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Duration 21 hours
Course Outline
Introduction to Edge AI and Kubernetes
- Exploring the strategic role of AI at the edge
- Leveraging Kubernetes as an orchestrator for distributed systems
- Examining typical use cases across various industries
Kubernetes Distributions for Edge Environments
- Comparing K3s, MicroK8s, and KubeEdge
- Installation processes and configuration workflows
- Node requirements and standard deployment patterns
Architectures for Edge AI Deployment
- Evaluating centralized, decentralized, and hybrid edge models
- Allocating resources efficiently across constrained nodes
- Structuring multi-node and remote cluster topologies
Deploying Machine Learning Models at the Edge
- Packaging inference workloads using containers
- Utilizing GPU and accelerator hardware where available
- Overseeing model updates across distributed devices
Communication and Connectivity Strategies
- Navigating intermittent and unstable network conditions
- Implementing synchronization techniques for edge-to-cloud data flows
- Considerations for message queues and protocol selection
Observability and Monitoring at the Edge
- Adopting lightweight monitoring approaches
- Gathering telemetry from remote nodes effectively
- Diagnosing and debugging distributed inference workflows
Security for Edge AI Deployments
- Safeguarding data and models on resource-limited devices
- Implementing secure boot and trusted execution strategies
- Managing authentication and authorization across nodes
Performance Optimization for Edge Workloads
- Minimizing latency through strategic deployment choices
- Addressing storage and caching considerations
- Optimizing compute resources for inference efficiency
Summary and Next Steps
Requirements
- A solid grasp of containerized application architectures
- Practical experience in administering Kubernetes
- A working knowledge of edge computing principles
Target Audience
- IoT engineers responsible for deploying distributed device networks
- Cloud-native developers creating intelligent applications
- Edge architects designing connected infrastructure environments
Testimonials (2)
As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .
Patrick V. Duylovski - UBB + DZI (KBC GROUP)
Course - Docker and Kubernetes
basic understanding of container/kubernetes and how they interact features of the openshift plattform
