Hacker News Reader

What if runtime performance and developer performance aren’t inversely proportional?

It might just be to a certain degree, we’re not actually getting any business efficiency from creating bloated and slow software?

A lot of things, especially in business IT, are built on top of outdated and misleading assumptions and are leaning on patterns and norms touted as best practices.

We sometimes get trapped in this belief that any form of performance improvement somehow costs us something. What if it’s baggage that we didn’t need in the first place?

I say this having worked in the software business for coming on 15 years: I don't think an organization where business is calling the shots would be capable of building an Internet search engine.

The entire project a fractal of this type of business-inscrutable engineering, and in any organization where engineers aren't calling the shots, that engineering isn't going to get done, and the project is going to be hideously slow and expensive as a result.

In a parallel universe where I had gone the classic startup route and started out using the biggest off-the-shelf pieces I could find, gluing them together with python (instead of building a bespoke index); then thrown VC money at hardware at when it started struggling; even more when it struggled again; I'd be absolutely dumbfounded when it yet again hit a brick wall and my hardware cost is tens of thousands every month (as opposed to $100/mo now).

Since I've instead built the solution from scratch, I've also built a deep understanding of both the domain and the solution, and when I'm faced with scaling problems, they're solvable in software rather than hardware. I can just change how the software works until it does. It's a slower route, but it's also able to take you places where conventional-wisdom-driven-development does not.

Congratulations on your latest steps forward. We empathise. Resourcefulness, the ultimate asset which sparks creativity.

> We sometimes get trapped in this belief that any form of performance improvement somehow costs us something

But it does always cost you something. Developer time isn't free, after all.

If we only cared about performance, we would be handwriting SIMD intrinsics for baremetal applications. But we don't, because it is easily worth a 20% performance penalty to write code in a modern programming language. We're willing to trade 10% performance for a well-tested framework and library ecosystem which greatly reduces development time. Nobody cares how efficient your application is when it never ships.

Even "bloated" and "slow" do not always mean the same thing. Just look at something like database indexes: they take up space (bloated), but make your application faster. Often that's a worthwhile tradeoff, but creating indexes for literally everything isn't a good idea either. It is all about finding the right balance.

I do agree that a lot of user-facing applications have gone way too far, though. Even completely trivial Android apps are 150MB+ binaries these days, and the widespread use of memory-hogging Electron tools is a bit worrying. When your app runs on millions of devices, you should care about resource usage!

> But it does always cost you something. Developer time isn't free, after all.

According to the rest of the comment we seem to largely agree. But this statement is what I want to challenge a bit.

Basically it comes down to this: We're doing plenty of unnecessary stuff all the time, especially in business IT (web applications, CRUD, CRM, CMS, reporting etc.) software.

Your Electron example points to the right direction, but there are also a lot of practices regarding code organization (patterns, paradigms), being too liberal with pulling down dependencies, framework bloat etc.

Simply getting rid of things that we don't need and thinking about performance in very rough terms gets us _both_ better performance and minimal code. I would wager that this isn't a tradeoff as in you describe. We might, especially in the mid-long term, actually gain developer time.

This often means thinking about DB access patterns, indexing and so on as you mentioned. Meaning we think in SQL and lean on the capabilities and heuristics of our DB. What does the DB actually need to do when I do these queries? How can I model the data in a way that gives me just enough flexibility with reasonable performance? Which parts of the system needs to know what? How does the data need to flow through it?

All that stuff we sometimes put on top (ORMs, OO patterns etc.) can get in the way of that. Does it really make us more productive to put these abstractions on top? Do we gain anything from doing these OO incantations?

The article in question is a really good example of removing complexity and drastically increasing performance at the same time.

I have a good example as well.

Our internal image optimization module that we use to generate differently sized images and formats in order to accommodate browser capabilities and screen sizes, was getting noticeably slow, especially for e-commerce related sites and brochures that typically feature a gallery per product/service.

Long story short: It got 50-60x faster simply by removing a convenience layer, writing SQL directly, processing the images in grouped batches and so on. AKA all just low hanging fruit. The end result is also simpler. It took work/time but it didn't need to be that slow in the first place.

And we are our own users too! We have to maintain, extend, test our code. Faster code gives us faster iteration cycles. Fast feedback loops lead to much higher productivity and flow.

The "no free lunch" fallacy is pervasive, but it's quote obviously false. Lots and lots of things are free.

Things normally don't exist in an optimum state where you must necessarily lose one thing to gain another.

> We're willing to trade 10% performance for a well-tested framework and library ecosystem which greatly reduces development time. Nobody cares how efficient your application is when it never ships.

