[grandrew]

Things are not quite that simple. You can't say "because my Go app serves a single request under no load in 50us, it will serve 20'000 per core under 100% load" you'd be surprised it will not.

Modern machines are like a networked cluster themselves. You need to do a ton of work to tune both kernel and "hardware" parameters to identify bottlenecks with near-non-existing debugging tools.

There is one truth here: we used to get more performance by scaling "horizontally". Maybe it's time to "scale within"?

[benbjohnson]

That's a fair point. I've updated the post to read, "That translates to thousands of requests per second per core" instead of saying it's linear scaling. Thanks for the feedback!

[lrossi]

That’s nice. But I didn’t really take it literally.

Do you have some benchmark results by any chance? Although it’s a bit of a can of worms, and I would understand if you didn’t want to get into it at this time.

[benbjohnson]

I've only done some light benchmarking so far. I had it running on a two-core DigitalOcean machine with sustained write load to test for race bugs and it was replicating 1K+ writes per second. But honestly I haven't even tried optimizing the code yet. I'm mainly focused on correctness right now. I would bet it could get a lot faster.

https://twitter.com/benbjohnson/status/1351590920664313856

[qwantim1]

Sharding is not really scaling for many, and I think despite your good intentions you may be misleading others. I’m glad you like the setup but people flocking to SQLite scares me.