Category: Technical How-to

Common streaming data enrichment patterns in Amazon Managed Service for Apache FlinkStream data processing allows you to act on data in real time. Real-time data analytics can help you have on-time and optimized responses while improving overall customer experience. Apache Flink is a distributed computation framework that allows for stateful real-time data processing. It provides a […]

In this post, we demonstrate how you can create a custom index analyzer in OpenSearch to implement autocomplete functionality efficiently by using the Edge n-gram tokenizer to match prefix queries without using wildcards.

In this post, we demonstrate how to access an Amazon SageMaker Unified Studio IDC-based domain with a new IAM-based domain using role reuse and attribute-based access control.

This post explores how to build and manage a comprehensive extract, transform, and load (ETL) pipeline using SageMaker Unified Studio workflows through a code-based approach. We demonstrate how to use a single, integrated interface to handle all aspects of data processing, from preparation to orchestration, by using AWS services including Amazon EMR, AWS Glue, Amazon Redshift, and Amazon MWAA. This solution streamlines the data pipeline through a single UI.

In this post, we demonstrate how to use Iceberg Kafka Connect with Amazon Managed Streaming for Apache Kafka (Amazon MSK) Connect to accelerate real-time data ingestion into data lakes, simplifying the synchronization process from transactional databases to Apache Iceberg tables.

In this post, we show you how to implement real-time data correlation using Apache Flink to join streaming order data with historical customer and product information, enabling you to make informed decisions based on comprehensive, up-to-date analytics. We also introduce an optimized solution to automatically load Hive dimension table data into Alluxio Universal Flash Storage (UFS) through the Alluxio cache layer. This enables Flink to perform temporal joins on changing data, accurately reflecting the content of a table at specific points in time.

In this post, we show how to set up workforce access with SageMaker Unified Studio using Ping Identity as an external IdP with IAM Identity Center.

The Alation and SageMaker Unified Studio integration helps organizations bridge the gap between fast analytics and ML development and the governance requirements most enterprises face. By cataloging metadata from SageMaker Unified Studio in Alation, you gain a governed, discoverable view of how assets are created and used. In this post, we demonstrate who benefits from this integration, how it works, the specific metadata it synchronizes, and provide a complete deployment guide for your environment.

In this post, we show you how the read-replica prewarm feature of Amazon EMR 7.12 improves HBase cluster operations by minimizing the hard cutover constraints that make infrastructure changes challenging. This feature gives you a consistent blue-green deployment pattern that reduces risk and downtime for version upgrades and security patches.

In this post, we discuss how you can use Amazon Redshift as a knowledge base to provide additional context to your LLM. We share best practices and explain how you can improve the accuracy of responses from the knowledge base by following these best practices.