Event Correlation

LogZilla documentation for Event Correlation

Event Correlation in LogZilla

Event correlation transforms individual log events into meaningful insights by identifying patterns, relationships, and anomalies across multiple events over time. LogZilla provides both simple trigger-based correlation and advanced stateful correlation through SEC (Simple Event Correlator).

Correlation Methods

Stateless Correlation (Triggers)

LogZilla Triggers provide immediate, single-event correlation:

  • Real-time event matching against defined filters
  • Instant action execution when conditions are met
  • Simple alerting and notification scenarios
  • Managed through the web interface or API

Stateful Correlation (SEC)

Simple Event Correlator enables complex, multi-event correlation:

  • Maintains state across events over time
  • Supports event pairs, thresholds, and time windows
  • Handles scenarios requiring memory of past events
  • Processes events through the Script Server architecture

Common Correlation Scenarios

Network Infrastructure

  • Interface flapping: Detect rapid link up/down cycles
  • Device reload monitoring: Correlate planned vs. unplanned restarts
  • Service dependency tracking: Monitor cascading service failures
  • Security incident detection: Identify attack patterns across devices

System Monitoring

  • Threshold-based alerting: Count events within time windows
  • Service availability: Track service start/stop sequences
  • Performance degradation: Correlate resource exhaustion indicators
  • Capacity planning: Identify usage pattern trends

Security Analysis

  • Brute force detection: Count failed login attempts
  • Privilege escalation: Correlate authentication and authorization events
  • Data exfiltration: Monitor unusual file access patterns
  • Audit trail integrity: Detect log tampering attempts

Windows Environment

  • Event ID correlation: Leverage Windows Event ID patterns
  • Security event monitoring: Track critical Windows security events
  • Service monitoring: Correlate Windows service state changes
  • System integrity: Monitor audit log and system file changes

Getting Started

Basic Correlation

  1. Identify patterns: Determine which events need correlation
  2. Choose method: Select triggers for simple cases, SEC for complex scenarios
  3. Create rules: Define correlation logic and actions
  4. Test thoroughly: Verify rules work with sample events
  5. Monitor performance: Ensure correlation processing scales appropriately

Advanced Correlation

  1. Design SEC instances: Organize rules by function or system type
  2. Configure forwarders: Route specific events to appropriate SEC instances
  3. Implement time windows: Define appropriate correlation timeframes
  4. Set up alerting: Configure actions for correlation matches
  5. Monitor and tune: Adjust rules based on operational experience

Architecture Overview

Event correlation in LogZilla follows this processing flow:

  1. Event ingestion: Syslog-ng receives and forwards events
  2. Parsing and enrichment: Events are normalized and tagged
  3. Trigger evaluation: Stateless triggers match individual events
  4. SEC processing: Complex correlation via Script Server and SEC instances
  5. Action execution: Correlated events trigger alerts and responses

Best Practices

Rule Design

  • Start with simple correlation scenarios
  • Use specific patterns to avoid false positives
  • Set appropriate time windows for event relationships
  • Test rules thoroughly before production deployment

Performance Considerations

  • Filter events before sending to SEC instances
  • Use multiple SEC instances for different correlation types
  • Monitor SEC process resource usage
  • Implement correlation rule lifecycle management

Operational Management

  • Document correlation rules and their purposes
  • Implement version control for SEC rule files
  • Monitor correlation effectiveness and tune as needed
  • Plan for correlation rule maintenance and updates

Advanced Capabilities

LogZilla's event correlation extends beyond basic pattern matching to provide enterprise-grade operational intelligence:

Business Process Monitoring

  • Revenue pipeline tracking: Monitor e-commerce workflows end-to-end
  • Service level correlation: Correlate technical metrics with business KPIs
  • Compliance automation: Automate SOX, PCI, and regulatory monitoring

Advanced Security Detection

  • APT correlation: Detect multi-stage advanced persistent threats
  • Lateral movement tracking: Identify sophisticated attack progressions
  • Behavioral analysis: Correlate user and system behavior patterns

Infrastructure Intelligence

  • Cascading failure prediction: Prevent widespread outages through early detection
  • Capacity planning automation: Predict resource exhaustion before impact
  • Multi-cloud correlation: Unified monitoring across cloud providers

DevOps Integration

  • CI/CD pipeline correlation: Track deployment success across environments
  • Performance regression detection: Correlate code changes with performance impact
  • Automated remediation: Trigger corrective actions based on correlation results

Related Topics

Event Correlation | LogZilla Documentation