AWS Generative AI Monitoring and Auditability

As generative AI transitions from experimental prototypes to production systems, ensuring compliance, security, and operational visibility becomes a critical requirement. This course provides a clear, text-based guide to setting up robust monitoring and audit trails for your AI workloads. You will progress from understanding foundational AI governance concepts to implementing practical tracking, logging, and auditing workflows on AWS. What you'll learn: - Learn the core principles of AI governance, risk management, and compliance frameworks. - Configure CloudTrail to capture and audit API activity across generative AI services. - Monitor model performance, latency, and system health using CloudWatch metrics and alarms. - Implement guardrails and track policy violations in real-time to prevent harmful outputs. - Analyze LLM inputs and outputs safely using structured logging and data privacy best practices. - Practice setting up automated alerts for anomalous behavior or unexpected cost spikes in your AI pipelines. The course begins with essential terminology and compliance fundamentals before guiding you through step-by-step text configurations for AWS monitoring tools. This course is designed for beginners, cloud administrators, and developers looking to secure their AI systems, with no prior AI auditing experience required. Start building secure, transparent, and compliant generative AI applications on AWS today.