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New top story on Hacker News: Show HN: Claude Artifacts" but creating real web apps

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Show HN: Claude Artifacts" but creating real web apps
20 by antonoo | 8 comments on Hacker News.
Hey Hacker News! Launching gptengineer.app into beta today. It's like Claude Artifacts, but: - you can edit the code in your fav IDE (two-way github sync) - installs npm packages - automatically picks up build and runtime errors and fixes them - very fast, built with rust The full stack capabilities are built on supabase (prefer to not have to handle auth + user data at this point so this is owned by the user) The seed for this project was an open source experiment, posted about that previously here: https://ift.tt/GtD4vSl Would love feedback if you give it a try!

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Tuesday, August 27, 2024

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Thursday, August 15, 2024

New top story on Hacker News: Show HN: Denormalized – Embeddable Stream Processing in Rust and DataFusion

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Show HN: Denormalized – Embeddable Stream Processing in Rust and DataFusion
20 by ambrood | 4 comments on Hacker News.
tl;dr we built an embeddable stream processing engine in Rust using apache DataFusion, check us out at https://ift.tt/ujmHVvO Hey HN, We’d like to showcase a very early version of our embeddable stream processing engine called Denormalized. The rise of DuckDB has abundantly made it clear that even for many workloads of Terabyte scale, a single node system outshines the distributed query engines of previous generation such as Spark, Snowflake etc in terms of both performance and cost. Now a lot of workloads DuckDB is used for were normally considered to be “big data” in the previous generation, but no more. In the context of streaming especially, this problem is more acute. A streaming system is designed to incrementally process large amounts of data over a period of time. Even on the upper end of scale, productionized use-cases of stream processing are rarely performing compute on more than tens of gigabytes of data at a given time. Even so, the standard stream processing solutions such as Flink involve spinning up a distributed JVM cluster to even compute against the simplest of event streams. To that end, we’re building Denormalized designed to be embeddable in your applications and scale up to hundreds of thousands of events per second with a Flink-like dataflow API. While we currently only support Rust, we have plans for Python and Typescript bindings soon. We’re built atop DataFusion and the Arrow ecosystems and currently support streaming joins as well as windowed aggregations on Kafka topics. Please check out out repo at: https://ift.tt/ujmHVvO We’d love to hear your feedback.

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Wednesday, August 14, 2024

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New top story on Hacker News: Launch HN: Stack Auth (YC S24) – An Open-Source Auth0/Clerk Alternative

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Launch HN: Stack Auth (YC S24) – An Open-Source Auth0/Clerk Alternative
16 by n2d4 | 4 comments on Hacker News.
Hi HN! We're Zai and Konsti, and we're building Stack Auth ( https://stack-auth.com/ ), an open-source managed authentication and authorization platform. Basically, we build your login and signup pages, and everything that comes with that. Our GitHub repo is at https://ift.tt/fNJaOrz , and there’s a zero-budget demo video here: https://www.youtube.com/watch?v=LTkjdPf2E2Q Stack Auth was born out of years of frustration with the incumbents. We wanted to build something that is developer-friendly and open-source at the same time. The dominant player in this space is Auth0, who appeals to enterprises but lags behind in developer-friendliness and has strong vendor lock-in. A newer one is Clerk, which markets directly to devs, but is still entirely proprietary. Open-source solutions like Supabase Auth or Auth.js/NextAuth are only authN, and don't provide the rest of the toolchain. On the other hand, building your own auth infrastructure is tedious work. Rolling your own crypto is already hard enough, but on top you'll have to deal with OAuth flows, access tokens, RBAC, permission syncing, API keys, and so on. Most handcrafted OAuth or password-based applications in the wild are vulnerable in at least some of these areas. To us, the solution to this was obvious, so we decided to build it. Stack Auth is 100% open-source, licensed under MIT and AGPL. You can self-host, or choose to use our managed hosting. If you choose the latter, there's no lockin. You can export all your data and/or start self-hosting at any time. Also, we're more than just authentication — we have authorization (orgs, teams, permissions, RBAC) and user management (impersonation, user dashboard, webhooks). One interesting feature is what we call "connected accounts": we can manage and refresh your OAuth access tokens even for services that your users don't use for sign in, such as when accessing GMail or OneDrive APIs. We also have a bunch of components for sign in, password reset, and organizations. For now, we only support Next.js frontends and backends in any language with our API, though our REST API docs ( https://ift.tt/NcT7jDv ) also contain the client endpoints, and some contributors have been building frontends for other languages. For more info, check out our GitHub repo above, or our documentation ( https://ift.tt/FWGmva8 ). Would love to hear about your own stories and opinions on auth. Also really curious to hear from anyone who's using one of our competitors and what aspects it would take for you to switch. Thanks all!

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Wednesday, August 7, 2024

New top story on Hacker News: Ask HN: How different is AWS/GCP/Azure in everyday work

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Ask HN: How different is AWS/GCP/Azure in everyday work
19 by michal_kluczek | 13 comments on Hacker News.
I've almost exclusively been working with GCP for years, with very few occasions when I've created some resources in AWS (I'm managing infra using terraform). When looking a job now, it's very common that I'm rejected before TI because I wasn't working with AWS. Is it really so fundamentally different from GCP or any other cloud provider for that matter? I have a wild feeling that 80-90% of the products all cloud providers offer are same toys but with different names and integrations mechanisms. There are surely some quirks that are exclusive for a specific cloud provider, but is it really that many to stifle your performance?

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