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Duration 21 hours
Course Outline
Foundations of Edge AI and Kubernetes
- The critical role of AI in edge computing
- How Kubernetes serves as the orchestrator for distributed environments
- Common use cases observed across various industries
Kubernetes Distributions Suited for Edge
- A comparative analysis of K3s, MicroK8s, and KubeEdge
- Standard installation and configuration workflows
- Node specifications and effective deployment patterns
Architectural Models for Edge AI
- Evaluating centralized, decentralized, and hybrid edge models
- Strategic resource allocation on constrained nodes
- Designing multi-node and remote cluster topologies
Implementing Machine Learning at the Edge
- Containerizing inference workloads for portability
- Leveraging GPU and accelerator hardware where available
- Strategies for managing model updates across distributed devices
Managing Communication and Connectivity
- Mitigating issues caused by intermittent or unstable networks
- Techniques for synchronizing data between edge and cloud
- Considerations regarding message queues and protocols
Observability and Monitoring in Edge Networks
- Adopting lightweight monitoring solutions
- Efficient telemetry collection from remote nodes
- Debugging complex, distributed inference workflows
Enhancing Security for Edge AI
- Safeguarding data and models on limited-capability devices
- Implementing secure boot and trusted execution environments
- Managing authentication and authorization across multiple nodes
Optimizing Performance for Edge Workloads
- Minimizing latency through intelligent deployment strategies
- Best practices for storage and caching
- Tuning compute resources to maximize inference efficiency
Conclusion and Future Directions
Requirements
- Core knowledge of containerized applications
- Practical experience with Kubernetes administration
- Basic familiarity with edge computing principles
Intended Audience
- IoT engineers managing distributed device fleets
- Cloud-native developers crafting intelligent applications
- Edge architects designing comprehensive 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