AWS re:Invent 2022: Wednesday’s top takeaways

On Monday, we got exciting news about Lambda cold starts being a thing of the past, and Tuesday came with a ton of announcements. So what did Wednesday have to bring? Here’s all you need to know about what happened on day three of re:Invent 2022!

Today Dr Swami Sivasubramanian — AWS’s Vice President of Database, Analytics, and Machine Learning — took the stage. After CEO Adam Selipsky’s keynote from yesterday, we were on edge to hear about what he had to say!

Dr Sivasubramanian kicked it off by talking about how we need a future-proof data foundation, one that we don’t need to keep re-architecting. He emphasized that without a strategy built for tomorrow, companies will lose their competitive edge, and reiterated we should let AWS “remove the undifferentiated heavy lifting”. His speech also came with a call to weave connective tissue across our organizations, and democratize data with tools and education.

The theme of the keynote was “Data is extremely powerful”, and he carried this idea through his keynote in several poetic ways. In the words of Spiderman, with great power comes great responsibility, and that means security. Let’s sling into the announcements, then.

Feeding into this theme of responsibility were the new SageMaker ML governance features, which help you take the reins with your Machine Learning models.  These include Amazon SageMaker Role Manager, Amazon SageMaker Model Cards, and Amazon SageMaker Model Dashboard.  That’s a lot of “Amazon SageMaker” naming!

All of these are now available today at no additional charge in all the AWS Regions where Amazon SageMaker is available, except for the AWS GovCloud and AWS China Regions.

Speaking of SageMaker, SageMaker Data Wrangler now supports over 40 data sources. It uses data sources for Machine Learning that integrate with AppFlow. That means it’s now easier than ever to aggregate data from over 40 third party SaaS application sources, including Salesforce and Google Analytics, so you better get to wranglin’!

Athena is cool — both the service and the Greek deity — and if you don’t know about the former, you should read Noreen Hasan’s excellent introductory article on the service (If you need to know about the latter, check Wikipedia). Now, you can run Apache Spark workloads using Jupyter Notebook as the Interface. You can perform data processing on Athena, and use Athena APIs to interact with spark applications.

Shifting gears into Zero ETL (that is: extract, transform, load), Amazon Redshift’s new auto-copy from S3 feature will most definitely help move toward that zero ETL that we know AWS is striving to achieve.

Previews are great, and here’s two worth checking out: AWS Glue Data Quality and AWS Verified Access.

AWS Glue Data Quality is a tool that automatically measures and monitors your data lake, analyzing your data and gathering statistics. It then recommends data quality rules, and you can add your own as well.  This can help stop you from polluting your data lake and turning it into a data swamp.

AWS Verified Access is a VPN-less way to secure network access to corporate applications.  This is to enable “Zero Trust” networking—also sometimes called BeyondCorp—and this service seems to be Amazon’s answer to Google’s Identity-Aware Proxy.  

I’m feeling a connection, and that connection is with AppFlow. Amazon AppFlow announced the release of 22 new data connectors, and now AppFlow supports over 50 applications. This allows you to securely transfer data between SaaS applications and Amazon S3 and Redshift. You can now set up data flows for Facebook Ads, Mailchimp, Microsoft Teams, and many more.

Yes, you heard me. This means easy building, training, and deploying machine learning models using geospatial data. It also includes built-in 3D visualization AND neural maps!

Keep tuning in for more news as re:Invent 2022 continues. And as always, Keep Being Awesome, Cloud Gurus!

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