Security and Monitoring for AI-200: Key Vault, App Configuration, OpenTelemetry, and KQL

Security and monitoring are core AI-200 topics because AI cloud applications are still production software. They use secrets, configuration, databases, queues, containers, functions, and external dependencies. If you cannot secure and troubleshoot the workflow, you are not ready for the exam.

Key Vault and managed identity

Know how to keep secrets out of code, images, and configuration files. Key Vault is the service for secret storage, rotation, and controlled access. Managed identity helps workloads access secrets without embedded credentials. In an exam scenario, look for phrases like avoid storing passwords, rotate credentials, audit secret access, or remove secrets from source control.

App Configuration

App Configuration is for non-secret application settings and feature flags. It is useful when several services need consistent endpoint names, feature flags, or environment-specific settings. A good AI-200 answer separates secrets from ordinary configuration instead of putting every setting in one place.

OpenTelemetry

Distributed AI systems need tracing. OpenTelemetry helps connect requests across APIs, queue workers, functions, and data calls. Study trace context, spans, metrics, dependency timing, and how instrumentation helps identify a slow or failing part of the pipeline.

KQL and troubleshooting

KQL lets you answer operational questions from logs and metrics: Which dependency is failing most often? Did latency increase after deployment? Which function executions failed in the last hour? Practice writing simple filters, summaries, and time-window queries.

The AI-200 practice exam on ExamStudyApp includes security and monitoring scenarios so you can test whether you understand the operational side of Azure AI development. If those questions feel harder than container questions, spend time with real logs and traces before scheduling the real exam.