OneUptime – Automatically fix your code by running a CI/CD job

Hacker News

ABOUT ONEUPTIME: OneUptime ( https://github.com/oneuptime/oneuptime ) is the open-source alternative to DataDog + StausPage.io + UptimeRobot + Loggly + PagerDuty. It's 100% free and you can self-host it on your VM / server. We collect telemetry data from your software by using OpenTelemetry and then fix your codebase by using OneUptime Copilot. Copilot (currently PoC) is a tool that helps you improve your codebase automatically. Copilot can fix following issues automatically by scanning your codebase for issues and sending PR's automatically: - Performance Issues: Improve database queries, optimize code, reduce memory usage, decrease API response time, etc. - Security Issues: Fix security vulnerabilities, prevent SQL injection, XSS, CSRF, etc. - Code Quality Issues: Improve code readability, maintainability, and scalability. Improve comments, naming conventions, refactor code, etc. - Error Handling Issues: Improve error handling, exception handling, logging, etc. - Testing Issues: Improve test coverage, test quality, test performance, etc. - Documentation Issues: Improve documentation quality, comments, README, etc. You can set this up by using an LLM Model of your choice. Here are the docs to read more: https://oneuptime.com/docs/copilot/introduction This integrates in your GitHub Actions CI/CD pipeline and no code is sent to us. OPEN SOURCE COMMITMENT: OneUptime is open source and free under Apache 2 license and always will be. REQUEST FOR FEEDBACK & FEATURES: This community has been kind to us. Thank you so much for all the feedback you've given us. This has helped make the softrware better. We're looking for more feedback as always. If you do have something in mind, please feel free to comment, talk to us, contribute. All of this goes a long way to make this software better for all of us to use.

Visit product View on Hacker NewsJul 16, 2024

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

96%96% 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 · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% 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 · Strong signals: way · Missing: mobile apps, ios, personal

55%55% 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

41%41% 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

14%14% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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