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Course Outline
Introduction to Edge AI and Kubernetes
- Understanding the role of AI at the edge
- Kubernetes as an orchestrator for distributed environments
- Typical use cases across industries
Kubernetes Distributions for Edge Environments
- Comparing K3s, MicroK8s, and KubeEdge
- Installation and configuration workflows
- Node requirements and deployment patterns
Architectures for Edge AI Deployment
- Centralized, decentralized, and hybrid edge models
- Resource allocation across constrained nodes
- Multi-node and remote cluster topologies
Deploying Machine Learning Models at the Edge
- Packaging inference workloads with containers
- Using GPU and accelerator hardware when available
- Managing model updates on distributed devices
Communication and Connectivity Strategies
- Handling intermittent and unstable network conditions
- Synchronization techniques for edge-to-cloud data
- Message queues and protocol considerations
Observability and Monitoring at the Edge
- Lightweight monitoring approaches
- Collecting telemetry from remote nodes
- Debugging distributed inference workflows
Security for Edge AI Deployments
- Protecting data and models on constrained devices
- Secure boot and trusted execution strategies
- Authentication and authorization across nodes
Performance Optimization for Edge Workloads
- Reducing latency through deployment strategies
- Storage and caching considerations
- Tuning compute resources for inference efficiency
Summary and Next Steps
Requirements
- An understanding of containerized applications
- Experience with Kubernetes administration
- Familiarity with edge computing concepts
Audience
- IoT engineers deploying distributed devices
- Cloud-native developers building intelligent applications
- Edge architects designing connected environments
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from £5700 online delivery, based on a group of 2 delegates, £1800 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (5)
There was a lot to lean, but it never felt rushed.
thomas gardner - National Oceanography Centre
Course - Docker, Kubernetes and OpenShift for Administrators
It is an in-deep Kubernetes training covering all important aspects to manage Kubernetes, be it in the cloud or on-premise, but the pace is gradual and well adjusted, so the training can be followed very well by students who have had no prior exposure to Kubernetes, as it builds up knowledge from the ground up.
Volker Kerkhoff
Course - Docker and Kubernetes: Building and Scaling a Containerized Application
It gave a good grounding for Docker and Kubernetes.
Stephen Dowdeswell - Global Knowledge Networks UK
Course - Docker (introducing Kubernetes)
I generally liked the trainer knowledge and enthusiasm.
Ruben Ortega
Course - Docker and Kubernetes
I mostly enjoyed the knowledge of the trainer.
