goofys VS litestream

The author needs to ask themselves: in this cloud technology stack, is there POSIX involved somewhere lower down, where I can't access it? The answer is, of course, "yes". The sort of cloud storage systems described all run on top of POSIX APIs. They provide convenience (cost efficiency is more debatable) compared to the POSIX alternative, but that's because they exist at an entirely different conceptual layer (hence the presence of POSIX anyway, just buried).

Your point about surfacing a POSIX that's actually there but hidden and thus visible to low-level Amazon employees building the S3 service which makes it invisible to S3 end customers is true but isn't the the point of the article. The author is saying there are motivations for a POSIX-like api visible also the end user.

So your explanation of stack looks like 2 layers: POSIX api <-- AWS S3 built on top of that

Author's essay is actually talking about 3 layers: POSIX <-- AWS S3 <-- POSIX

That's why the blog post has the following links to POSIX-on-top-of-S3-objects :

https://github.com/s3fs-fuse/s3fs-fuse

https://github.com/kahing/goofys

https://www.cuno.io/

How is this different than these other solutions?

https://github.com/kahing/goofys

https://github.com/s3fs-fuse/s3fs-fuse

But now I ask.. why not s3fs? Is it the GPL licensing? Or even goofys that also have Apache2 licensing and seems to hit similar goals (non fully POSIX compliant)? Why build your own?

If your 20TB is in S3, use a staging box with goofys (https://github.com/kahing/goofys) to mount the commercial S3 bucket(s) into a folder, then use s3 sync to copy to your bucket(s) in GovCloud.

So, we just need to change the dataloader function a bit to make this work then. Did you try just mounting S3 using https://github.com/kahing/goofys. In this case, we need not even change the dataloader code. Not sure of the performance though.

We're using goofys as the mounting utility. It's a "high-performance, POSIX-ish Amazon S3 file system written in Go" based on FUSE (file system in user space) technology.

will probably experiment with https://github.com/kahing/goofys and https://litestream.io/ to make services more easily moved between the devices :) Also, will continue working on https://synpse.net/ to make the operations easier.

I have not, but I keep meaning to collate everything I've learned into a set of useful defaults just to remind myself what settings I should be enabling and why.

Regarding Litestream, I learned pretty much all I know from their documentation: https://litestream.io/

This presentation is focused on the use-case of vertically scaling a single server and driving everything through that app server, which is running SQLite embedded within your application process.

This is the sweet-spot for SQLite applications, but there have been explorations and advances to running SQLite across a network of app servers. LiteFS (https://fly.io/docs/litefs/), the sibling to Litestream for backups (https://litestream.io), is aimed at precisely this use-case. Similarly, Turso (https://turso.tech) is a new-ish managed database company for running SQLite in a more traditional client-server distribution.

This post intends to help you setup replication for SQLite using Litestream.

I've been messing around with litestream. It is so cool. And, I either found a bug in the -timestamp switch or don't understand it correctly.

What I want to do is time travel into my sqlite database. I'm trying to do some forensics on why my web service returned the wrong data during a production event. Unfortunately, after the event, someone deleted records from the database and I'm unsure what the data looked like and am having trouble recreating the production issue.

Litestream has this great switch: -timestamp. If you use it (AFAICT) you can time travel into your database and go back to the database state at that moment. However, it does not seem to work as I expect it to:

https://github.com/benbjohnson/litestream/issues/564

I have the entirety of the sqlite database from the production event as well. Is there a way I could cycle through the WAL files and restore the database to the point in time before the records I need were deleted?

Will someone take sqlite and compile it into the browser using WASM so I can drag a sqlite database and WAL files into it and then using a timeline slider see all the states of the database over time? :)

We're using SQLite in production very heavily with millions of databases and fairly high operations throughput.

But we did run into some scariness around trying to use Litestream that put me off it for the time being. Litestream is really cool but it is also very much a cool hack and the risk of database corruption issues feels very real.

The scariness I ran into was related to this issue https://github.com/benbjohnson/litestream/issues/510

Litestream is a library that allows you to easily create backups. You can probably just do analytic queries on the backup data and reduce load on your server.

https://litestream.io/

One possible strategy is to have one directory/file per customer which is one SQLite file. But then as the user logs in, you have to look up first what database they should be connected to.

OR somehow derive it from the user ID/username. Keeping all the customer databases in a single directory/disk and then constantly "lite streaming" to S3.

Because each user is isolated, they'll be writing to their own database. But migrations would be a pain. They will have to be rolled out to each database separately.

One upside is, you can give users the ability to take their data with them, any time. It is just a single file.

[0]. https://litestream.io/

Upstream Kuma uses a local SQLite database to store account data, configuration for services to monitor, notification settings, and more. To make sure that our data is available across redeploys, we will bundle Uptime Kuma with Litestream, a project that implements streaming replication for SQLite databases to a remote object storage provider. Effectively, this allows us to treat the local SQLite database as if it were securely stored in a remote database.