LogAnalyzer was inspired by a recurring frustration I faced across multiple engineering teams — logs exist everywhere, but insights are fragmented, hard to search, and often discovered too late. Developers end up grepping through files, manually correlating timestamps, or jumping between systems like CloudWatch, Kibana, and raw CSV dumps. I wanted a simple, fast, developer-friendly tool that makes logs actually useful, not just stored. The core problem is visibility. Failures happen — pipelines break, jobs stall, processes retry invisibly — but teams often don’t know why until users complain. Traditional log tools are heavyweight, expensive, or too general. LogAnalyzr focuses specifically on: surfacing failure patterns early letting engineers filter, group, and compare logs instantly allowing teams to see what's missing, not just what's logged making logs readable and actionable instead of overwhelming Instead of saying: “We had logs, so we thought we were covered,” Log Analyzer helps teams say: “We understand what happened, why, and how to prevent it.” How did your approach or process evolve while working on this launch? The first version was a simple formatter — just clean, pretty logs. But after sharing prototypes with other engineers, I realized something bigger: the real value was in detecting gaps and anomalies, not just beautifying text. That shifted my focus from formatting → to analysis, aggregation, and insight extraction. I evolved LogAnalyzer to: support large files (MBs → GBs) parse multiple log formats (JSON, CSV, line-based) highlight missing events extract metrics without a data warehouse run locally or in the cloud It grew from a utility tool into a lightweight intelligence layer for logs — helping teams catch issues faster, with less guesswork, and zero vendor lock-in. https://github.com/fhcelik/Log-A...

Log Analyzer

Turn Logs into Actionable Insights

Turn Logs into Actionable Insights