> ## Documentation Index
> Fetch the complete documentation index at: https://arize-ax.mintlify.dev/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# RealTime

## Overview

The following notebook and lambda function implement the following architecture.

<Frame caption="">
  <img src="https://storage.googleapis.com/arize-phoenix-assets/assets/images/arize-docs-images/d354cb0b-image.jpeg" />
</Frame>

The SageMaker inference pipeline is deployed as a SageMaker endpoint. A Lambda function is generated that is tied to an external endpoint. When a realtime HTTP call is made the lambda function process the call, calls the SageMaker endpoint and returns the data.

A separate process is assumed to process actuals as they are received in the system.

The below file is a Jupyter notebook file that should be uploaded to the Sagemaker Notebook Instance.

<Card title="Google Colaboratory" href="https://colab.research.google.com/github/Arize-ai/tutorials_python/blob/main/Partnerships/SageMaker/PipeLinePlusLambda/PipeLinePlusLambda.ipynb" icon="https://storage.googleapis.com/arize-phoenix-assets/assets/images/arize-docs-images/cookbooks/gc.png" horizontal />

The Lambda function Python is below:

<Card title="tutorials_python/lambda_function.py at main · Arize-ai/tutorials_python" href="https://github.com/Arize-ai/tutorials_python/blob/main/Partnerships/SageMaker/PipeLinePlusLambda/lambda_function.py" icon="github" horizontal>
  GitHub
</Card>

Both the Jupyter Notebook and the Python file should be uploaded to a Notebook Instance.