It

Itsi – all-in-one HTTP server and proxy with first-class Ruby support

Hacker News

Itsi – all-in-one HTTP server and proxy with first-class Ruby support

Hey HN, Meet "Itsi", a high‑performance, all‑in‑one HTTP server and proxy with first-class Ruby support. It's a drop‑in replacement for your current Rack server, built on Hyper and Tokio, ships with batteries‑included middleware, and lets you go from dev to production without any surprises. Itsi is my attempt at eliminating the disparity that commonly exists between production and non-prod environments. A single, efficient process containing everything you need to serve your app, equally at home on a Raspberry Pi or local dev box as it is on your production VPS or Kubernetes cluster. You get a broad set of built-in security and performance features (rate limits, JWT auth, CSP, intrusion-protection, automated certs, compression, ETag support, cache-control, etc.), an ergonomic dev experience with bundled RubyLSP support, zero-downtime config reloads, first-class Ruby gRPC handler support, Fiber-scheduler mode (à la Falcon), and more—all in one minimal library. In addition to native performance on par with top Rust and C servers, Itsi’s big wins come from replacing Ruby middleware and application-level concerns with native equivalents, freeing your Ruby CPU cycles for the logic that actually matters. Itsi is new but well-tested and already powering small production apps. I’d love to hear from eager early adopters who can help kick the tires and battle-test it. Thank you!

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, new, single · Missing: mac, agents, macos
79%79% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps · Missing: mobile apps, ios, personal
34%34% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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