16 Airflow on AWS

 

This chapter covers

  • Designing a deployment strategy for AWS using ECS, S3, EFS and RDS services
  • An overview of several AWS-specific hooks and operators
  • Demonstrating how to use AWS-specific hooks and operators with a use case

After our brief introduction in the previous chapter, this chapter will dive further into how to deploy and integrate Airflow with cloud services in Amazon AWS. First, we’ll start by designing an Airflow deployment by mapping the different components of Airflow to AWS services. Then we’ll explore some of the hooks and operators that Airflow provides for integrating with several key AWS services. Finally, we’ll show how to use these AWS-specific operators and hooks to implement a use case for generating movie recommendations.

16.1 Deploying Airflow in AWS

In the previous chapter, we described the different components that comprise an Airflow deployment. In this section, we’ll design a few deployment patterns for AWS by mapping them to specific AWS cloud services. This should give you a good idea of the process involved in designing an Airflow deployment for AWS and provide a good starting point for implementing one.

16.1.1 Picking cloud services

 
 

16.1.2 Designing the network

 
 
 

16.1.3 Adding DAG syncing

 

16.1.4 Scaling with the CeleryExecutor

 
 

16.1.5 Further steps

 

16.2 AWS-specific hooks and operators

 
 

16.3 Use case: Serverless movie ranking with AWS Athena

 
 
 
 

16.3.1 Overview

 
 

16.3.2 Setting up resources

 
 
 

16.3.3 Building the DAG

 
 

16.3.4 Cleaning up

 
 
 
 

Summary

 
 
 
 
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