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Version: v1.1.0
This page documents behavior guaranteed in TealTiger v1.1.0. TealTiger emits two types of operational outputs: audit events for compliance evidence, and logs for debugging and monitoring. Both are structured and redaction-safe by default.

Logs vs Audit Events

Think of them like this:
  • Audit events = Your security camera footage (evidence for compliance)
  • Logs = Your system health monitor (debugging and operations)

Audit events (evidence)

Use audit events when you need:
  • Compliance evidence - Prove what happened for auditors
  • Incident response - Investigate security incidents
  • Forensics - Reconstruct past decisions
Audit events capture:
  • Decision outcome (allow/deny/redact)
  • Reason codes (why the decision was made)
  • Correlation IDs (link related events)
  • Policy identifiers (which policy applied)
  • Redaction indicators (what was redacted)

Logs (operations)

Use logs when you need:
  • Debugging - Figure out why something isn’t working
  • Monitoring - Track system health and performance
  • Alerting - Get notified of issues
Logs capture:
  • Component lifecycle events
  • Performance metrics
  • Error conditions
  • Integration status
Do not treat logs as compliance evidence. Use audit events for compliance.

Default logging posture

TealTiger logging is secure by default: Structured - Key/value pairs, not unstructured text
Redaction-safe - Sensitive data excluded by default
Correlation-ready - Includes trace IDs for distributed tracing
No prompts - User prompts excluded by default
No responses - Model outputs excluded by default
No secrets - API keys and tokens never logged

What logs include

Safe operational data:

What logs exclude

Sensitive data that could leak: ❌ Raw user prompts
❌ Model completions
❌ API keys or tokens
❌ PII (names, emails, phone numbers)
❌ Tool payload values
❌ Full error stack traces with user data
If you need to log additional fields for debugging, apply redaction first and keep them out of production.

Log levels

TealTiger uses standard severity levels:

Examples


Configuring log output

Console logging (default)

File logging

Custom logger


Exporting to observability platforms

OpenTelemetry

Datadog


Best practices

  1. Use INFO in production - Avoid DEBUG unless troubleshooting
  2. Monitor WARN logs - They indicate potential issues
  3. Alert on ERROR logs - Set up alerts for failures
  4. Correlate with traces - Use trace_id to link logs and audit events
  5. Separate logs and audit - Send to different destinations
  6. Rotate log files - Prevent disk space issues
  7. Redact before logging - If you add custom fields, redact first

Audit Event Schema

Complete audit event structure

Cost Metadata

Track AI spending

Audit and Redaction

Security-by-default approach

OpenTelemetry Integration

Export to observability platforms