I think this is the sticking point. People assert without any real evidence that whatever framework greatly reduces development time, and if that were the tradeoff, it might make sense. e.g. Rails and Laravel bill themselves this way.

Meanwhile, I've found that a more barebones framework in Scala is more productive to develop with, and also gets at least 100x the performance (e.g. a request rate in the 10s of thousands/second is easy to do on laptop hardware), which also makes it operationally easier since now you don't need a giant cluster.

In my opinion, a lot of "software bloat" we see these days for apps running on user machines comes from a mismatch between the developer machine and the user machine. The developer is often equipped with a high-end workstation as they simply need those resources to do their job, but they end up using the same machine to do basic testing.

Incidentally, I think the reason they need those specs is the same: the people building the dev tools all have top end hardware, and what’s fast enough for them is good enough to ship. I don’t think the people building the dev tools at meta, or apple, or google are seriously considering the use case of a developer working on an old dual core 8 gb machine, but that’s the reality in large parts of the world.

To a certain extent, yes.

On the other hand, development tools simply require a lot of resources: a debug build is always going to be more demanding than a production build, and a full recompilation of something like Firefox is never going to be fast.

I reckon a lot of developers are more than happy to sacrifice 8GB of RAM for near-instant advanced autocomplete and typechecking, but we should keep in mind that it should not become a requirement to do basic development.

Oh, I agree that this is the cause, but no thanks.

I will keep using the heavyweight development tools that run through all of my code discovering problems, analyzing its quality, changing it into more performant code, deducting all kinds of new code to complete my high-level view, and doing all kinds of the modern benefits that use my computer to replace my work.

I can get behind testing the resulting executable on a low-power machine. But not on using it for everything.

So i guess that is the point GP is making. From practical perspective one would just spend 50$ on RAM and forget about it. But you miss opportunity to make something great in terms of algorithm improvements for example. Even if it costs you more.

SO here artificial constraint is that "you cant have more RAM" and so you need to find other more creative solutions.

It also costs everyone else more to run the inefficient code that you produce.

But OP could have more RAM, and the end user doesn't care about how clever the algorithm is. They only care that the service is offline for a week while the developer is having fun implementing their new toy algorithm.

Working on improvements like this makes a lot of sense in academia, when you are running thousands of servers, or when you need so much memory that you can't buy a big enough server. It's a nice backlog item for when there is literally nothing else to do.

I have definitely fallen into this rabbit hole myself. Solving difficult problems with clever solutions is a lot of fun! But my manager - rightfully - chastised me for it because from a business PoV it was essentially a waste of time and money. Fine for a hobby project, not so much when you are trying to run a business.

> Working on improvements like this makes a lot of sense in academia, when you are running thousands of servers, or when you need so much memory that you can't buy a big enough server.

It also makes sense for all desktop and mobile apps, per gnyman’s point on not hitting individual limits. Also for anything that other people will be running, like libraries. Because your thing might perform marvelously in isolation on a beefy dev machine and still run like ass on every user’s somewhat underpowered computer with ten other apps competing for RAM (hello Slack).

See also: “craptop duty”[1]; how the 512K Mac reduced the competitive advantage of MS’s ruthlessly-optimized office apps but the MultiFinder, né Switcher, restored it[2].

[1] https://css-tricks.com/test-your-product-on-a-crappy-laptop/

[2] https://www.folklore.org/StoryView.py?project=Macintosh&stor...

Thanks for the links, interesting story about switcher.

And yes, hearty recommendation on the craptop.

I was discussing with a colleague a while back when he said he had to get one as he was unable to reproduce a problem on his M2 even with the 6x cpu throttling you can do in Chrome. On the old laptop he dug out of storage he managed to reproduce it instantly.

I need to check with him how easily he could fix it, one argument I have to why some optimisation is always good is that it's easier to fix things as you go along vs having to go back and try to make things better. I mean if there is one thing making it slow then it's easy, but I have a feeling it's often a mix of things and at that point you might not be able to replace the slow parts as everything else depends on them.

(I might have actually linked the wrong Switcher story. The one I remembered explained why it existence was strategic for Microsoft, but control over it was not: multitasking made memory optimization matter on a larger machine.)

> over 40 hours of developer time at at least $20

I think maybe you dropped a zero.

I intentionally underestimated the cost to provide a lower bound.

In reality the listed changes once you consider all team members are likely going to run closer to 80-120 hours at $150 / hour - but that only confirms the final conclusion.

Agreed, it's a no-brainer to add some cheap hardware rather than spend two orders of magnitude more to fix the inefficient code.