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Duration 14 hours
Course Outline
Introduction to AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments
- Fundamental components of the AgentCore framework
- Contextual placement within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Configuring and setting up the AgentCore Runtime
- Achieving secure API integration via Gateway
- Exercise: Deploying a sample agent application
Memory and Stateful Agents
- Integrating persistent context for agents
- Designing workflows for long-running agent operations
- Exercise: Enabling session-based memory capabilities
Identity, Permissions, and Security
- Implementing role-based access control for AI agents
- Handling identity federation and enterprise integrations
- Exercise: Configuring secure agent permissions
Observability and Monitoring
- Utilizing logging and tracing features in AgentCore
- Tracking metrics for usage patterns and performance
- Exercise: Building observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Applying design patterns for multi-agent collaboration
- Optimizing performance and ensuring system reliability
- Exercise: Orchestrating specialized agent workflows
Governance and Compliance
- Ensuring auditability and safe large-scale rollouts
- Adhering to compliance frameworks available on AWS
- Best practices for industries with strict regulatory requirements
Summary and Next Steps
Requirements
- Familiarity with cloud-based AI and ML services
- Practical experience with the AWS ecosystem and its tools
- Solid understanding of enterprise security and observability principles
Target Audience
- AI and ML engineers
- DevOps leaders
- Solution architects
