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Course Outline
Introduction to AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments.
- Core components of AgentCore.
- Its position within the AWS Bedrock ecosystem.
AgentCore Runtime and Gateway
- Setting up the AgentCore Runtime.
- Integrating securely via the Gateway API.
- Practical exercise: Deploying a sample agent.
Memory and Stateful Agents
- Implementing persistent context.
- Designing workflows for long-running agents.
- Practical exercise: Enabling session-based memory.
Identity, Permissions, and Security
- Role-based access control for AI agents.
- Identity federation and enterprise integration.
- Practical exercise: Configuring agent permissions.
Observability and Monitoring
- Logging and tracing capabilities with AgentCore.
- Monitoring metrics for usage and performance.
- Practical exercise: Building observability dashboards.
Scaling and Orchestrating Multi-Agent Systems
- Design patterns for multi-agent collaboration.
- Optimizing performance and ensuring reliability.
- Practical exercise: Orchestrating specialized agents.
Governance and Compliance
- Ensuring auditability and safe large-scale rollouts.
- Supported compliance frameworks within AWS.
- Best practices for regulated industries.
Summary and Next Steps
Requirements
- A foundational understanding of cloud-based AI and ML services.
- Practical experience with AWS ecosystem tools.
- Knowledge of enterprise security principles and observability concepts.
Audience
- AI and ML engineers.
- DevOps leads.
- Solution architects.
14 Hours
