Category: Intermediate (200)

In this post, we’ll show you how to use Kiro powers, a new capability that equips Kiro with contextual knowledge and tooling. You can simplify your MSK cluster management, from initial setup to diagnosing common issues, all through natural language conversations.

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 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 Amazon Managed Streaming for Apache Kafka (Amazon MSK) Express brokers brokers streamline the end-to-end activities for Kafka administration.

Finding the right data assets in large enterprise catalogs can be challenging, especially when thousands of datasets are cataloged with organization-specific metadata. Amazon SageMaker Unified Studio now supports custom metadata search filters. In this post, you learn how to create custom metadata forms, publish assets with metadata values, and use structured filters to discover those assets.

In this post, Vanguard’s Financial Advisor Services division describes how they evolved from a single Amazon Redshift cluster to a multi-warehouse architecture using data sharing and serverless endpoints to eliminate performance bottlenecks caused by exponential growth in ETL jobs, dashboards, and user queries.

In this post, we share insights from one of our customers’ migration from DC2 to RA3 instances. The customer, a large enterprise in the retail industry, operated a 16-node dc2.8xlarge cluster for business intelligence (BI) and ETL workloads. Facing growing data volumes and disk capacity limitations, they successfully migrated to RA3 instances using a Blue-Green deployment approach, achieving improved ETL query performance and expanded storage capacity while maintaining cost efficiency.

On November 4, 2025, Amazon Kinesis Data Streams introduced On-demand Advantage mode, a capability that enables on-demand streams to handle instant throughput increases at scale and cost optimization for consistent streaming workloads. Historically, you had to choose between provisioned mode, which required managing stream capacity, and on-demand mode, which automatically scaled capacity, but this new offering removes the need to think about stream type at all. In this post, we show three real-world scenarios comparing different usage patterns and demonstrate how On-demand Advantage mode can optimize your streaming costs while maintaining performance and flexibility.

OpenSearch Service offers zero-ETL integrations with other Amazon Web Service (AWS) services, enabling seamless data access and analysis without the need for maintaining complex data pipelines. Zero-ETL refers to a set of integrations designed to minimize or eliminate the need to build traditional extract, transform, load (ETL) pipelines. In this post, we explore various zero-ETL integrations available with OpenSearch Service that can help you accelerate innovation and improve operational efficiency.