Kudos to the Vite maintainers!
It all slowly adds up where you think a simple $10 VPS with 2 gigs of ram is enough but it's not, especially if you want a team of 10-30ish to work sporadically within the same box.
There can be a lot of major wins by rewriting these programs in more efficient languages like Go or Rust. It would make self hosting more maintainable and break away from the consulting class that often has worse solutions at way higher prices (for an example, one consulting group sells software similar to postiz but for $2k/month).
Why do you expect to be able to replace a 2k/month solution with a $10/month VPS?
In the age of cheap custom software solutions everyone should at least try to make something themselves that's fit for purpose. It doesn't take much to be a dangerous professional these days, and certainly more than ever before can a dangerous professional be truly dangerous.
2 gigs of ram should be considered overkill to cover every single business case for a variety of tools (analytics, mailer/newsletter, CRM, socials, e-commerce).
He's saying that the software seems free, but is so inefficient that it bloats other costs to run it. And he never said he wanted to replace $2K/month with $10/month.
Software can be drastically way less resource intensive, there is no excuse outside of wanting to exacerbate the climate crises.
This period of our history in the profession will be seen as a tremendous waste of resources and effort.
Go write the software yourself, no one owes you anything.
Maybe if you had to actually write it yourself, you'd quickly figure out why people prefer "inefficient" languages for these things.
A cron job scheduler does not in fact require 500 MB of memory. You're just being disingenous, that software is doing a lot more than just that.
People prefer JS because all they know is JS, it's that simple. Please tell me why you think devs choose JS, I'm legitimately curious but your attitude of constant dismissal and disparagement makes it seem you just want to beat people down and not engage.
It's just garbage software, I brought it up as an example IDK why. Commentators here like knowing snippets about other industries in the profession, I know I do at least.
But to answer your Q, yes I do expect a cron job schedule, analytics, and a CRM not to require 8 gig of ram in order to not barf on itself too hard.
These things are incredibly resource intensive for their actual jobs. The software is incredibly wasteful.
A $5/vps should be enough to host every suite of software a small business needs. To think otherwise is extremely out of touch. We're talking about 3 concurrent users max here, software should not be buckling under such a light load.
Where is this weird expectation coming from?
Why should that be the case?
These things aren't complicated, but when you choose NodeJS/Javascript they become way more complicated than expected. I say this as someone who has ever worked professionally with JS and nothing else for a 15 year long career.
Writing software that can only be used by the affluent is not the direction I want our industry to go in.
For a server built in the cloud those cycles could actually be taken up by other things, freeing the system and bringing costs down.
For a client computer running electron, as long as the user doesn't have so many electro apps open that their computer slows down noticeably, that inefficency might not matter that much.
Another aspect is that the devices get cheaper and faster so today's slow electron app might run fine on a system that is a few years away, and that capacity was never going to be taken up by anything else on the end user's device.
- Every Electron app ships with its own copy of Chromium (for rendering the UI) and Node.js (for system APIs). So even simple apps start with a fairly large memory footprint. It also means that electron essentially ships 2 instances of v8 engine (JIT-compiler used in Chromium and NodeJS), which just goes to show how bloated it is.
- Electron renders the UI using HTML, CSS, and JavaScript. That means the app needs a DOM tree, CSS layout engine, and the browser rendering pipeline. Native frameworks use OS widgets, which are usually lighter and use less memory.
- Lastly the problem is the modern web dev ecosystem itself; it is not just Electron that prioritises developer experience over everything else. UI frameworks like React or Vue use things like a Virtual DOM to track UI changes. This helps developers build complex UIs faster, but it adds extra memory and runtime overhead compared to simpler approaches. And obviously don't get me started on npm and node_modules.
at least 100x slower than it needs to be?
I feel the same way about tools like ESLint and Prettier as well after discovering Oxc https://oxc.rs/
All it has to do is put price pressure on your salary. (And it is already doing that.)
Compare this to essentially any modern business app, the product being sold has very little relationship with CPU cycles, or the CPU cycles are SO cheap relative to what you're getting paid, no one cares to optimize.
With Kotlin/Spring Boot, compilation is annoyingly slow. That's what you get with modern languages and rich syntax. Apparently the Rust compiler isn't a speed daemon either. But tests are something that's under your control. Unit tests should be done in seconds/milliseconds. Integration tests are where you can make huge gains if you are a bit smart.
Most integration tests are not thread safe and make assumptions about running against an empty database. Which if you think about it, is exactly how no user except your first user will ever use your system.
The fix for this is 1) allow no cleanup between tests 2) randomize data so there are no test collisions between tests and 3) use multiple threads/processes to run your tests to 1 database that is provisioned before the tests and deleted after all tests.
I have a fast mac book pro that runs our hundreds of spring integration tests (proper end to end API tests with redis, db, elasticsearch and no fakes/stubs) in under 40 seconds. It kind of doubles as a robustness and performance test. It's fast enough that I have codex just trigger that on principle after every change it makes.
There's a bit more to it of course (e.g. polling rather than sleeping for assertions, using timeouts on things that are eventually happening, etc.). But once you have set this up once, you'll never want to deal with sequentially running integration tests again. Having to run those over and over again just sucks the joy out of life.
And with agentic coding tools having fast feedback loops is more critical than ever.
For anyone that doesn't know: With sqlite you can serialize the db to a buffer and create a "new" db from that buffer with just `new Datebase()`. Just run the migrations once on test initialization, serialize that migrated db and reuse it instantly for each test for amazing test isolation.
This method is actually super popular in the PHP world, but people get themselves into trouble if they tidy up all the footguns that stock sqlite leaves behind for you (strict types being a big one).
Also, when you get a certain size of database, certain operations can become hideously slow (and that can change depending on the engine as well) but if you're running a totally different database for your test suite, it's one more thing that is different.
I do recognize that these are niche problems for healthy companies that can afford to solve them, so ymmv.
Once you've created a zfs snapshot, everything else is basically instant and costs very little perf.
Yea, cypress has this in their anti-patterns:
https://docs.cypress.io/app/core-concepts/best-practices#Usi...
Dangling state is useful for debugging when the test fails, you don't want to clean that up.
This has been super useful practice in my experience. I really like to be able to run tests regardless of my application state. It's faster and over time it helps you hit and fixup various issues that you only encounter after you fill the database with enough data.
This is because the kotlin compiler is not written in the way people write fast compilers. It has almost no backend to speak of (if you are targeting the jvm), and yet it can be slower at compilation than gcc and clang when optimizing.
Modern fast compilers follow a sort of emerging pattern where AST nodes are identified by integers, and stored in a standard traversal order in a flat array. This makes extremely efficient use of cache when performing repeated operations on the AST. The Carbon, Zig, and Jai compiler frontends are all written this way. The kotlin compiler is written in a more object oriented and functional style that involves a lot more pointer chasing and far less data-dense structures.
Then, if run on a non-graal environment, you also have to pay for the interpreter and JIT warmup, which for short-lived tasks represents nontrivial overhead.
But unlike header inclusion or templates, which are language level features that have major effects on compilation time, I don't think kotlin the language is inherently slow to compile.