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Comment by tonyhb | Hacker News Reader

RE. initial flows and diagnostics, I totally feel your pain. Part of the trouble with these systems is that they're too different from our average SDLC we have every day:

- Write regular code

- Test locally

- Then deploy

This is one of the key aspects we're fixing at https://www.inngest.com — you can write regular TS (or Go, or Elixir) code as a function, create simple workflows, test locally, and have your functions automatically triggered by events.

I still think there's room to go with improving automations here, and it's going to be an interesting few years as things develop.

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Elixir, really? That sounds amazing. So many of these tools are TS or Python only.

https://github.com/darwin67/ex_inngest. We'll officially support this soon — it's written by one of our engineering team.

The SDKs are lightweight, work in any language (we only support a few right now), and you can live-migrate long running functions across languages at any time. Long running state is automatically transferred across those SDKs.

One of our foundational aspects is to make long running state, queues, events really easy, and that means we need to make multi-cloud and multi-lang migrations easy, too.

Transferring state across sdks sound very cool, how do you achieve that?

With all the workflows as code frameworks (like say, Temporal), this is what I imagine to be a shortcoming. With regular services + state in database implementations, you can query the database separately. While with a temporal workflow, you can't cleanly figure out where a particular workflow run is atm since the state is an append only stream of events?

For Elixir, you might be interested in Broadway [1], described in their website as "Build concurrent and multi-stage data ingestion and data processing pipelines with Elixir." It is maintained by Jose Valim's consultancy company, so it should be pretty good. I'm looking forward to using it in a project at work soon.

[1] https://elixir-broadway.org/

Sorry for the loaded question, but can you share examples of companies using inngest in production and roughly what scale? Your product appears to fill the exact gaps in Supabase's current offering.

Yeah, for sure. Individual companies run tens of millions of functions a month across anything as basic as braze-like customer lifecycle emails (https://www.inngest.com/blog/lifecycle-emails-with-resend) to running complex AI workflows at scale.

The basic premise is that you can send Inngest events (for free) then start writing functions hosted in your own API at any time, with local testing, branch deploys, etc.

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