Thinking about on how to fit everything on a $5 VPS does not help your business.
I recall running LAMP stacks on something like 128MB about 20 years ago and not really having problems with memory. Most current website backends are not really much more complicated than they were back then if you don't haul in bloat.
I don't know what you value your time or opportunity cost as... but the $10/mo doesn't need to save very many minutes of your time deferring dealing with a resource constraint or add too much reliability to pay off.
If resource limitations end up upsetting one end user, that costs more than $10.
And most VPSs allow increasing memory with a click of a button and a reboot.
if the scalability is in the number of "zero cost" projects to start, then 5 vs 15 is a 3x factor.
$100 is peanuts to most businesses, of course. But even so, I'd rather spend it on fixing an actual bottleneck.
For example: Ticketmaster makes a ton of money and their site is complete dogshit.
That's 17 million hits per day in about 3.9 MiB/sec sustained disk IO, before factoring in the parallelism that almost any bargain bucket NVME drive already offers (allowing you to at least 4x these numbers). But already you're talking about quadrupling the infrastructure spend before serving a single request, which is the entire point of the article.
# ioping -R /dev/sda
--- /dev/sda (block device 38.1 GiB) ioping statistics ---
22.7 k requests completed in 2.96 s, 88.8 MiB read, 7.68 k iops, 30.0 MiB/s
generated 22.7 k requests in 3.00 s, 88.8 MiB, 7.58 k iops, 29.6 MiB/s
min/avg/max/mdev = 72.2 us / 130.2 us / 2.53 ms / 75.6 usThere is a good reason: teaching yourself not to over-engineer, over-provision, or overthink, and instead to focus on generating business value to customers and getting more paying customers. I think it’s what many engineers are keen to overlook behind fun technical details.
This is specious reasoning. You don't prevent anything by adding artificial constraints. To put things in perspective, Hetzner's cheapest vCPU plan comes with 4GB of RAM.
It is specious reasoning. Self-imposing arbitrary constraints don't make you write good, performant code. At most it makes your apps run slower because they will needlessly hit your self-impose arbitrary constraints.
If you put any value on performant code you just write performance-oriented code, regardless of your constraints. It's silly to pile on absurd constraints and expect performance to be an outcome. It's like going to the gym and work out with a hand tied behind your back, and expect this silly constraints to somehow improve the outcome of your workout. Complete nonsense.
And to drive the point home, this whole concern is even more perplexing as you are somehow targeting computational resources that fall below free tiers of some cloud providers. Sheer lunacy.
I think your analogy is flawed; a more apt one would be training with deliberately reduced oxygen levels, which trains your body to perform with fewer resources. Once you lift that constraint, you’ll perform better.
You’re correct that you can write performant code without being required to do so, but in practice, that is a rare trait.
In any case, this is for the OS itself - the webserver, application, database, etc. will all of course require their own. For a well-optimized program with a well-optimized schema, 1 GB is a reasonable lower bound.
The Macbook Neo with 8GB RAM is a showcase of how people underistimated its capabilities due to low amount of RAM before launch, yet after release all the reviewers point to a larger set of capabilities without any issues that people didn't predict pre-launch.
Even their $5 plan gives 4GB.
In my head, I call this the 'doubling algorithm'.
If there's anything that's both relatively cheap and useful, but where "more" (either in quality or quantity) has additional utility, 2x it.
Then 2x it again.
Repeat until either: the price change becomes noticeable or utility stops being gained.
Tl;dr -- saving order-of single dollars is rarely worth the tradeoffs.
> Immediately proposes alternative which is literally 4x the cost.