Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 21 hours
Course Outline
Foundations of Edge AI and Kubernetes
- The strategic role of AI in edge environments
- Leveraging Kubernetes as an orchestrator for distributed systems
- Key industry use cases and applications
Choosing Kubernetes Distributions for Edge
- Evaluating K3s, MicroK8s, and KubeEdge
- Installation procedures and configuration best practices
- Node prerequisites and standard deployment models
Designing Edge AI Architectures
- Centralized, decentralized, and hybrid edge models
- Resource distribution across limited-capacity nodes
- Structuring multi-node and remote cluster topologies
Executing Machine Learning Models on the Edge
- Containerizing inference workloads for deployment
- Utilizing GPU and accelerator hardware where applicable
- Overseeing model updates across distributed devices
Strategies for Communication and Connectivity
- Mitigating intermittent or unstable network conditions
- Techniques for edge-to-cloud data synchronization
- Considerations for message queues and communication protocols
Observability and Monitoring in Edge Settings
- Implementing lightweight monitoring solutions
- Gathering telemetry from remote nodes
- Diagnosing and debugging distributed inference processes
Securing Edge AI Deployments
- Safeguarding data and models on resource-limited devices
- Strategies for secure boot and trusted execution
- Managing authentication and authorization across nodes
Optimizing Edge Workload Performance
- Latency reduction through strategic deployment
- Storage and caching best practices
- Adjusting compute resources for optimal inference efficiency
Conclusion and Future Pathways
Requirements
- A solid grasp of containerized application development
- Practical experience in Kubernetes administration
- Foundational knowledge of edge computing principles
Target Audience
- IoT engineers managing distributed device deployments
- Cloud-native developers creating intelligent applications
- Edge architects designing connected system 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
