Getting a bare metal stack has interesting side effects on how they can plan future projects.
One that's not immediately obvious is to keep on staff experienced infra engineers that bring their expertise for designing future projects.
Another is the option to tackle project in ways that would be to costly if they were still on AWS (e.g. ML training, stuff with long and heavy CPU load).
A possible middle-ground option is to use a cheaper cloud provider like Digital Ocean. You don't need dedicated infrastructure engineers and you still get a lot of the same benefits as AWS, including some API compatibility (Digital Ocean's S3-alike, and many others', support S3's API).
Perhaps there are some good reasons to not choose such a provider once you reach a certain scale, but they now have their own versions of a lot of different AWS services, and they're more than sufficient for my own relatively small scale.
That’s the niche DigitalOcean is trying to carve out. I’ve always loved and preferred their UI/UX to that of AWS or Azure. No experience with the CLI but I would guess it’s not any worse than AWS CLI.
M4.xlarge (m4.xlarge, 4cpu, 16gb, no storage) is about $100 per month.
This cpu is 7 years old(slow! and power hungry) and has 36 threads. This means it runs 18 of these instances.
The total revenue so far for one cpu is 100x18x12x7 = $150k
If used as a spot instance it’s 144/month, so about 200k
A standard i9-14700k gen has 32 threads, but it can run 12 of these instances (max 192mem). This CPU will cost you $800. Memory is cheap, so for about 1-2k you’re all set, and have a machine that’s way faster and cheaper.
Basically, buy a bunch of NUCs and you’re saving yourself around $1500 per month per NUC. It pays itself back in 1 month
Cloud hosting is —insane—
Not even touching memory ballooning for mostly idle applications.
Lastly, don’t give me reliability s an argument. These were all ephemeral instances that have no storage, so you’ll have to pay for that slow non-nvme storage platform.
One that's not immediately obvious is to keep on staff experienced infra engineers that bring their expertise for designing future projects.
Another is the option to tackle project in ways that would be to costly if they were still on AWS (e.g. ML training, stuff with long and heavy CPU load).