Logdy v0.14 – Semantic log filtering now available

Hacker News

With the latest release Logdy has landed 2 significant features (among others). Semantic filtering - It uses Breser ( https://breser.dev - simple expression syntax for filtering structured data) to filter through logs. Timeframe picker - Allows you to limit log entries by time. What is Logdy? Logdy is a web-based platform designed to help developers monitor, track, and analyze application logs in real-time locally. Logdy is a single-binary that you add to your PATH so it's available just like any other tool: grep, awk, sed, jq. No installations, no deployments, no compilations. It works locally, so it's also secure.

Visit product View on Hacker NewsDec 14, 2024

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

70%70% 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.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

51%51% 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 · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

9%9% 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.

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