Course Outline
Introduction to Edge AI and the Role of Kubernetes
- Exploring the significance of AI at the edge
- Utilizing Kubernetes as an orchestrator for distributed systems
- Examining common industry use cases
Selected Kubernetes Distributions for Edge Contexts
- Evaluating K3s, MicroK8s, and KubeEdge
- Installation procedures and configuration best practices
- Node prerequisites and optimal deployment patterns
Architectural Models for Edge AI Implementation
- Centralized, decentralized, and hybrid edge architectures
- Distributing resources across constrained nodes
- Designing multi-node and remote cluster topologies
Implementing Machine Learning Models at the Edge
- Encapsulating inference workloads within containers
- Leveraging GPU and accelerator hardware where applicable
- Overseeing model updates across distributed devices
Communication and Connectivity Frameworks
- Managing intermittent and unstable network environments
- Techniques for synchronizing data between edge and cloud
- Considerations for message queues and communication protocols
Observability and Monitoring in Edge Settings
- Implementing lightweight monitoring solutions
- Acquiring telemetry data from remote nodes
- Diagnosing distributed inference workflows
Security Protocols for Edge AI Systems
- Safeguarding data and models on limited-capacity devices
- Secure boot processes and trusted execution strategies
- Implementing authentication and authorization across the node network
Optimizing Performance for Edge Workloads
- Minimizing latency via strategic deployment methods
- Addressing storage and caching requirements
- Calibrating compute resources for maximum inference efficiency
Conclusion and Path Forward
Requirements
- A solid grasp of containerized application architectures
- Practical experience in Kubernetes administration
- Knowledge of edge computing principles and concepts
Target Audience
- IoT engineers responsible for deploying distributed devices
- Cloud-native developers creating intelligent applications
- Edge architects designing interconnected environments
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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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
