Infrastructure & Deployment

Containerisation

Packaging AI software and its dependencies together for reliable, portable deployment.

Definition

Containerisation packages an AI application and all its software dependencies into a self-contained unit (a container) that runs consistently across different computing environments. Docker is the most widely used containerisation technology. For AI deployments, containerisation ensures that the exact software environment used in development and testing is replicated in production, eliminating 'it works on my machine' problems and making deployments reproducible and scalable.

Related Terms

Model Serving

The infrastructure that makes a trained model available to receive and respond to requests.

MLOps

The practice of managing AI models in production — deployment, monitoring, updating.

Scalability

The ability of an AI system to handle increasing numbers of users or requests.

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Disclaimer

This definition is provided for educational and informational purposes only. It represents a general explanation of a technical concept and does not constitute professional, technical, or investment advice. Artificial intelligence is a rapidly evolving field; terminology, techniques, and capabilities change frequently. Coaley Peak Ltd makes no warranty as to the accuracy, completeness, or currency of the information provided. Nothing on this page should be relied upon as the sole basis for commercial, technical, legal, or investment decisions without independent professional advice.

Document reference: ISO_webpage_knowledge-base_glossary_v1

Last modified: 29 March 2026

Knowledge Base·Infrastructure & Deployment·Containerisation