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Comment by QUFB | Hacker News Reader

I've seen the cloud agnostic nature of Kuberbetes mentioned in many posts here. This is only true on the surface for a significant number of use cases and deployment models.

Once petabytes of data are out there in your GCP or AWS environment, "portability" will be costly due to extortionistic pricing of egress bandwidth.

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A lot of people think of multi-cloud as some kind of arbitrage where you jump quickly between markets. Running applications in cloud environments is a lot more like leasing property. Once you set up there are costs to moving.

The portability argument boils down to saying you are not boxed in. If things get bad enough you can move. This is a big long-term advantage for businesses because it means you can correct mistakes or adjust to changing business conditions. That's what most people who run companies are really looking for.

It also leads to nullifying the advantages of the cloud. The whole point are the proprietary services they offer, and use those instead of building them yourself. Trying to be „cloud agnostic“ is one of the biggest mistakes one could make.

You're deploying to clusters of x86 machines in the first place because people in the 90s realized they were a little too into the proprietary APIs of their big iron vendors.

I'd argue the whole point is actually the fact that you can lease CPU/Memory/space as you need it, and capacity constraints now become simple cash constraints. You don't need to shell out millions of dollars on a specialist enormous hardware just to be able to use it for an hour.

Lots of big companies that operate extensively in AWS/Azure/GCP don't go anywhere near the managed services they offer, because they end up being a horror show in terms of scalability, functionality and troubleshootability. Depending on your risk appetite, running Kafka on Fargate/EC2 is a lot more attractive than using Kinesis (for example).

At that scale it is probably a better option to look into something like AWS Snowball and ship it on physical drives.

At the petabyte scale there will probably be huge cost savings to using your own private cloud on your own hardware.

With petabytes you should either have a procurement team that gets a great deal or you should look at co-location. At some point, hiring a team of infrastructure experts is the cheap option, esp if you leave hardware management with data center providers.

And it's not mutually exclusive. I've seen companies working very cost efficiently by using dedicated hardware for 99% of the workload and AWS or GCP for any experiments where they wanted to try out new features.

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