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Duration 21 hours
Course Outline
Foundations of Edge AI and Kubernetes
- The strategic role of AI in edge computing
- Kubernetes as an orchestration layer for distributed systems
- Key use cases spanning various sectors
Choosing Kubernetes Distributions for the Edge
- Evaluating K3s, MicroK8s, and KubeEdge
- Installation processes and configuration best practices
- Node prerequisites and deployment patterns
Architectural Models for Edge AI
- Centralized, decentralized, and hybrid edge topologies
- Resource distribution across limited hardware
- Multi-node and remote cluster structures
Implementing Machine Learning Models on the Edge
- Containerizing inference workloads
- Leveraging GPU and accelerator hardware where applicable
- Handling model updates on distributed endpoints
Communication and Connectivity Approaches
- Mitigating intermittent and unstable network conditions
- Data synchronization methods between edge and cloud
- Selection of message queues and relevant protocols
Observability and Monitoring in Edge Contexts
- Implementing lightweight monitoring solutions
- Gathering telemetry from remote infrastructure
- Troubleshooting distributed inference processes
Security Considerations for Edge AI
- Safeguarding data and models on restricted devices
- Strategies for secure boot and trusted execution
- Managing authentication and authorization across nodes
Optimizing Edge Workload Performance
- Minimizing latency through strategic deployment
- Best practices for storage and caching
- Adjusting compute resources for inference efficiency
Conclusions and Future Directions
Requirements
- A solid grasp of containerized application architecture
- Practical experience in managing Kubernetes clusters
- Acknowledgment of core edge computing principles
Target Audience
- IoT engineers implementing distributed device networks
- Cloud-native developers creating intelligent applications
- Edge architects structuring connected infrastructures
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