AWS Glue Best Practices: Building a Secure and Reliable Data Pipeline - AWS Glue Best Practices: Building a Secure and Reliable Data Pipeline

AWS Glue Best Practices: Building a Secure and Reliable Data Pipeline

Publication date: August 26, 2022 (Document revisions)


Data integration is a critical element in building a data lake and a data warehouse. Data integration enables data from different sources to be cleaned, harmonized, transformed, and finally loaded. When building a data warehouse, the bulk of development efforts are needed for building a data integration pipeline. Data integration is one of the most critical pillars in data analytics ecosystems. An efficient and well-designed data integration pipeline is critical for making the data available, and being trusted among the analytics consumers.

In this whitepaper, we show you some of the consideration and best practices for security and reliability of data pipelines built with AWS Glue.

To get the most out of reading this whitepaper, it helps to be familiar with AWS Glue, AWS Glue DataBrew, Amazon Simple Storage Service (Amazon S3), AWS Lambda, and AWS Step Functions.

Are you Well-Architected?

The AWS Well-Architected Framework helps you understand the pros and cons of the decisions you make when building systems in the cloud. The six pillars of the Framework allow you to learn architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable systems. Using the AWS Well-Architected Tool, available at no charge in the AWS Management Console, you can review your workloads against these best practices by answering a set of questions for each pillar.

For more expert guidance and best practices for your cloud architecture—reference architecture deployments, diagrams, and whitepapers—refer to the AWS Architecture Center.


Data volumes and complexities are increasing at an unprecedented rate, exploding from terabytes to petabytes or even exabytes of data. Traditional on-premises based approaches for bundling a data pipeline do not work well with a cloud-based strategy, and most of the time, do not provide the elasticity and cost effectiveness of cloud native approaches.

AWS hears from customers that they want to extract more value from their data, but struggle to capture, store, and analyze all the data generated by today’s modern and digital businesses. Data is growing exponentially, coming from new sources. It is increasingly diverse, and needs to be securely accessed and analyzed by any number of applications and people.

With changing data and business needs, the focus on building a high performing, cost effective, and low maintenance data pipeline is paramount. Introduced in 2017, AWS Glue is a fully managed, serverless data integration service that allows customers to scale based on their workload, with no infrastructures to manage.

The next section discusses common best practices for building and efficiently operating your data pipeline with AWS Glue. This document is intended for advanced users, data engineers and architects.

You may want to refer to AWS Glue Best Practices: Building an Operationally Efficient Data Pipeline to understand more about the AWS Glue product family before proceeding to the next sections.