instruction: Explain Docker containerization and best practices
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  Docker Hub catalogs are your go-to collections of trusted, ready-to-use
  container images and resources, tailored to meet specific development needs.
  They make it easier to find high-quality, pre-verified content so you can
  quickly build, deploy, and manage your applications with confidence. Catalogs in
  Docker Hub:
  Simplify content discovery: Organized and curated content makes it easy to
  discover tools and resources tailored to your specific domain or technology.
  Reduce complexity: Trusted resources, vetted by Docker and its partners,
  ensure security, reliability, and adherence to best practices.
  Accelerate development: Quickly integrate advanced capabilities into your
  applications without the hassle of extensive research or setup.
  The following sections provide an overview of the key catalogs available in Docker Hub.
  MCP Catalog
  MCP Catalog
  is a centralized, trusted
  registry for discovering, sharing, and running Model Context Protocol
  (MCP)-compatible tools. Seamlessly integrated into Docker Hub, the catalog
  includes:
  Over 100 verified MCP servers packaged as Docker images
  Tools from partners such as New Relic, Stripe, and Grafana
  Versioned releases with publisher verification
  Simplified pull-and-run support through Docker Desktop and Docker CLI
  Each server runs in an isolated container to ensure consistent behavior and
  minimize configuration headaches. For developers working with Claude Desktop or
  other MCP clients, the catalog provides an easy way to extend functionality with
  drop-in tools.
  To learn more about MCP servers, see
  MCP Catalog and Toolkit
  AI Models Catalog
  AI Models Catalog
  provides
  curated, trusted models that work with
  Docker Model
  Runner
  . This catalog is designed to make AI
  development more accessible by offering pre-packaged, ready-to-use models that
  you can pull, run, and interact with using familiar Docker tools.
  With the AI Models Catalog and Docker Model Runner, you can:
  Pull and serve models from Docker Hub or any OCI-compliant registry
  Interact with models via OpenAI-compatible APIs
  Run and test models locally using Docker Desktop or CLI
  Package and publish models using the
  docker model
  Whether you're building generative AI applications, integrating LLMs into your
  workflows, or experimenting with machine learning tools, the AI Models Catalog
  simplifies the model management experience.