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Course Outline
Introduction to AgentCore and Agentic AI
- The role of Agentic AI in enterprise environments.
- Overview of AgentCore's core components.
- Understanding its position within the AWS Bedrock ecosystem.
AgentCore Runtime and Gateway
- Configuration and setup of the AgentCore Runtime.
- Establishing secure API integrations via Gateway.
- Hands-on exercise: deploying a sample agent.
Memory and Stateful Agents
- Implementing persistent context capabilities.
- Designing workflows for long-running agents.
- Hands-on exercise: enabling session-based memory.
Identity, Permissions, and Security
- Managing role-based access for AI agents.
- Facilitating identity federation and enterprise integration.
- Hands-on exercise: configuring agent permissions.
Observability and Monitoring
- Utilizing logging and tracing tools within AgentCore.
- Tracking metrics for usage trends and performance optimization.
- Hands-on exercise: building observability dashboards.
Scaling and Orchestrating Multi-Agent Systems
- Exploring design patterns for effective multi-agent collaboration.
- Strategies for performance optimization and system reliability.
- Hands-on exercise: orchestrating specialized agents.
Governance and Compliance
- Ensuring auditability and managing safe, large-scale rollouts.
- Reviewing compliance frameworks supported by AWS.
- Adhering to best practices for regulated industries.
Summary and Next Steps
Requirements
- Foundational knowledge of cloud-based AI and ML services.
- Practical experience with tools within the AWS ecosystem.
- Familiarity with enterprise security protocols and observability principles.
Target Audience
- AI and ML engineers.
- DevOps team leads.
- Solution architects.
14 Hours
