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UnWebhook – A tool for working with webhooks in teams and staging

Hacker News

UnWebhook – A tool for working with webhooks in teams and staging

I needed to tool that would let me analyze webhook messages, and forward them to my machine, or replay them over and over again. I also needed a way to have a "fallback" delivery of webhooks. If a webhook call comes in and im offline, it sends it to the team shared staging environment. If I'm online working in the staging db, it comes to my machine so I can process it. Some tools work great for analysis but I couldnt find anything for the forwarding/replaying this was a "functional" project created over a weekend. available to play with online, and easy to deploy yourself. give it a try next time you're working with stripe webhooks

Visit productView on Hacker NewsFeb 26, 2024
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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, stripe · Missing: agents, macos, agent
55%55% 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: created · Missing: supports, reddit linkedin, podcasting
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
45%45% 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 · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
38%38% 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
12%12% 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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