AWS Big Data Blog
Category: Intermediate (200)
Announcing cross-account ingestion for Amazon OpenSearch Service
Amazon OpenSearch Ingestion is a powerful data ingestion pipeline that AWS customers use for many different purposes, such as observability, analytics, and zero-ETL search. Many customers today push logs, traces, and metrics from their applications to OpenSearch Ingestion to store and analyze this data. Today, we are happy to announce that OpenSearch Ingestion pipelines now […]
Tailor Amazon SageMaker Unified Studio project environments to your needs using custom blueprints
Amazon SageMaker Unified Studio is a single data and AI development environment that brings together data preparation, analytics, machine learning (ML), and generative AI development in one place. By unifying these workflows, it saves teams from managing multiple tools and makes it straightforward for data scientists, analysts, and developers to build, train, and deploy ML […]
Get started with Amazon OpenSearch Service: T-shirt size your domain for log analytics
When you’re spinning up your Amazon OpenSearch Service domain, you need to figure out the storage, instance types, and instance count; decide the sharding strategies and whether to use a cluster manager; and enable zone awareness. Generally, we consider storage as a guideline for determining instance count, but not other parameters. In this post, we […]
Amazon SageMaker introduces Amazon S3 based shared storage for enhanced project collaboration
AWS recently announced that Amazon SageMaker now offers Amazon Simple Storage Service (Amazon S3) based shared storage as the default project file storage option for new Amazon SageMaker Unified Studio projects. This feature addresses the deprecation of AWS CodeCommit while providing teams with a straightforward and consistent way to collaborate on project files across the […]
Accelerate your data and AI workflows by connecting to Amazon SageMaker Unified Studio from Visual Studio Code
In this post, we demonstrate how to connect your local VS Code to SageMaker Unified Studio so you can build complete end-to-end data and AI workflows while working in your preferred development environment.
Migrating from API keys to service account tokens in Grafana dashboards using Terraform
In this blog post, we walk through how to migrate from API keys to service account tokens when automating Amazon Managed Grafana resource management. We will also show how to securely store tokens using AWS Secrets Manager and automate token rotation with AWS Lambda.
Use the Amazon DataZone upgrade domain to Amazon SageMaker and expand to new SQL analytics, data processing, and AI uses cases
Don’t miss our upcoming webinar! Register here to join AWS experts as they dive deeper and share practical insights for upgrading to SageMaker. Amazon DataZone and Amazon SageMaker announced a new feature that allows an Amazon DataZone domain to be upgraded to the next generation of SageMaker, making the investment customers put into developing Amazon […]
Build a streaming data mesh using Amazon Kinesis Data Streams
AWS provides two primary solutions for streaming ingestion and storage: Amazon Managed Streaming for Apache Kafka (Amazon MSK) or Amazon Kinesis Data Streams. These services are key to building a streaming mesh on AWS. In this post, we explore how to build a streaming mesh using Kinesis Data Streams.
Introducing restricted classification terms for governed classification in Amazon SageMaker Catalog
Security and compliance concerns are key considerations when customers across industries rely on Amazon SageMaker Catalog. Customers use SageMaker Catalog to organize, discover, and govern data and machine learning (ML) assets. A common request from domain administrators is the ability to enforce governance controls on certain metadata terms that carry compliance or policy significance. Examples […]
Announcing SageMaker Unified Studio Workshops for Financial Services
In this post, we’re excited to announce the release of four Amazon SageMaker Unified Studio publicly available workshops that are specific to each FSI segment: insurance, banking, capital markets, and payments. These workshops can help you learn how to deploy Amazon SageMaker Unified Studio effectively for business use cases.









