Course Outline
Introduction to AI Inference with Docker
- Understanding AI inference workloads
- Benefits of containerized inference
- Deployment scenarios and constraints
Building AI Inference Containers
- Selecting base images and frameworks
- Packaging pretrained models
- Structuring inference code for container execution
Securing Containerized AI Services
- Minimizing container attack surface
- Managing secrets and sensitive files
- Safe networking and API exposure strategies
Portable Deployment Techniques
- Optimizing images for portability
- Ensuring predictable runtime environments
- Managing dependencies across platforms
Local Deployment and Testing
- Running services locally with Docker
- Debugging inference containers
- Testing performance and reliability
Deploying on Servers and Cloud VMs
- Adapting containers for remote environments
- Configuring secure server access
- Deploying inference APIs on cloud VMs
Using Docker Compose for Multi-Service AI Systems
- Orchestrating inference with supporting components
- Managing environment variables and configs
- Scaling microservices with Compose
Monitoring and Maintenance of AI Inference Services
- Logging and observability approaches
- Detecting failures in inference pipelines
- Updating and versioning models in production
Summary and Next Steps
Requirements
- An understanding of basic machine learning concepts
- Experience with Python or backend development
- Familiarity with foundational container concepts
Audience
- Developers
- Backend engineers
- Teams deploying AI services
Testimonials (3)
Encouraging and openness to expanding the discussion on topics related to the training scope but with the specific context of our company
Michal Koscinski - Volkswagen Poznan Sp. z o.o.
Course - Docker, Kubernetes and OpenShift 3 for Administrators
Machine Translated
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
the trainer had a lot of knowledge and patience to share with us
