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-# Deploy
-
-This section focuses on deploying real-world models. It contains
-the following documents:
-
- * [Distributed TensorFlow](../deploy/distributed.md), which explains how to create
- a cluster of TensorFlow servers.
- * [How to run TensorFlow on Hadoop](../deploy/hadoop.md), which has a highly
- self-explanatory title.
- * [How to run TensorFlow with the S3 filesystem](../deploy/s3.md), which explains how
- to run TensorFlow with the S3 file system.
- * The entire document set for [TensorFlow serving](/serving), an open-source,
- flexible, high-performance serving system for machine-learned models
- designed for production environments. TensorFlow Serving provides
- out-of-the-box integration with TensorFlow models.
- [Source code for TensorFlow Serving](https://github.com/tensorflow/serving)
- is available on GitHub.
-
-[TensorFlow Extended (TFX)](/tfx) is an end-to-end machine learning platform for
-TensorFlow. Implemented at Google, we've open sourced some TFX libraries with the
-rest of the system to come.