Full Stack Serverless Apps

Hacker News

## tldr You can deploy javascript apps on Cyclic after logging in with GH. Quick starts: < https://docs.cyclic.sh/docs/overview/starters > ## Description At my last job I saw new developers struggle to get experiments and POCs from their local to live in the cloud. As we continue to expand the software development profession, more developers will need this same help. So we built cyclic.sh. Our aim is to empower even the most junior developer with robust infrastructure and deployments that just work. We can build and deploy your code in less time than it took to read this paragraph. ## What works now - Zero-config build, deploy and hosting of javascript apps - Github integration supporting 'push to deploy' - Branch based builds - Auto-scaling Serverless backend - Custom sub-domains and custom domains - Token based authentication - Integrated single-table DB on top of AWS DynamoDB (in preview) ## Limits/Constraints < https://docs.cyclic.sh/docs/overview/limits > ## Ask Let us know what you think and what we need to add to make it so awesome you would start using it for all your projects. Built with joy by: - Mike < https://github.com/korostelevm > - Kam < https://github.com/seekayel >

Visit product View on Hacker NewsApr 7, 2022

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

85%85% 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: para · Missing: supports, reddit linkedin, podcasting

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

Hacker NewsStrong engagement from HN community · Strong signals: 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.

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

31%31% 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

24%24% 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

17%17% 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.

Incorrect prediction on native model

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