> For the complete documentation index, see [llms.txt](https://lwang010.gitbook.io/longw/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lwang010.gitbook.io/longw/mlops/chap-6.-team-infra/intro.md). # 3.1 Prototype Research (If the DVC + MLFlow + Anaconda stack works for you, that's great. Metaflow provides similar features. Cloud integration is really important at Netflix's scale ) * Hardware: how to connect multiple servers * Utility functions: the pre-processing/post-processing pipeline(DAG), the training pipeline, the inference pipeline, visualization pipeline, * Model register: a platform to track model and compare model * Data: Data management system/ data warehouse * Multiple containers/env maintaining **What elements should be covered in an ML platform?** * Data management * Experiment management * Model management * Deployment for inference * Reproducibility * Testing and monitoring All through a consistent interface. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://lwang010.gitbook.io/longw/mlops/chap-6.-team-infra/intro.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.