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Course Outline
Introduction to AI Inference using Docker
- Comprehending AI inference workloads.
- The advantages of containerized inference.
- Deployment scenarios and associated constraints.
Constructing AI Inference Containers
- Choosing appropriate base images and frameworks.
- Packaging pretrained models effectively.
- Organizing inference code for containerized execution.
Securing 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 ease of portability.
- Guaranteeing 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 virtual machines.
Leveraging Docker Compose for Multi-Service AI Systems
- Coordinating inference with supporting components.
- Managing environment variables and configurations.
- Scaling microservices using Compose.
Monitoring and Maintenance of AI Inference Services
- Approaches to logging and observability.
- Identifying failures in inference pipelines.
- Updating and versioning models in production.
Wrap-Up and Next Steps
Requirements
- A solid grasp of fundamental machine learning concepts.
- Practical experience with Python or backend development.
- Basic familiarity with core container concepts.
Target Audience
- Software Developers
- Backend Engineers
- Teams responsible for deploying AI services
14 Hours
Testimonials (3)
multi-tiered, structured course programme.
Bert Paelinckx - Cube SoftwareSolutions
Course - Introduction to Docker
How trainer deliver knowledge so effectively
Vu Thoai Le - Reply Polska sp. z o. o.
Course - Certified Kubernetes Administrator (CKA) - exam preparation
The knowledge and exchanges with Augustin