Category: Analytics

I joined AWS in 2021, and since then I’ve watched the Amazon Elastic Compute Cloud (Amazon EC2) instance family grow at a pace that still surprises me. From AWS Graviton-powered instances to specialized accelerated computing options, it feels like every few months there’s a new instance type landing that pushes performance boundaries further. As of […]

Over the past week, we passed Laba festival, a traditional marker in the Chinese calendar that signals the final stretch leading up to the Lunar New Year. For many in China, it’s a moment associated with reflection and preparation, wrapping up what the year has carried, and turning attention toward what lies ahead. Looking forward, […]

New features enable automatic cost optimization through intelligent storage tiering and simplified table replication across AWS Regions and accounts.

New capabilities help optimize application performance, analyze unlimited prefixes, and simplify metrics analysis through S3 Tables integration.

Build and optimize large-scale vector databases up to 10 times faster and at a quarter of the cost with new GPU acceleration and auto-optimization capabilities that automatically balance search quality, speed, and resource usage.

Simplify AI experimentation with zero-infrastructure MLflow that launches in minutes, scales automatically, and seamlessly integrates with SageMaker’s model customization and pipeline capabilities.

Access FSx for NetApp ONTAP file data through S3 to enable AI/ML workloads and analytics—letting you use enterprise file data with Bedrock, SageMaker, and analytics services while it remains in your file system.

Train ML models on sensitive collaborative data by generating synthetic datasets that preserve statistical patterns while protecting individual privacy through configurable noise levels and protection against re-identification.