AI Observability Engineering: Why Traditional Monitoring Misses 90% of Agent Risks
Traditional observability misses 90% of AI agent security risks. Microsoft's updated Secure Development Lifecycle (SDL) reveals why logs, metrics, and traces need AI-native signals to detect indirect prompt injection, multi-turn jailbreaks, and trust-boundary violations. Enterprise security teams need the 5-step framework to implement AI observability before production.
March 29, 2026 · 13 min read