Category: Analytics

In this post, we walk through two solutions that demonstrate how to stream data from your Amazon MSK provisioned cluster to Iceberg-based data lakes in Amazon S3 using Amazon Data Firehose.

In this post, we demonstrate a use case where you might need to use an MSK cluster in one AWS account, but MSK Connect is located in a separate account. We demonstrate how to implement IAM authentication after establishing network connectivity. IAM provides enhanced security measures, making sure your systems are protected against unauthorized access.

This post explores how to effectively architect a solution that addresses this specific challenge: enabling comprehensive analytics capabilities for global teams while making sure that your data remains in the AWS Regions required by your compliance framework. We use a variety of AWS services, including Amazon Redshift, Amazon Simple Storage Service (Amazon S3), and Amazon QuickSight.

This post explores RocksDB’s key features and demonstrates its implementation using Spark on Amazon EMR and AWS Glue, providing you with the knowledge you need to scale your real-time data processing capabilities.

In this post, we demonstrate how you can bring transactional data from AWS OLTP data stores like Amazon Relational Database Service (Amazon RDS) and Amazon Aurora flowing into Redshift using zero-ETL integrations to SageMaker Lakehouse Federated Catalog (Bring your own Amazon Redshift into SageMaker Lakehouse). With this integration, you can now seamlessly onboard the changed data from OLTP systems to a unified lakehouse and expose the same to analytical applications for consumptions using Apache Iceberg APIs from new SageMaker Unified Studio.

Amazon OpenSearch Service recently introduced a new Transport Layer Security (TLS) policy Policy-Min-TLS-1-2-PFS-2023-10, which supports the latest TLS 1.3 protocol and TLS 1.2 with Perfect Forward Secrecy (PFS) cipher suites. This new policy improves security and enhances OpenSearch performance. In this post, we discuss the benefits of this new policy and how to enable it using the AWS Command Line Interface (AWS CLI).

In this post, we describe Nexthink’s journey as they implemented a new real-time alerting system using Amazon Managed Service for Apache Flink. We explore the architecture, the rationale behind key technology choices, and the Amazon Web Services (AWS) services that enabled a scalable and efficient solution.

As organizations scale their use of OpenSearch Serverless, understanding network architecture and DNS management becomes increasingly important. This post covers advanced deployment scenarios focused on centralized and distributed access patterns—specifically, how enterprises can simplify network connectivity across multiple AWS accounts and extend access to on-premises environments for their OpenSearch Serverless deployments.

At AWS re:Invent 2024, we introduced a no code zero-ETL integration between Amazon DynamoDB and Amazon SageMaker Lakehouse, simplifying how organizations handle data analytics and AI workflows. In this post, we share how to set up this zero-ETL integration from DynamoDB to your SageMaker Lakehouse environment.

In this post, we guide you through the process of creating a Data Catalog view using EMR Serverless, adding the SQL dialect to the view for Athena, sharing it with another account using LF-Tags, and then querying the view in the recipient account using a separate EMR Serverless workspace and AWS Glue 5.0 Spark job and Athena. This demonstration showcases the versatility and cross-account capabilities of Data Catalog views and access through various AWS analytics services.