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Being a CTO in a startup is much more than the technical side.
However, the technical decisions you make early with software, especially in a timed-constraint environment like a startup, tend to stick with you for the rest of the project.
In this article, I will be listing a few of the technical decisions I made.
Some of them felt right at all time, some of them I hope not to make again.
Our project was a SaaS management application. We wanted our users to have a great experience, to distinguish ourselves from the competition, and improve their productivity.
We used Kotlin and Spring Boot on the backend, React and Typescript on the frontend.
I’m really comfortable with those technologies and that’s why I chose them.
Even if you’re only using parts of our stack, I believe that some of the things I learned will be useful to you.
It felt right (would do again in my next project)
Kotlin is a fantastic language. It takes inspirations from scala, groovy, ruby, keeps the best parts, and has a top notch IDE support.
There were a few rough edges at the start of the project (IDE performance regressions, erratic behavior on language updates) but for the past few months I can say without reserve that Kotlin has been nothing but a joy to work with.
Kotlin is Java, had it been designed in the past few years instead of having 20 years of legacy. Kotlin is Scala, had it been designed to be a productivity powerhouse instead of an academic language.
It is pragmatic, elegant, and with very few footguns. It would be really painful for me to start a new project with Java instead of Kotlin.
Postgres is an awesome database. Don’t listen to the bells and whistle of NoSQL. I’m completely sure that 90% of the web applications built in 2018 will not require advanced partitioning and clustering and will fit nicely in a relational database.
If you’re building a social network, it’s different of course, but otherwise, just take the best relational database. Your team will probably be at-ease with SQL and you will have the peace of mind of a database schema.
JOOQ and Flyway
JooQ is a java library which allows you to write type-safe SQL queries in Java.
Flyway is a very simple tool that handles your database migrations using simple SQL files (there is a bit more to it, but the concepts are very easy to grasp).
Both are very well designed and it felt liberating to be in control of the SQL of the application. I came to realize how powerful SQL really is. All of a sudden it was a world with window functions, views, schemas, users, and more, that was open to us.
I feel like I was never really in control of my schema when using JPA or other ORM tools in the past.
Typescript and React
For most of my career, I’ve worked with type-safe languages. I am 100% certain that they make me more productive. I can refactor my code and I have tremendous tools that empower me.
I will never start a new project without typescript or flow. My heart tells me typescript is the right tool for me, but choosing any of the type-safe languages that compile to JS will make you more productive.
The only downside with typescript is finding type definitions for some libraries. There are not always of the best quality and you might have to copy, paste, and modify some locally to get the job done.
I tend to have a bias towards libraries written in typescript: they come with type definitions and often have a better design.
React is a good library. I feel at ease with its API surface and I found that teaching React to newer developers is never too much of a burden.
Using a PaaS
Don’t waste time setting up docker containers and a Kubernetes cluster. You just started your project, it does not have to handle billions of requests. You just need to publish your project in one command without headaches.
We used Pivotal Cloud Foundry and we would type
cf push theApplication.jar and be done
with our deployment.
A good old monolith is all you want for the exact same reasons as the above.
Always strive for simplicity. You can create services later on when your startup is widely successful.
Martin Fowler wrote a wonderful article called Monolith First that I encourage you to read.
Not using webpack
I have a lot of respect for the folks maintaining webpack. It is a good tool with unprecedented possibilities. That being said, when I set up the project, and despite my two years of webpack experience, I always felt like I was struggling with legacy software, and weird edge cases. I had to use or write custom plugins just to overcome the shortcomings of the tool.
Webpack is getting better day after day but, for the sake of the project, I took a look at the competition.
For my JS build, I don’t want fancy configuration and a ton of plugins. I want something like spring-boot, with good defaults, and I want it to be fast out-of-the-box.
We used fuse-box, a very good bundler with an efficient cache. It is written in typescript and readily supports this language. Two decisive reasons for me.
I never regretted trusting the fuse-box team, they’re doing a awesome job and they really listen to their community.
The other tool I am following closely is parcel. It auto-detects the features you need and provide an all-around pleasurable developer experience with no configuration. And it’s faster than Webpack.
Parcel is still in its infancy and I expect a few rough edges in the next months but I would probably give it a shot for my next project.
It felt weird (would probably not do again)
Mobx and mobx-state-tree
I love mobx. That’s why I’m a reluctant to list it in this category.
It feels simple and powerful and it is written in typescript.
Those were compelling reasons for the choice of this library when I started the project.
I have been working with Redux intensively on a past project and I found it required a lot of design and tools (boilerplate) to get the simplest features working.
