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Duration 21 hours
Course Outline
Introduction to Edge AI and the Role of Kubernetes
- Exploring the significance of AI integration at the network edge
- Leveraging Kubernetes as an orchestrator for distributed systems
- Examining common industry use cases for edge AI
Choosing Kubernetes Distributions for Edge Scenarios
- Evaluating K3s, MicroK8s, and KubeEdge for suitability
- Streamlining installation and configuration processes
- Understanding node specifications and optimal deployment patterns
Designing Architectures for Edge AI
- Analyzing centralized, decentralized, and hybrid edge models
- Optimizing resource allocation on constrained devices
- Structuring multi-node and remote cluster topologies
Implementing Machine Learning Models at the Edge
- Encapsulating inference workloads using containers
- Utilizing GPU and accelerator hardware where applicable
- Overseeing model updates across distributed endpoints
Strategies for Communication and Connectivity
- Mitigating the impact of intermittent or unstable network conditions
- Applying synchronization methods for edge-to-cloud data transfer
- Assessing message queues and protocol requirements
Ensuring Observability and Monitoring at the Edge
- Adopting lightweight monitoring solutions
- Acquiring telemetry data from distant nodes
- Troubleshooting distributed inference processes
Enhancing Security for Edge AI Deployments
- Safeguarding data and models on resource-limited devices
- Implementing secure boot and trusted execution protocols
- Managing authentication and authorization across the node network
Optimizing Performance for Edge Workloads
- Minimizing latency through strategic deployment techniques
- Addressing storage and caching requirements
- Adjusting compute resources to maximize inference efficiency
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of containerized application concepts
- Practical experience in Kubernetes administration
- Familiarity with the fundamentals of edge computing
Target Audience
- IoT engineers managing distributed device fleets
- Cloud-native developers creating intelligent software solutions
- Edge architects designing interconnected 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
