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 Duration 21 hours

Course Outline

Introduction to Edge AI and Kubernetes

  • The strategic role of AI in edge computing
  • Leveraging Kubernetes as an orchestrator for distributed systems
  • Key industry use cases

Kubernetes Distributions for Edge Environments

  • Evaluation of K3s, MicroK8s, and KubeEdge
  • Best practices for installation and configuration
  • Node prerequisites and deployment patterns

Architectures for Edge AI Deployment

  • Centralized, decentralized, and hybrid edge models
  • Resource allocation strategies for constrained nodes
  • Multi-node and remote cluster topologies

Deploying Machine Learning Models at the Edge

  • Containerizing inference workloads
  • Utilizing GPU and accelerator hardware where available
  • Managing model updates across distributed devices

Communication and Connectivity Strategies

  • Mitigating intermittent and unstable network conditions
  • Techniques for edge-to-cloud data synchronization
  • Considerations for message queues and protocols

Observability and Monitoring at the Edge

  • Implementing lightweight monitoring solutions
  • Gathering telemetry from remote nodes
  • Troubleshooting distributed inference workflows

Security for Edge AI Deployments

  • Safeguarding data and models on constrained devices
  • Secure boot and trusted execution mechanisms
  • Authentication and authorization protocols across nodes

Performance Optimization for Edge Workloads

  • Latency reduction through strategic deployment
  • Optimizing storage and caching mechanisms
  • Tuning compute resources for inference efficiency

Summary and Next Steps

Requirements

  • A solid grasp of containerized applications
  • Proficiency in Kubernetes administration
  • Familiarity with core edge computing principles

Target Audience

  • IoT engineers managing distributed device fleets
  • Cloud-native developers creating intelligent applications
  • Edge architects designing connected operational 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

Provisional Upcoming Courses (Require 5+ participants)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-11-13 09:30
21 hours
InterContinental Hanoi Westlake
304,860,354 VND (Online)
304,860,354 VND (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-11-27 09:30
21 hours
JW Marriott Hanoi
304,860,354 VND (Online)
304,860,354 VND (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-12-11 09:30
21 hours
Pullman Ha Noi
304,860,354 VND (Online)
304,860,354 VND (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2026-12-25 09:30
21 hours
Sofitel Legend Metropole Hanoi
304,860,354 VND (Online)
304,860,354 VND (Classroom)

Edge AI on Kubernetes: Deploying Intelligent Applications at the Edge

2027-01-08 09:30
21 hours
Toong IPH
304,860,354 VND (Online)
304,860,354 VND (Classroom)

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