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Duration 21 hours
Course Outline
Foundations of Hybrid AI Deployment
- Examining hybrid, cloud, and edge deployment models
- Analyzing AI workload characteristics and infrastructure constraints
- Selecting the optimal deployment topology
Containerizing AI Workloads with Docker
- Creating GPU and CPU-based inference containers
- Managing secure images and registries
- Establishing reproducible environments for AI applications
Deploying AI Services to Cloud Environments
- Executing inference on AWS, Azure, and GCP via Docker
- Provisioning cloud compute resources for model serving
- Securing cloud-based AI endpoints
Edge and On-Prem Deployment Techniques
- Operating AI on IoT devices, gateways, and microservers
- Utilizing lightweight runtimes for edge environments
- Handling intermittent connectivity and local data persistence
Hybrid Networking and Secure Connectivity
- Establishing secure tunnels between edge and cloud infrastructure
- Managing certificates, secrets, and token-based access control
- Tuning performance for low-latency inference
Orchestrating Distributed AI Deployments
- Leveraging K3s, K8s, or lightweight orchestration for hybrid configurations
- Implementing service discovery and workload scheduling
- Automating rollout strategies across multiple locations
Monitoring and Observability Across Environments
- Tracking inference performance across various locations
- Implementing centralized logging for hybrid AI systems
- Detecting failures and executing automated recovery protocols
Scaling and Optimizing Hybrid AI Systems
- Scaling edge clusters and cloud nodes
- Optimizing bandwidth consumption and caching strategies
- Balancing computational loads between cloud and edge resources
Summary and Next Steps
Requirements
- Foundational knowledge of containerization concepts
- Proficiency with Linux command-line operations
- Working familiarity with AI model deployment workflows
Target 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.
