Advanced Features

Unlock Gonzo's most powerful capabilities with AI-driven analysis, sophisticated pattern detection, and intelligent format processing. These features transform Gonzo from a log viewer into an intelligent analysis platform.

What Makes Gonzo Advanced?

Gonzo goes beyond traditional log analysis tools by incorporating cutting-edge technologies:

🤖 AI-Powered Intelligence

Leverage machine learning models to automatically identify patterns, anomalies, and root causes in your logs without manual analysis.

📊 Advanced Pattern Detection

Built-in algorithms automatically discover recurring patterns, cluster similar events, and identify unusual behavior in your log streams.

🔍 Intelligent Format Processing

Automatic detection and parsing of complex log formats with smart field extraction and type inference.

📈 Deep Analytics

Time-series analysis, heatmap visualizations, and statistical insights that reveal trends invisible to traditional log analysis.

Prerequisites: Complete the User Guide section first. Advanced features build on fundamental Gonzo knowledge and assume familiarity with the interface and basic operations.

Feature Overview

AI Integration

Transform log analysis with artificial intelligence

Gonzo integrates with multiple AI providers to bring intelligent analysis to your logs:

• Pattern Recognition - AI identifies recurring issues and anomalies automatically

• Root Cause Analysis - Get intelligent suggestions about what caused problems

• Natural Language Queries - Ask questions about your logs in plain English

• Predictive Insights - Understand trends and potential future issues

• Multi-Provider Support - Works with OpenAI, local models (Ollama, LM Studio), and custom APIs

Key Capabilities:

• Automatic anomaly detection in log patterns

• Intelligent correlation across multiple log sources

• Natural language explanations of complex technical issues

• Proactive identification of potential problems

• Context-aware analysis based on your specific application domain

Time to master: 45-60 minutes Prerequisites: Basic Gonzo proficiency, API key for AI service

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Log Analysis

Deep analytical insights with advanced algorithms

Sophisticated analysis capabilities that reveal hidden patterns and trends:

• Drain3 Pattern Detection - Automatically cluster similar log entries

• Time-Series Analysis - 60-minute rolling window with severity tracking

• Heatmap Visualization - ASCII-based intensity mapping over time

• Service Distribution - Understand which services generate what log types

• Anomaly Detection - Statistical analysis to identify unusual patterns

Advanced Analytics:

• Pattern extraction using state-of-the-art clustering algorithms

• Real-time trend analysis with configurable time windows

• Statistical outlier detection for identifying anomalies

• Cross-correlation analysis between different log sources

• Performance trend identification and prediction

Time to master: 30-45 minutes Prerequisites: Understanding of log patterns, basic statistics helpful

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Format Detection

Intelligent parsing of complex log formats

Advanced format processing that goes beyond simple pattern matching:

• Multi-Format Support - JSON, logfmt, plain text, and custom formats

• Intelligent Type Inference - Automatic detection of data types and structures

• Nested Object Handling - Deep parsing of complex JSON structures

• Custom Format Adaptation - Learn and adapt to your specific log formats

• Real-Time Processing - Format detection that works with streaming data

Smart Processing:

• Automatic field extraction with semantic understanding

• Dynamic schema inference for evolving log formats

• Error-tolerant parsing that handles malformed entries

• Performance-optimized processing for high-volume streams

• Custom transformation rules for legacy formats

Time to master: 20-30 minutes Prerequisites: Basic understanding of log formats

Learning Paths

Choose your path based on your goals and current expertise:

AI-First Path

Focus on intelligent analysis and automation

Perfect for users who want to leverage AI for log analysis:

1. AI Integration Setup - Configure your AI provider

2. AI Providers Guide - Choose the right AI service

3. Using AI Features - Master AI-powered analysis

4. Log Analysis - Combine AI with algorithmic analysis

5. Format Detection - Optimize data input for AI

Benefits:

• Fastest path to intelligent insights

• Automated problem detection

• Natural language interaction with logs

• Reduced time to resolution for issues

Estimated time: 2-3 hours total

Analytics-First Path

Format-First Path

Advanced Feature Combinations

The real power of Gonzo comes from combining these advanced features:

AI-Enhanced Pattern Detection

# 1. Start with automatic pattern detection
gonzo -f complex-app.log --follow

# 2. Enable AI analysis
export OPENAI_API_KEY="your-key"
gonzo -f complex-app.log --follow --ai-model="gpt-4"

# 3. Use Counts panel for pattern analysis
# Press Enter on Counts panel → Review drain3 patterns
# Press 'i' on interesting patterns for AI explanation

# 4. Combine insights
# Algorithmic patterns + AI interpretation = Powerful insights

Multi-Format Intelligent Analysis

# Analyze mixed-format logs with AI
gonzo -f json-logs.log -f plain-text.log -f logfmt.log \
      --follow --ai-model="gpt-4"

# Benefits:
# - Automatic format detection for each log type
# - Unified analysis across different formats  
# - AI correlation of events across formats
# - Pattern detection that spans format boundaries

Real-Time Anomaly Detection

# Advanced real-time monitoring
gonzo -f production.log --follow --ai-model="gpt-4" \
      --update-interval=30s --log-buffer=5000

