Category: Intermediate (200)

This post outlines a solution to automatically replicate the entitlements for readers from the source (AWS Lake Formation) to Amazon QuickSight. This solution can be used even when the authentication method in Amazon QuickSight is not using IAM Identity Center and can work with both direct query and SPICE datasets in Amazon QuickSight.

This post shows how to enhance the multi-cluster solution by integrating Amazon Managed Workflows for Apache Airflow (Amazon MWAA) with BPG. By using Amazon MWAA, we add job scheduling and orchestration capabilities, enabling you to build a comprehensive end-to-end Spark-based data processing pipeline.

In this post, we demonstrate how to use Lake Formation for read access while continuing to use AWS Identity and Access Management (IAM) policy-based permissions for write workloads that update the schema and upsert (insert and update combined) data records into the Iceberg tables.

In this post, we walk you through the process of setting up ThoughtSpot integration with Amazon Redshift using IAM Identity Center authentication. The solution provides a secure, streamlined analytics environment that empowers your team to focus on what matters most: discovering and sharing valuable business insights.

In this post, we show you how to use Amazon OpenSearch Service and Amazon Managed Grafana to correlate the various observability signals that improve root cause analysis, thereby resulting in reduced Mean Time to Resolution (MTTR). We also provide a reference solution that can be used at scale for proactive monitoring of enterprise applications to avoid a problem before they occur.

In this post, we show how to develop and test AWS Glue 5.0 jobs locally using a Docker container. This post is an updated version of the post Develop and test AWS Glue version 3.0 and 4.0 jobs locally using a Docker container, and uses AWS Glue 5.0.

In this post, we demonstrate how Amazon Redshift Serverless AI-driven scaling and optimization impacts performance and cost across different optimization profiles.

In this post, we address common challenges associated with manual MSK topic configuration management and present a robust Terraform-based solution. This solution supports both provisioned and serverless MSK clusters.

The Amazon EMR runtime for Apache Spark offers a high-performance runtime environment while maintaining 100% API compatibility with open source Apache Spark and Apache Iceberg table format. In this post, we demonstrate the performance benefits of using the Amazon EMR 7.5 runtime for Spark and Iceberg compared to open source Spark 3.5.3 with Iceberg 1.6.1 tables on the TPC-DS 3TB benchmark v2.13.

In this post, we explore how Apache XTable, combined with the AWS Glue Data Catalog, enables background conversions between open table formats residing on Amazon S3-based data lakes, with minimal to no changes to existing pipelines, in a scalable and cost-effective way.