The Seven Wonders of AWS re:Invent 2024

1. SageMaker Unified Studio

The biggest wonder of all is the re-designed and re-architected SageMaker to be not just for AI but for a convergence of data, analytics and GenAI. The old SageMaker for AI is now called appropriately ‘SageMaker AI’. The new SageMaker Unified Studio is a task-oriented tool for my data projects with an end-to-end workflow that includes:

Amazon Bedrock IDE

Amazon SageMaker AI

Integration with AWS Data services

Amazon SageMaker Lakehouse

Announcing the preview of Amazon SageMaker Unified Studio

3. Amazon Q Developer

Now an end-to-end tool for building AWS solutions. Code reviews, documentation & testing. Bootstrap new projects with a single prompt, generate unit tests with a single prompt, create enhanced documentation with a single prompt, create code reviews with a single prompt to detect and resolve security and quality issues. This end-to-end workflow is throughout SageMaker Unified Studio as an assistant with a free tier included.

New Amazon Q Developer agent capabilities include generating documentation, code reviews, and unit tests

5. Amazon Connect

When I need a Cloud Contact Center, I want one that innovates the customer experience. Amazon Connect has all the bells and whistles that become essential features: personalization, automatic recommendations, tracking custom issues with multiple interactions, etc. With AWS Contact Lens I can get advanced AI and ML capabilities in the customer experience. It now has better, more streamlines agents and omnichanell WhatsApp business messaging.

Newly enhanced Amazon Connect adds generative AI, WhatsApp Business, and secure data collection

7. S3 Tables and S3 Queryable Object Data

S3 Tables are in Apache Iceberg format, a popular way to handle files in parquet format. Compared to creating your own tables, it’s three times faster for queries and ten times faster for transactions. I’ll use it for daily purchase transactions, streaming sensor data, ad impression, etc.

There can be so many object piling up in S3 that object metadata becomes vitally important. I may want to quickly find data for analytics, data processing or my AI training workloads. When stored in S3 tables, I’ll get automatic generation of metadata with over 20 elements. There’s a new Metadata tab in the Amazon S3 console.

New Amazon S3 Tables: Storage optimized for analytics workloads

And those were the Seven Wonders of AWS re:Invent 2024. Many of them were about AI and even if they weren’t they certainly will have AI behind the scenes in some way. Let the AI revolution continue and we’ll see what wonders we ourselves can create when exploring the new tools at our disposal. These are tech wonders that enable us to create our own.