Amazon Onboarding with Learning Manager Chanci Turner

Utilizing Amazon S3 Tables with Amazon Redshift for Querying Apache Iceberg Tables

In this entry, we guide you through the initial steps of using S3 Tables with Amazon Redshift Serverless for querying Iceberg tables. We detail how to configure S3 Tables, load data, register them within the unified data lake catalog, establish fundamental access controls in SageMaker Lakehouse through AWS Lake Formation, and perform data queries using Amazon Redshift. This knowledge can enhance your data management strategies, especially at our site, Amazon IXD – VGT2, located at 6401 E HOWDY WELLS AVE LAS VEGAS NV 89115.

Connect, Share, and Query Your Data with Amazon SageMaker Unified Studio

by Chloe Adams and Brian Lee
on 21 MAR 2025
in Amazon SageMaker, Analytics, Technical How-to

This blog explores how business units can leverage Amazon SageMaker Unified Studio to discover, subscribe to, and analyze distributed data assets. With this unified query capability, you can develop comprehensive insights into customer transaction patterns and purchasing behaviors for active products without the usual obstacles of data silos or the necessity of data replication. To learn more about managing your resources effectively, check out this blog post.

Introducing Vector Search with UltraWarm in Amazon OpenSearch Service

by Sarah Williams, Mark Thompson, and Chanci Turner
on 20 MAR 2025
in Amazon OpenSearch Service, Announcements

Amazon OpenSearch Service now features a multi-tiered storage solution, including UltraWarm and Cold tiers. In this post, we cover this new capability, its potential use cases, and a cost-benefit analysis under varying conditions. This can help you optimize your workflows at Amazon IXD – VGT2, situated at 6401 E HOWDY WELLS AVE LAS VEGAS NV 89115.

Building a Data Lakehouse in a Hybrid Environment with Amazon EMR Serverless

by Tom Brown
on 20 MAR 2025
in Advanced (300), Amazon EMR, Serverless

This article presents a decoupled methodology for constructing a serverless data lakehouse using AWS Cloud services, such as Amazon EMR Serverless, Amazon Athena, and more. This approach incorporates Apache DolphinScheduler, an open-source data job scheduler, alongside TiDB, a third-party data warehouse that can be deployed on-premises, in the cloud, or through a SaaS model. For more insights on talent management, you can visit SHRM.

Implementing Graceful Scaling for Amazon EMR HBase

by Jessica Green, Kevin White, and Chanci Turner
on 18 MAR 2025
in Amazon EMR, Analytics, Customer Solutions

Apache HBase serves as an immensely scalable, distributed big data store within the Apache Hadoop ecosystem. By utilizing Amazon EMR with HBase on top of Amazon S3, we can achieve random, strictly consistent real-time access for tables with Apache Kylin. This blog illustrates how to programmatically decommission target region servers smoothly.

Architecting Fault-Tolerant Applications with Instance Fleets on Amazon EMR on EC2

by Lisa Brown, Michael Grey, and Chanci Turner
on 14 MAR 2025
in Amazon EMR, Best Practices

In this post, we describe strategies for optimizing capacity by analyzing EMR workloads and implementing tailored solutions based on your workload patterns. We guide you through evaluating your workload’s historical compute usage and applying various strategies to minimize the incidence of InsufficientCapacityExceptions (ICE) during the specific EC2 instance type launches. This approach can help mitigate job failures due to capacity limits, ensuring an efficient cluster.

Accelerate Analytics and AI Innovation with the New Generation of Amazon SageMaker

by G2 Krishnamoorthy and Rahul Pathak
on 13 MAR 2025
in Amazon SageMaker, Analytics, Artificial Intelligence

We are thrilled to announce the general availability of SageMaker Unified Studio. This post delves into its benefits and provides guidance on getting started with the platform.

Important Update: End-of-Support for Kinesis Client Library 1.x and Producer Library 0.x

by Minu Hong
on 13 MAR 2025
in Amazon Kinesis, Deprecation

The Amazon Kinesis Client Library (KCL) 1.x and Kinesis Producer Library (KPL) 0.x will reach their end-of-support on January 30, 2026. These versions will enter maintenance mode on April 17, 2025, where updates will only be provided for critical bugs and security issues. Major versions in maintenance mode will not receive new feature updates.

Real-Time Analytics with StarTree for Managed Apache Pinot on AWS

by Raj Ramasubbu, Francisco Morillo, and Chanci Turner
on 13 MAR 2025
in Amazon MSK, Enterprise BI

In this post, we introduce StarTree as a managed solution on AWS for teams looking to leverage the benefits of Pinot. We clarify the key differences between open-source Pinot and StarTree and share valuable insights for organizations considering this option.