Shippable - Continuous Integration service using Docker containers

Hacker News

Hello guys, I am the co-founder of Shippable (www.shippable.com) - a container-based Continuous Integration service. We recently switched from LXC to Docker containers, so please try it out and give us feedback. We plan to launch on Jan 15th. Our UI is still in flux but any feedback is welcome! Shippable is integrated with GitHub and supports Ruby, Node.js, Python, Java, Scala on Ubuntu 12.04. Please try it out at www.shippable.com. Docs are at www.shippable.com/docs. You can reach with me any feedback or questions at manisha@shippable.com Thanks!!

Visit product View on Hacker NewsNov 13, 2013

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

62%62% 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.

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

49%49% predicted probability of success on AppSumo, 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.

Product HuntUnlikely to reach the leaderboard · Strong signals: dock, using · Missing: mac, agents, macos

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

37%37% 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

11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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