Category: Advanced (300)

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.

In this post, we present an observability agent using OpenSearch Service and Amazon Bedrock AgentCore that can help surface root cause and get insights faster, handle multiple query-correlation cycles, and ultimately reduce MTTR even further.

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.

Tipico is the number one name in sports betting in Germany. Every day, we connect millions of fans to the thrill of sport, combining technology, passion, and trust to deliver fast, secure, and exciting betting, both online and in more than a thousand retail shops across Germany. We also bring this experience to Austria, where we proudly operate a strong sports betting business. In this post, we show how Tipico built a unified data transformation platform using Amazon Managed Workflows for Apache Airflow (Amazon MWAA) and AWS Batch.