Secure & Portable AI Inference with Docker: From Local to Cloud Training Course

Introduction to AI Inference with Docker for Government

• Understanding AI inference workloads for government applications
• Benefits of containerized inference in public sector environments
• Deployment scenarios and constraints for government operations

Building AI Inference Containers for Government

• Selecting appropriate base images and frameworks for government use
• Packaging pretrained models for secure governmental deployment
• Structuring inference code to ensure compatibility with container execution in public sector systems

Securing Containerized AI Services for Government

• Minimizing the attack surface of containers used in government applications
• Managing secrets and sensitive files to meet governmental security standards
• Implementing safe networking and API exposure strategies for government services

Portable Deployment Techniques for Government

• Optimizing images for portability in diverse government environments
• Ensuring predictable runtime environments across governmental systems
• Managing dependencies to support seamless deployment across multiple platforms for government use

Local Deployment and Testing for Government

• Running services locally with Docker to facilitate development in government settings
• Debugging inference containers to ensure reliability in governmental applications
• Testing performance and reliability to meet the high standards required by government operations

Deploying on Servers and Cloud VMs for Government

• Adapting containers for deployment in remote governmental environments
• Configuring secure server access to comply with government security protocols
• Deploying inference APIs on cloud VMs to support scalable government operations

Using Docker Compose for Multi-Service AI Systems in Government

• Orchestrating inference with supporting components to enhance governmental efficiency
• Managing environment variables and configurations for consistent performance in government systems
• Scaling microservices with Docker Compose to meet the dynamic needs of government services

Monitoring and Maintenance of AI Inference Services for Government

• Implementing logging and observability approaches to ensure transparency and accountability in government operations
• Detecting failures in inference pipelines to maintain the reliability of government services
• Updating and versioning models in production to support continuous improvement in governmental AI applications

Summary and Next Steps for Government