On the other side of the spectrum, we have Mobx. You feel really strong when you design your first stores, because it just works.
On the other hand, edge cases are rough. Some libraries like react-table would just not behave.
After using it for a year, I can probably list a few rules of thumbs:
- Create wrappers using
<Observer />for libraries using
shouldComponentUpdateaggressively, because they will mess up with the expectations of the developers
- Come up with strategies for serialization and deserialization early in the project with libraries like seriliazr.
But all of this has a cost in terms of code and mobx has a somewhat hidden learning curve that makes it difficult to grasp for junior developers.
All in all, choosing a state library for React is hard.
I still do not have the definitive answer to the question of state management in a React application. Remember there are no silver bullets and be careful when you design your frontend architecture early on.
I have an idea of what a good rest API looks like.
I think it involves a lot of design and bikeshedding.
When a developer is in charge of a new feature, they always have a lot of choices to make:
- Should I add attributes to an existing REST resource? (overfetching)
- Should I add a new REST resource? (duplication)
- Should aggregate resources on the backend or the frontend? (inconsistency)
And I did not even talk about HATEOAS or documentation.
Creating a good REST API is definitely something you should strive for and take the time to get right, if your business model requires it.
Otherwise, I would consider GraphQL very seriously.
In our case, our model looked like a tree and not like small separated entities. That’s also something to consider.
I feel that thinking your API in terms of a cluster of objects comes more naturally to developers. It favors emergent design and it encourages your developers and your business to get together and figure out the aggregates in your model.
Not using “strict: true” with typescript
Typescript is awesome, but you have to enable strict null checks to make the most of it. We started the project without strict checks and it was a significant endeavor to change it, so we never had the time to do it.
Every time we got an “X is undefined” error in the frontend, I regretted not adding
strict: true to the typescript
configuration at the start of the project.
It felt wrong (would never do again)
Using an in memory database for tests and development
We used Postgres in production and H2 (an in-memory database) for development and tests.
We had too many errors that we could only see after deploying the product to production.
Fortunately, most of them were easy to fix. The errors we saw the most were differences in ordering and grouping between the two DBMS.
Hence the rule: “every SQL query shall have an ORDER BY clause”.
As Lukas Eder pointed out in the comments: If you don’t need ordering, you should always avoid it, as ordering mostly incurs an O(N log N) operations (apart from those rather rare cases where you can pull the data directly from an index).
You can probably overcome those inconsistencies by setting up a CI build where your tests run against Postgres.
The next time I’m starting a project I will use the same DBMS in development and in production.
I feel that having a little
docker-compose.yml at the root of your project, loose a little time (1 second) at the
start of the day to boot it, and having a slightly worst developer experience is well worth the investment.
At the beginning of the project, I was sure I could take advantage of SSR. I had set up a few projects in JS that leveraged SSR in the past, and studied libraries like nextjs carefully.
On the JVM, it is a bit less common, but I managed to pull something off using J2V8.
Besides, measuring the benefits of SSR is really tricky. You have to consider different metrics than the “time to render”. Take, for example, time to interactive.
It is a fascinating subject but it was foolish to spend time on this matter as SEO and slow processors were clearly not a priority for the business.
Removing Server-Side Rendering was a good call, and reduced the overall complexity of the server code.
That being said, there is room for a tool that would simplify SSR on the JVM. It would be a amazing side project if you’re interested in the challenge.
Not spending enough time on the simplest aspect of the architecture was something I came to regret a few months into the project with multiple people working on the code.
Make sure that every layer has clear boundaries and do not hesitate to split your project in small modules early on.
For example, these modules can be a good starting point:
model: mapping with your database and helpers
services: fetching and updating your database, only exports higher-level functions like Graphql endpoints
web-backend: things that depend on HTTP libraries
web-frontend: JS stuff
Modules are a great way to enforce architectural decisions.
Moreover, you can only use the
in Kotlin by splitting your code into modules.
Later in the project, when you figure out cluster of domain objects that work together well, you should also split the service layer into smaller modules.
Good examples might be the “order module”, the “transaction module”, or the “security module” depending on your domain.
I like to think of this approach as a stepping stone towards “micro-services”, without the complexity of deploying them as separate network entities.
There is actually a continuum between an integrated system and a distributed system and you probably won’t have to cross the line.
For more insights, I recommend watching the Majestic Modular Monoliths talk by Axel Fontaine.
Your time is precious, you don’t want to be spending it unwisely or come to regret too many engineering decisions later.
Only experience can make you aware of the tradeoffs you will make in the early stages of a product. I hope that mine will help you avoid some traps and make better choices when designing a greenfield project.