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 Duration 21 hours

Course Outline

Introduction to Edge AI and Kubernetes

  • The strategic role of AI at the network edge
  • Leveraging Kubernetes as an orchestrator for distributed systems
  • Common use cases across various industries

Kubernetes Distributions for Edge Environments

  • Evaluating K3s, MicroK8s, and KubeEdge
  • Installation and configuration best practices
  • Node prerequisites and deployment architectures

Architectures for Edge AI Deployment

  • Centralized, decentralized, and hybrid edge models
  • Resource distribution across limited-capacity nodes
  • Multi-node and remote cluster topologies

Deploying Machine Learning Models at the Edge

  • Encapsulating inference workloads in containers
  • Utilizing GPU and accelerator hardware where applicable
  • Overseeing model updates across distributed devices

Communication and Connectivity Strategies

  • Managing intermittent and unstable network conditions
  • Techniques for synchronizing data between edge and cloud
  • Considerations for message queues and protocols

Observability and Monitoring at the Edge

  • Implementing lightweight monitoring solutions
  • Gathering telemetry from remote nodes
  • Troubleshooting distributed inference workflows

Security for Edge AI Deployments

  • Safeguarding data and models on constrained devices
  • Strategies for secure boot and trusted execution
  • Authentication and authorization mechanisms across nodes

Performance Optimization for Edge Workloads

  • Minimizing latency through strategic deployment
  • Optimizing storage and caching mechanisms
  • Tuning compute resources for inference efficiency

Summary and Next Steps

Requirements

  • Foundational knowledge of containerized applications
  • Practical experience in Kubernetes administration
  • Basic understanding of edge computing principles

Target Audience

  • IoT engineers responsible for deploying distributed devices
  • Cloud-native developers creating intelligent applications
  • Edge architects designing interconnected environments

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