Trout – relay webhook events and listen to them locally

Hacker News

Today, the apps we build use a LOT of APIs, including Stripe for payments, Clerk for auth, Twilio for messaging and more. But receiving these webhook events to keep our own data synchronized has traditionally been a big hassle. The problem applies to both prod and dev. In prod, we need a reliable way to subscribe to these events and deliver them to their eventual destination. In dev, we need a way to test against these events locally. The existing products in this space include ngrok, HookDeck, Convoy and others. They are all great, but they have some caveats. For one, ngrok doesn't provide stable URLs for webhook development unless you fork over money for a paid plan. For an indie/hobbyist developer just trying to test their app, this can be a non-starter. Meanwhile, HookDeck and Convoy are full-fledged webhook relays which can be complicated to use. Trout is a simpler way to do webhook development. You can create sources and plug them into your external services e.g. Stripe. Then, you can forward these events anywhere. Trout also comes with a CLI you can install and use to listen to events on any source. This makes developing on localhost easy. All feedback is welcome!

Visit product View on Hacker NewsJul 28, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, stripe, grok · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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