Category: Analytics

Twenty years ago this past week, Amazon S3 launched publicly on March 14, 2006. While Amazon Simple Storage Service is often considered the foundational storage service that defined cloud infrastructure, what began as a simple object storage service has grown into something far larger in scope and scale. As of March 2026, S3 stores more […]

Fiti AWS Student Community Kenya! Last week was an incredible whirlwind: a round of meetups, hands-on workshops, and career discussions across Kenya that culminated with the AWS Student Community Day at Meru University of Science and Technology, with keynotes from my colleagues Veliswa and Tiffany, and sessions on everything from GitOps to cloud-native engineering, and […]

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.