AWS News Blog

Amazon Aurora PostgreSQL now supports direct querying of Apache Iceberg and Parquet data in your data lake

Amazon Aurora PostgreSQL now lets you directly query Apache Iceberg and Parquet data stored in your data lake alongside live operational data—no ETL pipelines required. Powered by DuckDB embedded within Aurora, this capability enables single queries that join transactional and historical data using familiar PostgreSQL syntax. It supports AWS Glue Data Catalog, S3, and S3 Tables, with optimizations like predicate pushdown and caching for efficient performance.

AWS Heroes

Celebrating Our Newest AWS Heroes – September 2026

Today, we’re excited to introduce the newest members of the AWS Heroes program. AWS Heroes are a vibrant, worldwide group of AWS experts who go above and beyond to share knowledge, mentor others, and build thriving communities. These individuals make a real difference in helping developers and organizations succeed with AWS. This month, we welcome […]

AWS Weekly Roundup: GPT-6 Sol and Luna, Claude Opus 5.5 on Amazon Bedrock, Strands harness, and more (September 28, 2026)

If there’s one theme that defined last week, it’s choice. The frontier models keep arriving, and the interesting question is no longer just “how smart is it?” but “which model fits this step, at this cost, at this latency?” That’s exactly what landed on Amazon Bedrock over the past few days: GPT-6 Sol and GPT-6 […]

Introducing enhanced custom event buses in Amazon EventBridge for enterprise-scale event-driven applications

Amazon EventBridge announces an enhanced custom event bus for organizations scaling event-driven applications across teams and accounts. Deploy a single event bus shared across all AWS accounts in your organization, with ordering guarantees, a simplified Subscriber resource, and improved economics at scale.

Introducing Amazon CloudWatch Omni: AI-powered observability for generative AI and agentic workloads

Learn how Amazon CloudWatch Omni delivers AI-powered observability purpose-built for generative AI and agentic workloads. Trace, evaluate, and experiment with AI agents across any framework—directly from your IDE or a standalone web experience—using open standards and built-in evaluators for quality, correctness, and coherence.