Category: Serverless

Over the last several years, enterprises have accumulated massive amounts of data. Data volumes have increased at an unprecedented rate, exploding from terabytes to petabytes and sometimes exabytes of data. Increasingly, many enterprises are building highly scalable, available, secure, and flexible data lakes on AWS that can handle extremely large datasets. After data lakes are […]

This post is co-written with Madhavan Sriram and Diego Menin from Amazon Transportation Services (ATS). The transportation and logistics industry covers a wide range of services, such as multi-modal transportation, warehousing, fulfillment, freight forwarding, and delivery. At Amazon Transportation Service (ATS), the lifecycle of the shipment is digitally tracked and appended to tens of tracking […]

June 2023: This post was reviewed and updated for accuracy. August 2021: AWS Glue custom blueprints are now generally available. Please visit https://docs.aws.amazon.com/glue/latest/dg/blueprints-overview.html to learn more. Organizations spend significant time developing and maintaining data integration pipelines that hydrate data warehouses, data lakes, and lake houses. As data volume increases, data engineering teams struggle to keep up with […]

This blog post was last reviewed and updated in June 2025. Many AWS customers use a multi-account strategy to host applications for different departments within the same company. However, you might deploy services like Amazon QuickSight using a single-account approach, which raises challenges when you need to use QuickSight in combination with Amazon Athena to […]

May 2022: This post was reviewed for accuracy. In August 2020, we announced the availability of AWS Glue 2.0. AWS Glue 2.0 reduced job startup times by 10x, enabling customers to reali­­ze an average of 45% cost savings on their extract, transform, and load (ETL) jobs. The fast start time allows customers to easily adopt […]

April 2025: This post was reviewed for accuracy. Customers are adopting event-driven-architectures to improve the agility and resiliency of their applications. As a result, data engineers are increasingly looking for simple-to-use yet powerful and feature-rich data processing tools to build pipelines that enrich data, move data in and out of their data lake and data […]

April 2024: This post was reviewed for accuracy.  Organizations of all sizes have recognized that data is one of the key enablers to increase and sustain innovation, and drive value for their customers and business units. They are eagerly modernizing traditional data platforms with cloud-native technologies that are highly scalable, feature-rich, and cost-effective. As you […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Search engines provide the means to retrieve relevant content from a collection of content. However, this can be challenging if certain exact words aren’t entered. You need to find the right item from a catalog of products, or the correct […]

While creating data lakes on the cloud, the data catalog is crucial to centralize metadata and make the data visible, searchable, and queryable for users. With the recent exponential growth of data volume, it becomes much more important to optimize data layout and maintain the metadata on cloud storage to keep the value of data […]

Data quality plays an important role while building an extract, transform, and load (ETL) pipeline for sending data to downstream analytical applications and machine learning (ML) models. The analogy “garbage in, garbage out” is apt at describing why it’s important to filter out bad data before further processing. Continuously monitoring data quality and comparing it […]