Fastly Pub/Sub

Hacker News

Fastly Pub/Sub

Hi HN! Fastly Pub/Sub makes it easy to send messages in real-time to browsers and other devices, using SSE or MQTT. It is built on top of Fanout, our global connection management & message routing infrastructure, which means it works at mega scale across all of Fastly's 100+ regions (POPs). We hope folks find it to be a compelling alternative to other "real-time pub/sub" SaaS offerings. Also, we are shipping this product in a novel way: as an open source app for Fastly Compute. You can run it on Fastly as-is or fork it if you'd like. It runs serverlessly and there is nothing to manage. It's free to try since all the components it depends on have free tiers/trials, and the app itself has no cost of its own. The costs of using it are simply the costs of Compute & dependencies. There's a demo here: https://pubsub-test.glitch.me/ With the demo you can play around with sending messages between browser windows and with curl. Announcement & setup guide here: https://dev.to/fastly/announcing-the-pubsub-compute-app-35ki Let us know what you think!

Visit product View on Hacker NewsFeb 27, 2025

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2points

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

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

58%58% predicted probability of success on Indie Hackers, 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.

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

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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