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Duration 14 hours
Course Outline
Overview of AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments
- Essential components of the AgentCore framework
- Integration within the broader AWS Bedrock ecosystem
AgentCore Runtime and Gateway Services
- Configuration and setup of the AgentCore Runtime
- Establishing secure API connections via Gateway
- Lab exercise: deploying a reference agent
Memory Management and Stateful Agents
- Implementing persistent context retention
- Architecting workflows for long-running agents
- Lab exercise: activating session-based memory
Identity Management, Permissions, and Security
- Applying role-based access controls to AI agents
- Managing identity federation and enterprise integrations
- Lab exercise: defining agent permission sets
Observability and System Monitoring
- Executing logging and tracing features in AgentCore
- Tracking metrics for usage patterns and performance
- Lab exercise: building observability dashboards
Scaling and Orchestrating Multi-Agent Architectures
- Adopting design patterns for multi-agent cooperation
- Enhancing performance reliability and optimization
- Lab exercise: coordinating specialized agents
Governance and Regulatory Compliance
- Ensuring auditability and safe large-scale rollouts
- Leveraging compliance frameworks available in AWS
- Adhering to best practices in regulated sectors
Recap and Future Directions
Requirements
- Familiarity with cloud-native AI/ML services
- Proficiency with tools within the AWS ecosystem
- Foundational knowledge of enterprise security and observability principles
Target Audience
- AI/ML Engineers
- DevOps Leaders
- Solution Architects
