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Container

As explained in Build AI-Enhanced Web Apps

A software container created and run using Docker to isolate an application and its dependencies.

A software container packages an application with its dependencies and configuration into a self-contained unit. Created and run with Docker, it isolates application components and helps them behave consistently across deployment environments. section 9.6.1

Containers fit into a broader deployment architecture:

  • Docker packages an application or AI service into a repeatable deployment unit. section 9.6.1
  • Kubernetes manages containers at scale, automating load balancing, demand-based scaling, and rolling updates. section 9.6.1
  • Containerization can work alongside caching layers, serverless functions, and model-serving frameworks within backend infrastructure. section 1.2.1

Deploying an AI service

Package an AI model and its associated service in a Docker container so the application can run consistently across environments. When demand or availability requirements increase, place those containers under Kubernetes management for scaling, load balancing, and rolling updates. section 9.6.1

How Build AI-Enhanced Web Apps covers it

How deep it goes
Explains packaging and orchestration roles but stops short of container internals, configuration, or setup commands.
Examples
Uses Docker containers for AI models and associated services, with Kubernetes managing them at scale.
What you can do after
Evaluate how Docker packaging and Kubernetes orchestration support consistent, scalable AI-service deployment.
How it connects
Connects containers to Docker, Kubernetes, orchestration, self-hosting, serverless functions, and model-serving frameworks.

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This explainer was generated by Manning's knowledge graph from the text of Build AI-Enhanced Web Apps. The section links point to the parts of the book it draws on.