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
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)
About the microservices and how to maintenance kubernetes
Yufri Isnaini Rochmat Maulana - Bank Indonesia
Course - Advanced Platform Engineering: Scaling with Microservices and Kubernetes
The way he approached every one of us when he was explaining what we did not understand.
Marian - REGNOLOGY ROMANIA S.R.L.
Course - Deploying Kubernetes Applications with Helm
He explained everything, not only k8s notions.
Stefan Voinea - EMAG IT Research S.R.L
Course - Certified Kubernetes Application Developer (CKAD) - exam preparation
Depth of knowledge of the trainer
Grant Miller - BMW
Course - Certified Kubernetes Administrator (CKA) - exam preparation
There was a lot to lean, but it never felt rushed.