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Course Outline
Introduction to AgentCore and Agentic AI
- Agentic AI in the enterprise environment
- Key components of AgentCore
- Integration within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Configuring the AgentCore Runtime for government use
- Secure API integration with the Gateway
- Practical exercise: deploying a sample agent for government applications
Memory and Stateful Agents
- Implementing persistent context in stateful agents
- Designing long-running workflows for continuous operations
- Practical exercise: enabling session-based memory for enhanced user experience
Identity, Permissions, and Security
- Role-based access control for AI agents in government systems
- Federated identity management and enterprise integration
- Practical exercise: configuring agent permissions to ensure secure operations
Observability and Monitoring
- Logging and tracing capabilities with AgentCore for government
- Metrics for usage and performance monitoring
- Practical exercise: implementing observability dashboards for real-time insights
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for collaborative multi-agent systems
- Performance optimization and reliability in government operations
- Practical exercise: orchestrating specialized agents to enhance efficiency
Governance and Compliance
- Ensuring auditability and safe deployment at scale for government projects
- Compliance frameworks supported within AWS for government use
- Best practices for regulated industries, including government agencies
Summary and Next Steps
Requirements
- A comprehensive understanding of cloud-based artificial intelligence and machine learning services for government.
- Practical experience with the AWS ecosystem tools.
- Proficiency in enterprise security and observability concepts.
Audience
- AI/ML engineers for government.
- DevOps leads for government.
- Solution architects for government.
14 Hours