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Duration 21 hours
Course Outline
Foundations of Hybrid AI Deployment
- Exploring hybrid, cloud, and edge deployment architectures
- Analyzing AI workload characteristics and infrastructure limitations
- Selecting optimal deployment topologies
Containerizing AI Workloads with Docker
- Creating GPU and CPU inference containers
- Managing secure images and registry strategies
- Establishing reproducible AI environments
Deploying AI Services to Cloud Environments
- Executing inference on AWS, Azure, and GCP via Docker
- Provisioning cloud compute resources for model serving
- Securing cloud-hosted AI endpoints
Edge and On-Prem Deployment Techniques
- Running AI on IoT devices, gateways, and microservers
- Utilizing lightweight runtimes for edge contexts
- Handling intermittent connectivity and local data persistence
Hybrid Networking and Secure Connectivity
- Implementing secure tunneling between edge and cloud layers
- Managing certificates, secrets, and token-based access controls
- Optimizing performance for low-latency inference
Orchestrating Distributed AI Deployments
- Applying K3s, K8s, or lightweight orchestration for hybrid configurations
- Implementing service discovery and workload scheduling
- Automating multi-location rollout strategies
Monitoring and Observability Across Environments
- Monitoring inference performance across distributed locations
- Implementing centralized logging for hybrid AI systems
- Enabling failure detection and automated recovery mechanisms
Scaling and Optimizing Hybrid AI Systems
- Scaling edge clusters and cloud nodes
- Optimizing bandwidth consumption and caching strategies
- Balancing compute loads between cloud and edge resources
Summary and Next Steps
Requirements
- A solid grasp of containerization principles
- Proficiency with Linux command-line utilities
- Knowledge of AI model deployment processes
Intended Audience
- Infrastructure Architects
- Site Reliability Engineers (SREs)
- Edge and IoT Developers
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
multi-tiered, structured course programme.