Discussions

Monitoring is a fundamental component of secure LLM development. Continuous observation of model usage helps detect anomalies, such as unexpected query patterns or potential adversarial attacks. Real-time monitoring can flag misuse, prompt injection, or exposure of sensitive information. Logging user interactions and system behavior provides audit trails for compliance and forensic analysis. Monitoring also enables performance tracking, helping ensure models maintain accuracy, fairness, and robustness over time. Alerts can be configured for abnormal outputs or high-risk scenarios, allowing rapid intervention. By integrating monitoring into the LLM lifecycle, teams enhance overall security, reduce operational risk, and reinforce secure LLM development best practices.