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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 AgentCore
- Integration within the AWS Bedrock ecosystem
AgentCore Runtime and Gateway
- Configuring the AgentCore Runtime
- Secure API integration via Gateway
- Practical exercise: deploying a sample agent
Memory and Stateful Agents
- Establishing persistent context
- Designing workflows for long-running agents
- Practical exercise: activating session-based memory
Identity, Permissions, and Security
- Implementing role-based access for AI agents
- Identity federation and enterprise integration strategies
- Practical exercise: setting up agent permissions
Observability and Monitoring
- Utilizing logging and tracing features in AgentCore
- Tracking metrics for usage and performance
- Practical exercise: creating observability dashboards
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for collaboration among multiple agents
- Optimizing performance and ensuring reliability
- Practical exercise: orchestrating specialized agents
Governance and Compliance
- Ensuring auditability and safe large-scale rollouts
- Compliance frameworks available in AWS
- Best practices for industries with regulatory requirements
Summary and Next Steps
Requirements
- A solid understanding of cloud-based AI/ML services
- Familiarity with tools within the AWS ecosystem
- Knowledge of enterprise security and observability principles
Target Audience
- AI/ML engineers
- DevOps leads
- Solution architects
