AWS re:Invent 2024 Day 3 Recap

In case you missed it, here's a quick recap of Day 1 & Day 2 at AWS re:Invent 2024!

I’ve pulled together some of the key highlights and announcements from those days.

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Highlights from Day 3

Amazon SageMaker AI Innovations: Some exciting updates for SageMaker are reimagining how we build and scale generative AI and machine learning models.

S3 Automatic Metadata Generation: S3 will now automatically generate metadata when objects are captured.

This feature is in preview, and the data will be stored in managed Apache Iceberg tables, making it easier to handle workloads and share data with services like Bedrock.

Amazon S3 Tables: A new storage option designed specifically for tabular data—think daily transactions, sensor data, and more.

Aurora DSQL: AWS has revamped its database engine with Aurora DSQL, the fastest distributed SQL database around. It’s built for super-low-latency reads and writes and is Postgres-compatible.

DynamoDB Global Tables: DynamoDB is also getting global tables with low-latency capabilities across regions, making it even more powerful.

Some talks I attended and found interesting:

Best practices for end-to-end digital experience monitoring

Imaya and Bobby shared some valuable tips on best practices for end-to-end digital experience monitoring, showing how to get full-stack visibility into app performance, from the internet all the way to your services.

They explained how AWS digital experience monitoring combines network monitoring, user experience tracking, and backend metrics to provide a complete view of your app's performance.

Enhancing observability in Amazon ECS to gain actionable insights

Steven and Lucy walked us through how to boost observability in Amazon ECS using AWS tools. They showed how services like Amazon CloudWatch Container Insights, AWS X-Ray, and myApplications can provide actionable insights into your ECS environments.

They also shared some practical examples of how to use these AWS services to troubleshoot, optimize performance, and get a better grip on how your containerized applications are running.

[NEW LAUNCH] Investigate operational issues faster with AI

Jared, Ania, and Wei introduced a great new way to troubleshoot operational issues faster with AI.

They showed how Amazon Q acts like an extra teammate, analyzing your AWS setup and observability data to help pinpoint potential issues. Once the root cause is identified, Amazon Q provides personalized suggestions for fixing the problem, using AWS's curated runbooks.

Definitely check out the session when it’s available!

The journey and challenges of operationalizing generative AI at FINRA

Leah, Kym, and Daniel walked us through FINRA's journey of integrating generative AI into their operations. They shared the challenges they've faced and gave us a peek into their pilot programs, like the developer assistant built on Amazon Q. 

If you're curious about how they manage over an exabyte of data and use advanced analytics and cloud operations, definitely check it out! 

Do meet me at Booth #166 if you haven’t yet.

At Last9, we give you the freedom and flexibility you need with our OTel-native approach—no vendor lock-in, no high costs, just open standards that let you adapt your observability setup as the OTel ecosystem evolves.

Day 3 was packed with fun and interesting AWS announcements and definitely some great discussions with the observability community. 

The excitement is growing, and I can't wait to see what tomorrow holds!