Log2fluent – send logs to Fluent over TCP/Unix sockets

Hacker News

log2fluent is a command line tool (written in Go) that sends application logs to a Fluent server (e.g. Fluent Bit, Fluentd) via the Fluent Forward Protocol as structured log data. Adopted from my blog original post "Utilizing Pipes for High Performance Log Management": https://cyral.com/blog/utilizing-pipes-for-high-performance-... It's mostly useful for situations where you don't want to ever write logs to disk and you don't want to update your app's code to send logs directly to Fluent. Check it out at: https://github.com/ccampo133/log2fluent The README has a bunch more information as well as some example usage. Thanks!

Visit product View on Hacker NewsAug 21, 2024

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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.

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

38%38% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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