workers-rs VS litestream

- The speed of the Python interpreter running in WebAssembly

Today, Python cold starts are slower than cold starts for a JavaScript Worker of equivalent size. A basic "Hello World" Worker written in JavaScript has a near zero cold start time, while a Python Worker has a cold start under 1 second.

That's because we still need to load Pyodide into your Worker on-demand when a request comes in. The blog post describes what we're working on to reduce this — making Pyodide already available upfront.

Once a Python Worker has gone through a cold start though, the differences are more on the margins — maybe a handful milliseconds, depending on what happens during the request.

- There is a slight cost (think — microseconds not milliseconds) to crossing the "bridge" between JavaScript and WebAssembly — for example, by performing I/O or async operations. This difference tends to be minimal — generally something measured in microseconds not milliseconds. People with performance sensitive Workers already write them in Rust https://github.com/cloudflare/workers-rs, which also relies on bridging between JavaScript and WebAssembly.

- The Python interpreter that Pyodide provides, that runs in WebAssembly, isn't as fast as the years and years of optimization that have gone into making JavaScript fast in V8. But it's still relatively early days for Pyodide, compared to the JS engine in V8 — there are parts of its code where we think there are big perf gains to be had. We're looking forward to upstreaming performance improvements, and there are WebAssembly proposals that help here too.

Not yet, but we're working on that https://github.com/cloudflare/workers-rs/pull/324

I'm also in the Workers org but I have had a bit of interaction with Rust. There's some Rust in the Workers runtime using lol-html for HTMLRewriter as well as some tooling and there's the full blown workers-rs framework that I work on, but that's about it for the Rust I work on regularly.

I'm an engineer at Cloudflare working on Workers (and a maintainer of workers-rs) and I'd love to help whoever ends up maintaining this get that PR rewriting it in Rust across the line.

GitHub - cloudflare/workers-rs: Write Cloudflare Workers in 100% Rust via WebAssembly

I never said it was, but thankfully nowadays there are plenty of other tools that are fast enough to keep the dev cycle quick. Personally esbuild is my go-to when I need a bundler but I've grown really fond of SWC native api, we used to use it at work for our wasm build tool for our workers-rs framework.

There's actually a rust framework for Workers https://github.com/cloudflare/workers-rs

I'm a maintainer of the of the Cloudflare workers-rs project to allow you to write serverless functions in Rust running as WASM in our V8-based runtime. There's certainly some rough spots (doesn't have complete parity with our default JS runtime apis), but if you're concerned with cold start times and you don't need a full containerized environment I think it's a solid choice.

Most likely, it should, we just haven't had the time to fully implement it or add a library to wrap the FFI. Please let us know you need a feature by opening an issue.

I may be biased, as the original project author, but I’d recommend using Cloudflare Workers https://github.com/cloudflare/workers-rs - totally free their with very generous limits.

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.