Log Analyzer

This tool ingests log data from common web and application servers and produces actionable metrics that aid in identifying operational issues. It formalizes a reproducible workflow for parsing, filtering, and aggregating large log datasets into concise summaries. The approach is format aware yet resilient to variations in log structures, adapting to Apache, Nginx, or JSON formats, and it can be integrated into CI pipelines or used as a standalone analysis step. By highlighting traffic shifts, error spikes, and latency distribution, it helps engineers prioritize fixes and optimize capacity planning. Core outputs include request counts, error rates, top endpoints, and latency percentiles, which support performance tuning and incident review. Unique value lies in its balance of auto detection with configurable filters, allowing rapid analysis of diverse log sources without specialized SIEM tooling. Use cases span post-incident analysis, daily monitoring, and quarterly capacity planning, where teams need repeatable, exportable results that fit into existing data workflows. Core features cover ingestion, automatic format detection, field extraction, time window alignment, aggregation, and export in CSV or JSON. Advanced options include custom parsers and cross-log correlation for multi-source analysis. The tool emphasizes speed and clarity, delivering machine readable outputs suitable for downstream analytics.