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Duration 14 hours
Course Outline
Fundamentals of AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments
- Key structural elements of AgentCore
- Contextual positioning within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway Services
- Initialization and setup of the AgentCore Runtime
- Establishing secure API integrations via Gateway
- Applied task: Launching a sample agent deployment
Memory Management and Stateful Agents
- Creating persistent context for interactions
- Structuring long-duration agent workflows
- Applied task: Activating session-based memory features
Identity, Permissions, and Security Protocols
- Implementing role-based access controls for AI agents
- Managing identity federation and enterprise-level integration
- Applied task: Configuring specific agent permissions
Observability and Monitoring Strategies
- Utilizing logging and tracing capabilities in AgentCore
- Tracking metrics for resource usage and performance
- Applied task: Building comprehensive observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Architectural patterns for multi-agent collaboration
- Enhancing performance optimization and system reliability
- Applied task: Orchestrating specialized agent functions
Governance and Compliance Frameworks
- Ensuring auditability and safe, large-scale rollouts
- Overview of compliance frameworks supported by AWS
- Recommended best practices for highly regulated sectors
Recap and Future Directions
Requirements
- A solid grasp of cloud-based AI/ML services
- Proficiency with tools within the AWS ecosystem
- Familiarity with enterprise security and observability principles
Target Audience
- AI/ML Engineers
- DevOps Leaders
- Solution Architects
