# Serving Models

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## Introduction

TensorFlow Serving is a flexible, high-performance serving system for machine
learning models, designed for production environments. TensorFlow Serving makes
it easy to deploy new algorithms and experiments, while keeping the same server
architecture and APIs. TensorFlow Serving provides out-of-the-box integration
with TensorFlow models, but can be easily extended to serve other types of
models and data.

Detailed developer documentation on TensorFlow Serving is available:

- [Architecture Overview](https://www.tensorflow.org/tfx/serving/architecture)
- [Server API](https://www.tensorflow.org/tfx/serving/api_docs/cc/)
- [REST Client API](https://www.tensorflow.org/tfx/serving/api_rest)