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Duration 14 hours
Course Outline
Introduction to AgentCore and the Agentic AI Landscape
- The role of Agentic AI in enterprise environments
- Key architectural elements of AgentCore
- Integration within the broader AWS Bedrock ecosystem
AgentCore Runtime and Gateway Mechanisms
- Configuring the AgentCore Runtime environment
- Secure API connections via the Gateway
- Lab work: Deploying a sample agent instance
Memory Management and Stateful Agent Design
- Establishing persistent contextual awareness
- Structuring workflows for long-running agent tasks
- Lab work: Activating session-based memory features
Identity, Access Control, and Security Posture
- Role-based access management for AI agents
- Identity federation and enterprise system integration
- Lab work: Setting up granular agent permissions
Observability and Performance Monitoring
- Implementing logging and tracing with AgentCore
- Tracking usage metrics and performance indicators
- Lab work: Creating comprehensive observability dashboards
Scaling and Orchestrating Multi-Agent Architectures
- Patterns for effective multi-agent collaboration
- Strategies for performance tuning and reliability
- Lab work: Coordinating specialized agent clusters
Governance and Regulatory Compliance
- Ensuring auditability and safe large-scale rollouts
- Overview of AWS-supported compliance frameworks
- Best practices for highly regulated sectors
Conclusion and Path Forward
Requirements
- Familiarity with cloud-native AI/ML services
- Hands-on experience with AWS ecosystem tools
- Solid grasp of enterprise security and observability principles
Target Audience
- AI/ML Engineers
- DevOps Leaders
- Solution Architects
