Deploying AI Copilots with Docker and Azure Kubernetes Service

Scaling and deploying modern AI applications requires robust cloud infrastructure. This text-based course guides you through the foundational steps of containerizing an AI copilot application and running it reliably on a managed Kubernetes cluster. You will transition from understanding basic container concepts to deploying a fully functional, scalable AI copilot. By reading through practical architecture explanations, you will learn how to manage container registries, configure orchestrators, and handle modern application patterns like retrieval-augmented generation backend integrations. What you will learn: Understand the core architecture of containerized AI applications and Kubernetes components; Configure Docker containers to package your AI copilot application and its dependencies; Deploy container images securely using Azure Container Registry; Set up and manage an Azure Kubernetes Service cluster for container orchestration; Apply modern deployment patterns, including managing environment variables for AI model APIs; Practice configuring basic scaling and self-healing policies for your deployed services. The curriculum starts with essential definitions of containerization and cloud orchestration before walking you through step-by-step configuration files and deployment manifests. You will read through clear explanations of networking, security, and integration with external AI APIs. This course is designed for beginner cloud enthusiasts, developers, and system administrators looking to deploy AI workloads without prior Kubernetes experience. Begin reading today to build your cloud deployment skills and run your own AI copilot in the cloud.