EdgeNode – Global Serverless Deployments

Hacker News

Hey HN, we're Sebastian and Mish and we are working on EdgeNode - A global serverless deployment platform. Typically, most applications are hosted in a single location. This makes the experience worse for the users based further away due to high latency. Higher latency leads to decreased conversion rates, impairs user interactions and ultimately reduces customer satisfaction. Amazon and Google operate their services globally to eliminate this issue and increase service reliablity. However, setting up and maintaining such an infrastructure is technically challenging and very costly. With EdgeNode, we want to enable companies to scale globally in a cost-effective and developer-friendly way. EdgeNode runs your existing apps (Next.js, Ruby on Rails, Laravel, Spring, Django) or Docker containers globally on the edge, no modifications required. Your application scales down to zero instances when there are no active requests, so you only pay for the resources you use. We're committed to make global deployments as simple as possible. To achieve that, we will offer a one-click deployment process, eliminating complex configurations and minimizing the time and effort required to get your application up and running on the edge. Please sign up for Early Access and let us know what you think!

Visit product View on Hacker NewsJun 29, 2023

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

88%88% 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: google, apps, user · Missing: mac, agents, macos

88%88% 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, existing, io · Missing: https docs, excited, just released

61%61% 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: platform, host, friendly · Missing: plus, intuitive, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · 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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