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 Duration 21 hours

Course Outline

Introduction to Edge AI and Kubernetes

  • Exploring the significance of AI at the edge
  • Leveraging Kubernetes as an orchestrator for distributed settings
  • Common industry use cases

Kubernetes Distributions for Edge Environments

  • Evaluating K3s, MicroK8s, and KubeEdge
  • Installation and configuration procedures
  • Node prerequisites and deployment patterns

Architectural Models for Edge AI Deployment

  • Centralized, decentralized, and hybrid edge paradigms
  • Distributing resources across limited nodes
  • Structures for multi-node and remote clusters

Implementing Machine Learning Models at the Edge

  • Containerizing inference tasks
  • Utilizing GPU and accelerator hardware where possible
  • Overseeing model updates on dispersed devices

Communication and Connectivity Approaches

  • Mitigating intermittent and unstable network states
  • Data synchronization methods between edge and cloud
  • Considerations for message queues and protocols

Observability and Monitoring at the Edge

  • Implementing lightweight monitoring solutions
  • Gathering telemetry from remote locations
  • Troubleshooting distributed inference processes

Security in Edge AI Deployments

  • Safeguarding data and models on limited devices
  • Strategies for secure boot and trusted execution
  • Managing authentication and authorization across nodes

Performance Tuning for Edge Workloads

  • Mining latency via deployment tactics
  • Optimizing storage and caching mechanisms
  • Adjusting compute resources for inference effectiveness

Conclusion and Future Steps

Requirements

  • A solid grasp of containerized applications
  • Practical experience in Kubernetes administration
  • Acquaintance with edge computing principles

Target Audience

  • IoT engineers responsible for deploying distributed devices
  • Cloud-native developers creating intelligent applications
  • Edge architects designing interconnected environments

Number of participants


Price per participant

Open Training Courses require 5+ participants.

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

Eric Scholze - NOW IT GmbH
Course - Introduction to Containers, Kubernetes & OpenShift

Upcoming Courses

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-11-24 09:30
21 hours
Bratislava CBC
1160 EUR (Online)
1760 EUR (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-12-08 09:30
21 hours
Bratislava CBC
1160 EUR (Online)
1760 EUR (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-12-22 09:30
21 hours
Bratislava CBC
1160 EUR (Online)
1760 EUR (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2027-01-05 09:30
21 hours
Bratislava CBC
1160 EUR (Online)
1760 EUR (Classroom)

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