Something an older and wiser programmer taught me, is to think of the infrastructure costs as a per-user cost. These numbers look enormous next to my bank balance, but if you save 500k per year to service 1 million users, it's nothing to your bottom line.
Meanwhile there's the opportunity cost of moving. All of the people who put effort into this migration, who could otherwise be building something revenue-generating. I think that's why in many companies cloud costs are a problem, but never enough to make it high up the backlog.
Somehow no one was ever making this argument when companies were spending tens if not hundreds of millions of dollars to move their on prem workflows to the cloud.
At that point it was all “you will save the money because you will need such a smaller ops team”.
But once people actually did make the move and noticed that their ops teams didn’t get any smaller, then we started being gaslit into “well the cloud was never about saving money…it was about <fill in the blank>”.
Thenper user calculation is a terrible one. It essentially justifies any inefficiency as long as it’s not some arbitrary multiple of your user base, but inefficiencies add up.
The correct approach, that you even allude to, is to do a complete cost-benefit analysis. And the costs and benefits should include non dollar factors such as time, risk, control, reputational risk, data being available to 3rd parties, etc.
There’s no reason to divide your cost/benefit analysis by your user base at all. You can simply compare the absolute and total values against other potential initiatives and stack rank them based on their net expected benefit.
If you’re comfortable where you are as a business, and not looking for more than steady revenue growth in your core market, then finding efficiencies is a fine use of time.
I know that mindset is antithetical to the VC “make every chart a hockey stick” culture, which is well-represented here on HN. But actually tons of businesses are run that way.
Tech is seen in this very biased lens because Tech seems to be the only place imo that VC's are genuinely interested in seeing very high growth in.
They want to know that they have bet on the next google and they want to know it fast.
Actually, it is real funny that we are talking about this on a forum which is funded by y-combinator/ a lot of this VC nuance.
I don't know man, if I can be honest or not, but I was thinking for a moment and the whole idea of tech seems to be a lot more overflated man... , as a dev, I was just thinking about the influence of money and I was genuinely just wondering what is the fastest way I can make money and It was probably creating a proprietory product and selling the startup / getting VC fund-ed and not organic growth.
I am still very nuanced though, on one hand, both of these go against my personal philosophy, I myself would "love" to open source (preferably MIT but hey AGPL would also cut the deal like the recent redis...) my product and probably have no 0 VC funding.
But on the other hand, I am not sure, A lot of what I feel like building, is probably immature, its better off hidden. I am using Ai to build a lot of stuff for now, and I am not quite proud of it.
I feel, that as someone who has made very meaningless contributions (I guess?) in my past and while I was writing this comment, I was getting this vague sense of an issue being popped up on whatever software I create with "WHY DOESN'T IT WORK" and no issues or nothing.... I don't know, it makes it less lucrative to open source, quite frankly any product.
Maybe I want an AI which can genuinely resolve such very meaningless issues but I also don't trust AI, what if there are some issues which are actually good and AI filters it wrong.
I don't know man. I was thinking about this yesterday and I just realized that I am not thinking this much, I would do whatever I think in the heat of the moment.
They've talked about this at length in both blog posts and podcasts. The gist is that all the Amazon cloud stuff still took effort, their ops team is essentially the same size and they're actually saving all this money.
Also the AWS cloud engineers are so much more expensive because the AWS learning treadmill runs at a 10x speed compared to the on-prem one.
Our cloud engineers spend so much of their time simply keeping up with all the things they need to keep up with, even for workflows that have been running just fine, for years.
The on-prem engineers also need to be up to date, but the changes are more measured and easier to manage.
More money in the company pocket.
More work for the people who did the migration and now maintaining their own cloud. Then when the people who put this together leave, the rest are stuck with one of a kind cloud.
Maybe a good idea, but if it's only saving money that can only happen 1 time, then people expect the same cost going forward ...
They open sourced the entire deployment apparatus that they built to do all of this - it is simple to use. They'll have no issues maintaining it or finding new people if/when needed.
And, if you bothered reading, there's significant annual savings, into perpetuity. Because aws is a racket.
Building revenue generating things is hard (you have to figure out new things that people will pay for). Writing new features also requires generally different skill sets than operating servers. Running software in a datacenter is a more defined problem with straightforward ROI.
Meanwhile there's the opportunity cost of moving. All of the people who put effort into this migration, who could otherwise be building something revenue-generating. I think that's why in many companies cloud costs are a problem, but never enough to make it high up the backlog.