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Duration 21 hours
Course Outline
Foundations of Edge AI and Kubernetes
- Exploring the strategic role of AI at the edge
- Leveraging Kubernetes as an orchestrator for distributed ecosystems
- Examining typical use cases across various industries
Kubernetes Distributions for Edge Environments
- A comparative analysis of K3s, MicroK8s, and KubeEdge
- Installation and configuration workflows
- Node requirements and standard deployment patterns
Architectures for Edge AI Deployment
- Centralized, decentralized, and hybrid edge models
- Resource allocation strategies for constrained nodes
- 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
- Managing model updates across distributed devices
Communication and Connectivity Strategies
- Mitigating intermittent and unstable network conditions
- Synchronization techniques for edge-to-cloud data flows
- Considerations for message queues and protocol selection
Observability and Monitoring at the Edge
- Implementing lightweight monitoring approaches
- Gathering telemetry from remote nodes
- Debugging complex distributed inference workflows
Security for Edge AI Deployments
- Safeguarding data and models on constrained devices
- Secure boot and trusted execution strategies
- Authentication and authorization mechanisms across nodes
Performance Optimization for Edge Workloads
- Latency reduction through strategic deployment
- Storage and caching best practices
- Tuning compute resources for maximum inference efficiency
Summary and Recommended Next Steps
Requirements
- A foundational understanding of containerized applications.
- Practical experience in Kubernetes administration.
- Acquaintance with the core concepts of edge computing.
Target Audience
- IoT engineers responsible for deploying distributed devices.
- Cloud-native developers constructing intelligent applications.
- Edge architects designing complex connected 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
