---
title: AWS
description: Integrate DataRobot with Amazon Web Services.

---

# AWS {: #aws }

The sections described below provide techniques for integrating Amazon Web Services with DataRobot.

Topic | Describes...
----- | ------
[Import data from AWS S3](import-from-aws-s3) | Importing data from AWS S3 to AI Catalog and creating an ML project.
[Deploy models on EKS](deploy-dr-models-on-aws) | Deploying and monitor DataRobot models on AWS Elastic Kubernetes Service (EKS) clusters.
[Path-based routing to PPS on AWS](path-based-routing-to-pps-on-aws) | Using a single IP address for all Portable Prediction Servers through path-based routing.
[Score Snowflake data on AWS EMR Spark](score-snowflake-aws-emr-spark) | Scoring Snowflake data via DataRobot models on AWS Elastic Map Reduce (EMR) Spark.
[Ingest data with AWS Athena](ingest-athena) | Ingesting AWS Athena and Parquet data for machine learning.

## Lambda {: #lambda }

Topic | Describes...
----- | ------
[AWS Lambda reporting to MLOps](aws-lambda-reporting-to-mlops) | AWS Lambda serverless reporting of actuals to DataRobot MLOps.
[Use DataRobot Prime models with AWS Lambda](prime-lambda) | Using DataRobot Prime models with AWS Lambda.
[Use Scoring Code with AWS Lambda](sc-lambda) | Making predictions using Scoring Code deployed on AWS Lambda.

## SageMaker {: #sagemaker }

Topic | Describes...
----- | ------
[Deploy models on Sagemaker](sagemaker-deploy) | Deploying on SageMaker and monitoring with MLOps agents.
[Use Scoring Code with AWS SageMaker](sc-sagemaker) | Making predictions using Scoring Code deployed on AWS SageMaker.
