Parsing and analyzing logs from diverse formats (CSV, XML, YAML, JSON, pattern-based text) using impulse. Covers reader configuration for CSV and pattern logs, mapping columns to semantic fields, timestamp extraction, hierarchical signal organization, severity tagging with regex patterns, multi-source log correlation, wave extraction, state visualization with Gantt diagrams, distribution analysis with pie charts, and applying predefined views across different log files.

Learn how to automatically create log readers using LLM assistance in impulse. Covers using the MCP server tools and /createLogReader prompt to analyze log sources, detect formats, and generate reader configurations for CSV, XML, YAML, JSON, and pattern-based text files. Shows the complete workflow from attaching log content to chat, triggering the LLM prompt, and testing the generated configuration.