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Unlogged – open-source record and replay for Java

Hacker News

Unlogged – open-source record and replay for Java

Hello HN! Parth, and Shardul here. We have been building unlogged.io for the last 21 months. We started as a time travel debugger and pivoted to record and replay with assertions, mocking, and code coverage. You can save the replays in the form of a JSON and commit them to your git. Both Parth and I come from an e-commerce/payments background where production bugs meant heavy financial losses. Big billion days/Black Friday sales meant months of code freezes with low productivity. Before committing the code, we wanted to replay production traffic and know the breaking changes right away, like in sub-second. Kind of like unit+integration tests on steroids. So, we built an SDK that adds probes to the code in compile time. The SDK logs code execution, in detail. Git: https://github.com/unloggedio/unlogged-sdk We also built an IDE plugin that keeps monitoring code changes, hot reloads these changes, replays the relevant methods, and alerts on failing replays. It also lets developers call Java methods directly, mock downstream methods in run time, highlight code coverage in real-time, and show performance numbers for methods with inlay hints. (right above each method) Git: https://github.com/unloggedio/intellij-java-plugin We are excited to launch the first version of our product that replays with assertions + mocking + code coverage reports right inside the IDE. Link to our IntelliJ plugin: https://plugins.jetbrains.com/plugin/18529-unlogged/ Record and Replay Demo: https://www.youtube.com/watch?v=muCyE-doEB0 Define Assertions on Replay: https://www.youtube.com/watch?v=YKsi1p634-M Track Code Coverage: https://www.youtube.com/watch?v=NMmp954kfaU Generate JUnit Test Cases: https://www.youtube.com/watch?v=rTUmg5b1Z_Q Mocking when replaying: https://www.youtube.com/watch?v=O_aqU1u-Kmw Documentation: http://read.unlogged.io/ Roadmap: 1. Create a production logger -So that the performance impact is minimal -out of the box masking PII from production logs -creating meaningful input/return value combinations from production traffic to be replayed locally. 2. Creating a CI test runner that can integrate with CI/CD pipelines. 3. Auto-Replaying API endpoints of only the changed code. 4. Real-time alerts for the performance impact of code changes. 5. Creating a dashboard with reports, email/slack alerts.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
91%91% 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: slack, email, code · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, pipe · Missing: https docs, just released, exist
68%68% 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: month, way · Missing: mobile apps, ios, personal
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% 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
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.

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