2Implementation and Integration

• 2.1Agentic AI Solutions and Tool Integrations

  Learn to implement agents that reason and use tools autonomously: multi-agent with Strands Agents/Agent Squad, tool integration via MCP (Model Context Protocol), Bedrock AgentCore, ReAct/stopping conditions with Step Functions, and MCP servers on Lambda/ECS.

• 2.2Model Deployment Strategies

  Learn FM deployment matched to app needs: on-demand invocation with Lambda, Bedrock provisioned throughput, SageMaker endpoints, containers (GPU/memory/token throughput), and model cascading.

• 2.3Designing Enterprise Integration Architectures

  Learn to embed FM capabilities into existing enterprise environments: event-driven (EventBridge), GenAI gateway, identity federation/RBAC/least privilege, Outposts/Wavelength, and CI/CD with CodePipeline/CodeBuild.

• 2.4FM API Integrations

  Learn to integrate FM APIs robustly: sync/async (SQS), Bedrock streaming (WebSocket/SSE), exponential backoff/rate limiting/fallback, observability with X-Ray, and model routing.

• 2.5Application Integration Patterns and Development Tools

  Learn integrations and dev tools that accelerate GenAI apps: UI with Amplify, OpenAPI, no-code with Bedrock Prompt Flows, Bedrock Data Automation, Amazon Q Developer, and troubleshooting with CloudWatch Logs Insights/X-Ray.