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Rantenki

I have a personal dev cloud on AWS that has:

* AWS MSK (Kafka server) with redundant instances across 3 AZs

* Aurora Posgres instance with redundancy across 3 AZs

* Multiple Lambdas for incoming messages from MQTT to Kafka

* IoT/MQTT and about a dozen iot devices sending telemetry continuously (every second)

* 20+ services with nearly 40 tasks, running on ECS

* All the supporting route53, certificates, VPCs etc. for the above

* A bunch of miscellaneous stuff I've forgotten that's used by other developers.

* All deployed via TF

_THAT_ all costs well under a grand. You're doing it wrong.

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I think that's unfair. Your setup involving more distinct services than his has little bearing on the amount of data you're working with. Our setup is a lot simpler than yours (no postgres, lambda, mqtt) but deals with presumably a lot more data (~800Gib daily) so it costs an order of magnitude more than yours.

Absolutely. My setup is, as stated, a dev instance. We have a substantially larger prod setup, but I can't get into the details about production scale on a public forum. That said, even the dev instance is moving a substantial amount of data; nothing like 800GB/day, but within an order of magnitude.

And yes, bandwidth costs can be brutal, especially if you try to build a hybrid solution that uses heavy services that live outside of AWS.

That said, the above comment didn't get into enough detail to get an accurate read on their bandwidth or CPU/Memory/Storage utilization, but if they can run it in a lab for $5/mo (which I doubt, since that barely covers power), then it can't be much, so I think it's fair to assume it's at least back-of-the-napkin similar scale.

Most all of those services are pay for use. Which means listing out the services you use means nothing. The price would be based on your level of usage. I have a bunch of lambdas setup in AWS and it's basically free because at the moment, I'm not running them.

Our ECS containers all run continuously processing Kafka messages. Dev has variable throughput, but it's hundreds of messages per second at least. The containers all use between 256MB and 2048MB commits (they're stream processors, so they don't hammer the memory like a stateful monolithic service would).

My point was just that it doesn't have to cost over $1k on Amazon to run a combination of services which apparently CAN run in a private lab for $5/mo, however that is calculated. I can't run my full stack even without load (due to memory commit) on my 32GB, 3 year old Xeon workstation, and that would cost a lot more than $5/mo at any provider I am aware of.

Although he doesn't mention API Gateway in his list, I used to design AWS solutions for people, and it was by far the biggest mistake I saw them make cost-wise: It can get scary-expensive in a hurry, especially if you aren't careful at your cloud architecture and really understand what all you'll be paying for.

Difference is probably that you run real microservices that have small footprint and you can binpack them on very small instances together with very very small aurora cluster.

If you wrote exactly the numbers of instances and types -> we could have a real comparison then.

Which is most likely the case 99% of times people decry a technology on HN

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