AWS Big Data Blog

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.

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.

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 […]

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.

Amazon OpenSearch Service is a fully managed service to support search, log analytics, and generative AI Retrieval Augment Generation (RAG) workloads in the AWS Cloud. It simplifies the deployment, security, and scaling of OpenSearch clusters. As organizations scale their log analytics workloads by continuously collecting and analyzing vast amounts of data, they often struggle to […]

In this post, we will walk through how you can use the improved Amazon Q Developer chat and the new built-in Amazon Q Developer CLI in SageMaker Unified Studio for coding ETL tasks, to fix code errors, and generate ML development workflows. Both interfaces use MCP to read files, run commands, and interact with AWS services directly from the IDE. You can also configure additional MCP servers to extend Amazon Q Developer’s capabilities with custom tools and integrations specific to your workflow.

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 […]

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.

AWS Glue Zero ETL (extract, transform, and load) now supports Salesforce Bulk API, delivering substantial performance gains compared to Salesforce REST API for large-scale data integration for targets such as Amazon SageMaker lakehouse and Amazon Redshift. In this blog post, we show you how to use Zero-ETL powered by AWS Glue with Salesforce Bulk API to accelerate your data integration processes.

Encryption of both data at rest and in transit is a non-negotiable feature for most organizations. Furthermore, organizations operating in highly regulated and security-sensitive environments—such as those in the financial sector—often require full control over the cryptographic keys used for their workloads. Amazon Managed Service for Apache Flink makes it straightforward to process real-time data […]