Hatchet | Full-Stack Engineer | NYC or SF or REMOTE (US and EU) | https://hatchet.run
Hey HN! I'm Alexander, one of the founders of Hatchet. Hatchet is an open-source platform for running background jobs at scale.
We're hiring engineers who are excited to build the next class of engineering primitives, starting with queues, background tasks and durable execution. We started in early 2024 after launching our distributed task queue (https://news.ycombinator.com/item?id=39643136).
Hatchet is currently used by thousands of engineers for all kinds of workloads: log ingestion pipelines, code review agents, video encoding, GPU scheduling, etc. Our target customer is fast-growing startups who have a strong need for background jobs system. These days, that tends to be AI companies, though we're general-purpose and not exclusively targeted for AI workloads.
Applying: email me at alexander@hatchet.run and tell me about something impressive you've built, along with your CV and why you're interested in Hatchet.
Note that we're fully open-source, which you can check out here: https://github.com/hatchet-dev/hatchet (and if you have thoughts / opinions / questions about the codebase, please include those in your note!)
> Our analysis revealed the fork-to-star ratio as the strongest simple heuristic for identifying potential manipulation. The logic is straightforward: a star costs nothing and conveys no commitment. A fork means someone downloaded the code to use or modify it.
This is just clearly...incorrect? You can both modify code without forking it and most software is distributed via a registry or binary download, which also wouldn't be represented in forks. For most projects, the number of forks is a lossy signal for how busy the contributor ecosystem is, nothing else.
Candidly we're still trying to figure that out: all of the plumbing is there in the open source, but the actual implementation of writes to S3 are only on the cloud version. This is partially because we're loath to introduce additional dependencies, and partially because this job requires a decent amount of CPU and memory and would have to run separate from the Hatchet engine, which adds complexity to self-hosted setups. That said, we're aware of multi-TB self-hosted instances, and this would be really useful for them - so it's important that we can get this into the open source.
The payloads are time-partitioned (in either case) so we do drop them after the user-defined retention period.
Author here - I'm also generally skeptical of coding agents, but with the right problem domain and approach they can produce quality output when paired with humans. There was a point in time in the chess world where computer + human was stronger than computer or human alone. I think we're in that era for a handful of applications. Not for things like kernels, browsers, or databases.
> Besides, who is going to maintain that code?
I maintain the code. If Claude gets sunset tomorrow, I'll still be able to maintain and write it - I've already rewritten parts of it.
You could make the same argument for a team member leading a project that you've worked on. Is that code forever required to be maintained by one team member?
Previously the overhead of ensuring code quality when the development process was driven by Claude Code was greater than just writing the code myself. But that was different for this project.
Hi, thanks! To be clear, the demo there is merely a WASM-based Ghostty build which is rendering the TUI on a web page, just so people could try it out without needing to install anything. The actual TUI runs in your terminal. I'm guessing it's the WASM side of things causing the fans to spin, which you wouldn't see locally.
Hi everyone, I enjoyed building this TUI for myself and wanted to write down how I did it. I appreciate all the thoughts and feedback! The web app is our main investment, but I think there's a slice of developers who really like to interact with TUIs, so I'm going to keep working on it.
For the demo at https://tui.hatchet.run, to answer some messages asking about it: I built this with the fantastic ghostty-web project (https://github.com/coder/ghostty-web). It's been a while since I've used WASM for anything and this made it really easy. I deployed the demo across six Fly.io regions (hooray stateless apps) to try to minimize the impact of keystroke latency, but I imagine it's still felt by quite a few people.
You're right - I'll remove that now until we can get it more performant or drop it altogether. This wasn't something we caught during testing. I appreciate the feedback!
If you check the source (not the DOM) the actual content is loaded in `<div hidden="" id="S:0"> ...` which is then moved/copied into the proper main content div in the DOM using a JS event it seems.
I used to try EWW sometimes, but it sometimes made whole Emacs crash at unpredictable times, so I stopped trying to use it. But good to know, maybe I will try again in the future, hoping it becomes more stable/safe.
Drawing the boundary at high throughput, huge fan-out and ultra-low-latency is correct - I'd also add that MQs are often used for pub/sub and signaling.
MQs are heavily optimized for reducing E2E latency between publishers and consumers in a way that DE engines are not, since DE engines usually rely on an ACID compliant database. Under load I've seen an order of magnitude difference in enqueue times (low single-digit milliseconds for the MQ p95 vs 10ms p95 for Postgres commit times). And AMQP has a number of routing features built-in (i.e. different exchange types) that you won't see in DE engines.
Another way to think about it is that message queues usually provide an optional message durability layer alongside signaling and pub/sub. So if you need a very simple queue with retries _and_ you need pub/sub, I'd be eyeing an MQ (or a DE execution engine that supports basic pub/sub, like Hatchet).
Hey HN! I'm Alexander, one of the founders of Hatchet. Hatchet is an open-source platform for running background jobs at scale.
We're hiring engineers who are excited to build the next class of engineering primitives, starting with queues, background tasks and durable execution. We started in early 2024 after launching our distributed task queue (https://news.ycombinator.com/item?id=39643136).
Hatchet is currently used by thousands of engineers for all kinds of workloads: log ingestion pipelines, code review agents, video encoding, GPU scheduling, etc. Our target customer is fast-growing startups who have a strong need for background jobs system. These days, that tends to be AI companies, though we're general-purpose and not exclusively targeted for AI workloads.
Stack: Postgres, Go, Typescript, React, Kubernetes
Applying: email me at alexander@hatchet.run and tell me about something impressive you've built, along with your CV and why you're interested in Hatchet.
Note that we're fully open-source, which you can check out here: https://github.com/hatchet-dev/hatchet (and if you have thoughts / opinions / questions about the codebase, please include those in your note!)
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