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797 points burnerbob | 1 comments | | HN request time: 0.234s | source
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pritambarhate ◴[] No.36810820[source]
Here the even bigger red flag is that Fly doesn't have a (automated?) way to quickly move workload from a faulty server to a good server. Especially when containers (and orchestrators) have abstracted away the concept of data volumes which can be attached and detached. (Yes, it needs a lot of serious technical investment to provide this and I think it's one of the reasons storage is expensive on the big 3 clouds.) If you are offering data persistence services then you absolutely need this capability.

I think there is an expectation mismatch between what Fly wants to offer and what the market wants from it. Fly wanted to innovate on offering the ability to the devs to be able run their apps from multiple data centers. But without a proper data persistence service, the ability to run apps from multiple data centers is not useful to a vast majority of people.

I think Fly is trying to solve the persistence issue with their SQLite replication, but that means the vast majority of the devs will have to change the way they develop applications to suit Fly platform.

I think Fly needs to choose between what it wants to become. A reliable and affordable Heroku replacement, which is a decent sized market or offer an opinionated way of developing apps which offer best performance to users all around the world.

But opinionated ways of doing things is a double edged sword. (Rails and Spring Boot are highly successful because of their opinionated defaults.) App Engine is an interesting case study in the app hosting domain. It was way ahead of the time and prescribed you a way of developing apps which allowed the apps to scale to very high traffic. But people didn't want to change the way they develop to adapt to it.

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1. linuxftw ◴[] No.36813111[source]
They don't have remote attached storage, it's all local on the node, lvm based volumes. The data persistence is 24hr or manually created lvm snapshots that are exported to s3.

It's really not a place to run persistent workloads. If you run postgres there, you need to be prepared to either hot load your data into a new instance, or restore from backups.