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Cptn.io – open-source integration platform

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Cptn.io – open-source integration platform

Hi, I am Krishna Thota. I am building an open source integration and data platform( https://cptn.io ). The product is MIT licensed and the repo is at https://github.com/cptn-io/el-cptn . I have started on my startup journey an year ago and launched a monitoring platform called DevRaven. Unfortunately the product did not takeoff as expected. That story is for another day. But during the course of building the product, I have built several integrations leveraging MQs and Cloud Functions. While building and deploying Cloud Functions for happy paths is easy, I had to monitor logs for failures, build retry mechanisms or manually process failed events, keep instances running to prevent cold start timeouts. It can also get expensive with charges for MQs, server time for running cloud functions etc and costs can be unpredictable. I thought of building a platform where I can build integrations quickly, have the ability to look at incoming/outgoing events, look at logs, retry any failed events etc. And finally, predictable costs for running the infrastructure. cptn.io provides all these capabilities and more. You can build pipelines to integrate with any cloud services, send data from your backend to data warehouses, listen to web hook events etc. The platform can be integrated into any stack by sending events to HTTP end points. Instead of trying to build a business first or launch an open source product under restrictive licenses, the platform will be available under MIT license so any user or customer can use it. There is no ee folder or complex dual licensing and I am also committing to releasing SSO under MIT. The plan is to offer a managed service in the cloud at a later time, accept sponsors for prioritizing features for enterprise customers and charge for enterprise support. It should take less than 5 minutes to get the platform running on your machine. Welcome any feedback, feature requests, PRs and bug reports.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
92%92% 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: mac, user, open · Missing: agents, macos, agent
91%91% 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, pipe · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
37%37% 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
18%18% 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.

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