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Course Outline
Overview of Managed AI Agents
- Definition and scope of AgentCore
- Primary functionalities and service components
- Application scenarios for public sector and industrial use
Initial Agent Architecture and Design
- Defining agent roles and operational objectives
- Setting up managed agent parameters
- Practical exercise: Developing a foundational agent structure
Enhancing Agent Functionality with Memory and Tools
- Incorporating persistent storage and contextual data
- Connecting external tools and application programming interfaces
- Practical exercise: Expanding agent operational capabilities
Foundations of AgentCore Runtime and Gateway
- Summary of runtime system architecture
- Implementing gateway integration for application access
- Practical exercise: Linking an agent to a client application
Deployment of Managed Agents
- Available deployment strategies within AgentCore
- Considerations for scalability and operational continuity
- Practical exercise: Deploying a fully managed agent instance
Monitoring and Observability Standards
- Utilizing metrics and dashboards in AgentCore
- Tracking performance indicators and usage patterns
- Practical exercise: Establishing a monitoring workflow
Best Practices and Future Developments
- Governance, compliance, and regulatory adherence
- Optimizing for system usability and dependability
- Prospective trends in managed AI agent infrastructure
Conclusions and Subsequent Actions
Requirements
- Foundational understanding of artificial intelligence and machine learning principles
- Proficiency with cloud service environments
- Exposure to application development processes
Target Audience
- Professionals interested in AI technologies
- Product management staff
- Generalist software developers
14 Hours