# Workflow:
# 1. Gonzo detects patterns automatically (drain3)
# 2. Tracks statistical baselines over time  
# 3. AI analyzes deviations from normal patterns
# 4. Alerts you to anomalies worth investigating

Use Case Scenarios

Production Monitoring with AI

Scenario: 24/7 production monitoring with intelligent alerting

# Setup intelligent monitoring
export OPENAI_API_KEY="your-production-key"
gonzo -f /var/log/app/*.log --follow \
      --ai-model="gpt-4" \
      --log-buffer=10000 \
      --update-interval=60s

# AI continuously analyzes:
# - Error rate changes vs historical baselines
# - New error patterns not seen before
# - Performance degradation indicators
# - Security anomaly detection

Development Debugging Enhancement

Scenario: AI-assisted debugging during development

# Enhanced debugging session
gonzo -f logs/debug.log --follow --ai-model="gpt-3.5-turbo"

# Workflow:
# 1. Reproduce issue while Gonzo monitors
# 2. AI identifies unusual patterns during reproduction
# 3. Press 'i' on error logs for AI explanation
# 4. AI suggests debugging steps and root causes
# 5. Faster resolution with intelligent insights

Complex System Analysis

Scenario: Multi-service architecture investigation

# Comprehensive system analysis
gonzo -f api-gateway.log -f user-service.log -f db.log \
      --follow --ai-model="gpt-4"

# Advanced capabilities:
# - Cross-service correlation with AI insights
# - Pattern detection across service boundaries
# - Intelligent trace following through system
# - Root cause analysis spanning multiple services

Performance Considerations

AI Feature Optimization

Managing AI API Costs:

# Use faster models for development
export GONZO_AI_MODEL="gpt-3.5-turbo"

# Use premium models for production issues
export GONZO_AI_MODEL="gpt-4"

# Local AI for cost-free analysis
export OPENAI_API_BASE="http://localhost:11434"  # Ollama
export GONZO_AI_MODEL="llama3"

Balancing Features with Performance:

# High-volume logs - optimize for speed
gonzo -f busy.log --follow \
      --update-interval=10s \
      --log-buffer=20000 \
      --memory-size=50000

# AI analysis - balance frequency vs cost
# Run AI analysis on filtered subsets rather than all logs
gonzo -f app.log --follow | grep ERROR | gonzo --ai-model="gpt-4"

Advanced Analytics Tuning

Pattern Detection Optimization:

# Tune drain3 sensitivity (via configuration)
# More sensitive = more patterns detected
# Less sensitive = broader pattern grouping

# Balance pattern granularity with usefulness
# Too many patterns = noise
# Too few patterns = missed insights

Integration with Existing Workflows

CI/CD Integration

# AI-enhanced CI/CD analysis
build-command 2>&1 | gonzo --ai-model="gpt-3.5-turbo" &
GONZO_PID=$!

# After build completion
if [ $BUILD_FAILED ]; then
    echo "Build failed - check Gonzo AI analysis"
    # AI has been analyzing build logs in real-time
    # Press 'i' on error logs for failure analysis
fi

Monitoring Integration

# Enhanced alerting with AI context
if grep -q "ERROR" /var/log/app.log; then
    # Launch Gonzo with AI for context
    tail -100 /var/log/app.log | gonzo --ai-model="gpt-4" &
    
    # AI provides context for alerts
    echo "Error detected - Gonzo AI analysis running"
fi

Getting Started with Advanced Features

Quick Start Checklist

For AI Integration:

• Choose AI provider (OpenAI, Ollama, LM Studio)

• Configure API keys and endpoints

• Test with simple log analysis

• Explore AI chat and analysis features

For Log Analysis:

• Understand the Counts panel and modal

• Practice with pattern detection

• Learn time-series analysis interpretation

• Experiment with different log types

For Format Detection:

• Test with JSON, logfmt, and plain text logs

• Observe automatic field extraction

• Understanding nested object handling

• Practice with mixed-format scenarios

First Advanced Session

# Complete advanced features test drive
# 1. Set up AI (if available)
export OPENAI_API_KEY="your-key"

# 2. Analyze logs with all features
gonzo -f mixed-format.log --ai-model="gpt-4"

# 3. Explore each advanced feature:
# - Press Enter on Counts panel (advanced analytics)
# - Press 'i' on log entries (AI analysis)  
# - Observe format detection in Attributes panel
# - Try AI chat with 'c' in log details

# 4. Combine features for comprehensive analysis

What's Next?

After mastering Advanced Features, you'll be ready for:

• Configuration - Optimize settings for advanced workflows

• Integration Examples - Apply advanced features to real scenarios

• API & Architecture - Understand how advanced features work

• Contributing - Help improve advanced features

Getting Help with Advanced Features

Community Resources:

• 📖 Advanced feature documentation and examples

• 💬 GitHub Discussions for complex use cases

• 🔧 GitHub Issues for advanced feature bugs

• 🤝 Community examples and patterns

Best Practices:

• Start with one advanced feature at a time

• Practice with sample data before production use

• Understand cost implications of AI features

• Document successful patterns for team sharing

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Ready to unlock Gonzo's full potential? 🚀 Advanced features transform log analysis from manual investigation to intelligent, automated insights. Start with AI Integration to experience the future of log analysis!