.g. extremely high throughput relative to the rest of the system (video streaming would be an example), GPUs, high memory requirements with low CPU or vice versa, etc.
Solution is to deploy a service that only handles the specific workload. Whether or not this is a microservice probably depends on your point of view but I'd argue it's at least close.
One reason is that microservice architecture requires much more operational overhead. So any server we have (except for the database) should be self-contained as a rule, so that it can be autonomous and horizontally scalable.
So far, it is working quite well. You do not need suddenly a Redis for one thing, a ZooKeeper for the next one, and 3 or 4 things to just run the damn binaries. The binaries will start, do whatever migrations need to be done if it applies, and start running. They only need the database. They land health checks, api calls and all the logic needed, in one binary with zero dependencies that is containerized.
This has saved me a lot of pain compared to other architectures where I worked, but those were massive and it was justified (and there was budget for it). But you just need a bunch of teams to be able to do that.
I think going the microservices way for a small team not only does not pay off. I think it can be a suicide.
At the same time, I keep the servers internally modular (enable/disable feature).
So the key here is good engineering leadership to recognize when that point arrives, and push the company to start the transition.
And indeed, microservices solve a organization problem not an engineering problem. When I taught the architecture to new hires, I always say: a service is the largest piece of system that stays together in a reorg :)
And Service Oriented Architecture is the nice middle ground of that infrastructure axis
The history of distributed software is littered with the corpses of attempts to make the RPC look like a function/method call (I worked for a CORBA vendor decades ago). But these two techniques are so different on a fundamental level they are not substitutable except in the most trivial cases. The compute and elapsed time RPC overhead which makes perfectly good local abstractions completely impractical across a network. And then there are the differences in terms of failure modes, concurrency and synchronicity.
So even a beautifully designed and layered piece of “monolithic” software with a code base costing of coherent and clean abstractions will not be easy to port to a microservices/distributed architecture.
It was a nightmare at that point. We pretty much gave up.
Thing is we were in an illiquid market that didn’t require the kind of scale he envisioned.
Long story short we burnt a hell of a lot of runway building something that was painful to work with compared to the monolith. It did not end well.
Micro services are something that sounds good to the inexperienced but are almost never right for an immature business looking for market fit.
If you really know you can’t scale with just a big box from the outset use something like Elixir or Erlang. Otherwise stick to a modular monolith for as long as you can.
Everything was built/deployed in a single release (unless there was a hot patch, emergency bug fix, in which case we "could" work around it if needed.)
For example, in microservices if you want some data that another service owns you have to define what it is, write an API, and handle all the fun of network problems. But once it's done you have a nice contract for getting that data.
In a monolith you can just reach over and take what you want. If you know there's a function for getting something you can use it. If you know the instantiated db connection has permission to view a row, just query the db directly. If you want to pipe some data somewhere just add it to the session object and it magically appears where you need it. And so on. You can go so fast! But then someone else does the same thing, and over time your monolith gets slower and slower, and needs more memory, and you find yourself having things on a god object that really shouldn't be there but it's hard to change because the behavior is threaded through everything.
Both of these problems are relatively simpler architectural issues, but it's always preferable to have well-defined complexity over accidental complexity. If you can define how code goes into a monolith and stick with those rules then a monolith is great. Most people can't, and I've never seen a company with multiple teams manage it.
Works out for many people and usually ideal for beginners. But post a couple of years, if validation is still your primary model, your model tells you how clueless you are in your domain.
Make logical derivations. Build. Determinism is a luxury only affordable for the ones who put in the effort. Others are doomed to chase validation for eternity.
The so-called pattern and antipatten are useless for startup, is just like parenting guides are useless for new parents. The complexity and novel problems are so large in volume that only basic instinct function. And if you are the successful one, you would guide by whatever success brings you, if you are the failed one, well, you can fail and learned that these patterns are useless and rant here like myself.
In the end, don't destroy your health.
It comes down to deceiving or annoying your customers. E.g. making cancellation difficult or confusing, tricking the users into buying yearly subscription by showing them the monthly price of the yearly subscription (explicitly prohibited by Apple in mobile apps btw) and many others which can boost your revenue short-term but do a lot more harm in the long term, or eventually even kill your company.
These sales anti-patterns can work for bigger companies that are long past their growth stage and are now looking for ways to squeeze pennies out of every customer. Early stage or growth stage startups should not copy these practices: growth is a very fragile thing that can be destroyed by negative word of mouth easily.
That entry isn’t published yet, but… this can be a viable tactic as part of a larger strategy. I’ve seen people raise significant money by designing for investors, and it got them to where they wanted to be.
Doubly so if they are mediocre to start with and triple so if they bring with them their legion of yes-men.
The justification was that we had to be prepared for the scale-up phase. The problem was that we never saw that scale in practice, becausee company had to downsize a year later because we had failed to deliver.
Having a good experienced team generally helps in mitigating some of them, especially in tough situations.