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Course Outline
Foundations of AI Inference with Docker
- Comprehending AI inference workloads
- Advantages of containerized inference
- Deployment scenarios and associated constraints
Creating AI Inference Containers
- Choosing appropriate base images and frameworks
- Encapsulating pretrained models
- Organizing inference code for container execution
Protecting Containerized AI Services
- Reducing the container attack surface
- Handling secrets and sensitive files securely
- Strategies for safe networking and API exposure
Techniques for Portable Deployment
- Optimizing images for enhanced portability
- Maintaining predictable runtime environments
- Managing dependencies across different platforms
Local Deployment and Testing
- Executing services locally via Docker
- Troubleshooting inference containers
- Evaluating performance and reliability
Deployment on Servers and Cloud VMs
- Adjusting containers for remote environments
- Setting up secure server access
- Deploying inference APIs on cloud VMs
Leveraging Docker Compose for Multi-Service AI Systems
- Coordinating inference with supporting components
- Managing environment variables and configurations
- Scaling microservices using Compose
Monitoring and Maintaining AI Inference Services
- Approaches to logging and observability
- Identifying failures in inference pipelines
- Updating and versioning models in production
Wrap-up and Future Directions
Requirements
- A grasp of fundamental machine learning principles
- Proficiency with Python or backend development
- Knowledge of core container concepts
Target Audience
- Developers
- Backend engineers
- Teams responsible for deploying AI services
14 Hours
Testimonials (2)
multi-tiered, structured course programme.
Bert Paelinckx - Cube SoftwareSolutions
Course - Introduction to Docker
The training met expectations with its clear explanations, real-world examples, and hands-on labs that made complex topics easy to understand. It provided valuable insights into container orchestration, security, scaling and many other advanced topics.