Category: Advanced (300)

On February 6th 2025, AWS introduced fine-grained access control based on AWS Lake Formation for EMR on EKS from Amazon EMR 7.7 and higher version. You can now significantly enhance your data governance and security frameworks using this feature. In this post, we demonstrate how to implement FGAC on Apache Iceberg tables using EMR on EKS with Lake Formation.

This post showcases a solution that businesses can use to access real-time data insights without the traditional delays between data creation and analysis. By combining Amazon MSK Serverless, Debezium MySQL connector, AWS Glue streaming, and Apache Iceberg tables, the architecture captures database changes instantly and makes them immediately available for analytics through Amazon Athena. A standout feature is the system’s ability to automatically adapt when database structures change—such as adding new columns—without disrupting operations or requiring manual intervention.

In this post, we show you the upgrade process from DC2 instances to Amazon Redshift Serverless. By using Amazon Redshift Serverless, you can run and scale analytics without managing data warehouse infrastructure.

Stifel Financial Corp, a diversified financial services holding company is expanding its data landscape that requires an orchestration solution capable of managing increasingly complex data pipeline operations across multiple business domains. Traditional time-based scheduling systems fall short in addressing the dynamic interdependencies between data products, requires event-driven orchestration. Key challenges include coordinating cross-domain dependencies, maintaining data consistency across business units, meeting stringent SLAs, and scaling effectively as data volumes grow. Without a flexible orchestration solution, these issues can lead to delayed business operations and insights, increased operational overhead, and heightened compliance risks due to manual interventions and rigid scheduling mechanisms that cannot adapt to evolving business needs. In this post, we walk through how Stifel Financial Corp, in collaboration with AWS ProServe, has addressed these challenges by building a modular, event-driven orchestration solution using AWS native services that enables precise triggering of data pipelines based on dependency satisfaction, supporting near real-time responsiveness and cross-domain coordination.

In this post, we show you how to create custom notifications for events occurring in SageMaker Catalog using Amazon EventBridge, AWS Lambda, and Amazon SNS. You can expand this solution to automatically integrate SageMaker Catalog with in-house enterprise workflow tools like ServiceNow and Helix.

This post demonstrates how to configure SageMaker Unified Studio with SSO, set up projects and user onboarding, and access data securely using integrated analytics tools.

As analytical demands grow, many customers are upgrading from DC2 to RA3 or Amazon Redshift Serverless, which offer independent compute and storage scaling, along with advanced capabilities such as data sharing, zero-ETL integration, and built-in artificial intelligence and machine learning (AI/ML) support with Amazon Redshift ML. This post provides a practical guide to plan your target architecture and migration strategy, covering upgrade options, key considerations, and best practices to facilitate a successful and seamless transition.

In this post, we demonstrate how to build a serverless architecture that processes real-time ICU patient monitoring data using Lambda event source mapping for immediate alert generation and data aggregation, followed by persistent storage in Amazon S3 with an Iceberg catalog for comprehensive healthcare analytics.

Apache Airflow 3.x on Amazon MWAA introduces architectural improvements such as API-based task execution that provides enhanced security and isolation. This migration presents an opportunity to embrace next-generation workflow orchestration capabilities while providing business continuity. This post provides best practices and a streamlined approach to successfully navigate this critical migration, providing minimal disruption to your mission-critical data pipelines while maximizing the enhanced capabilities of Airflow 3.

In this post, we introduce Amazon DataZone and explore how Volkswagen used Amazon DataZone to build their data mesh, tackle the challenges encountered, and break the data silos.