Category: Technical How-to

In this blog post, we use Athena and Amazon SageMaker Unified Studio to explore Parquet Column Indexes and demonstrate how they can improve Iceberg query performance. We explain what Parquet Column Indexes are, demonstrate their performance benefits, and show you how to use them in your applications.

In this post, we show how to configure Kerberos authentication for Spark jobs on Amazon EMR on EKS, authenticating against a Kerberos-enabled HMS so you can run both Amazon EMR on EC2 and Amazon EMR on EKS workloads against a single, secure HMS deployment.

In this post, we introduce the workload simulation workbench for Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express Broker. The simulation workbench is a tool that you can use to safely validate your streaming configurations through realistic testing scenarios.

In this post, we show you how to build a serverless, low-cost monitoring solution for Amazon Redshift Serverless that proactively detects performance anomalies and sends actionable alerts directly to your selected Slack channels.

In this post, we provide implementation guidance for building integrated analytics solutions that combine the generative BI features of Amazon Quick with Amazon Redshift and Amazon Athena SQL analytics capabilities.

In this post, we show you how to use the new topic management capabilities of Amazon MSK to streamline your Apache Kafka operations. We demonstrate how to manage topics through the console, control access with AWS Identity and Access Management (IAM), and bring topic provisioning into your continuous integration and continuous delivery (CI/CD) pipelines.

In this post, we explore scenarios where customers need more control over their network infrastructure when building their unified data and analytics strategic layer. We’ll show how you can bring your own Amazon Virtual Private Cloud (Amazon VPC) and set up Amazon SageMaker Unified Studio for strict network control.

In this post, we explore SageMaker Unified Studio multi-account deployments in depth: what they entail, why they matter, and how to implement them effectively. We examine architecture patterns, evaluate trade-offs across security boundaries, operational overhead, and team autonomy. We also provide practical guidance to help you design a deployment that balances centralized control with distributed ownership across your organization.

In this post, we show you how to use Apache Airflow tags to systematically manage DAG permissions, reducing operational burden while maintaining robust security controls that complement infrastructure-level security measures.

In this post, we show you how to configure a native identity provider (IdP) federation for Amazon Redshift Serverless using Network Load Balancer. You will learn how to enable secure connections from tools like DBeaver and Power BI while maintaining your enterprise security standards.