An open-source backend for frontend framework built on Express.js

Hacker News

Hey All! I started a project to create a simple API proxy server that would allow me to use third-party APIs in my frontend apps without exposing my API keys. This solved a common problem I faced: needing to interact with external services securely without building a full backend for every project. As I worked on it, the project evolved into something more comprehensive: a Backend for Frontend (BFF) Framework built on Express.js. This framework now helps you quickly spin up a backend for your client applications, especially useful when you're dealing with APIs you don't fully control. You can configure the BFF using a simple YAML file, and it comes with built-in policies for CORS, JWT validation, and rate limiting. If you need more customization, you can extend its functionality by writing custom Express middleware and handlers. I'd love to get your feedback and hear if this would be useful for your projects!

Visit product View on Hacker NewsJul 13, 2024

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

79%79% 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: started · Missing: supports, reddit linkedin, podcasting

60%60% 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

47%47% 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

40%40% 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

26%26% 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

15%15% 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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