Yesterday I had the chance to attend AWS summit London with some of my colleagues at Zava.

We have become more of an aws shop recently, after moving the majority of our infrastructure to the cloud.

Besides attending the sessions, and touring around to check the booths, and enjoy the freebies AWS gives for the certified engineers. I have also shot for the ML workshop as I did back in December in the AWS builders day 2018.

The first session was titled "IOT and Alexa in connected homes"

The interesting part for me in it was how you can use Alexa to interact with your users to extract specific information that you can use in your workflow, like order placement, or online help.

They also showcased a study about how Lancaster university implemented a voice-enabled service for the students in 120 days with awesome features.

Some slides documenting their journey can be found here Using Voice Technology to Enhance the Student Experience

The second session was titled "Build data driven high performance internet-scale applications with aws databases" It was database architecture strategies and best practices for building high-performance and internet-scale applications using Amazon DynamoDB, Amazon Timestream, and Amazon ElastiCache.

They also showcased how the Guardian moved away from MongoDB after more than one production downtime, to RDS PostgresSQL

The third session I attended was "Modern application architecture"

That one was purely a marketing session showing more AWS tools, and motivations to use them in your architecture. they also showcased how they implemented many tools with Sage, specifically the CI/CD process.

After the sessions, I attended the "Using AI/ML to Personalize your Recommendations" workshop for about 2 hours, which wasn't enough to train all the models and create all the solutions campaigns.

I got to use the AWS personalize which is still in a preview, and I see how much manual work it saved when I did similar examples back in December.

You can find the full workshop guide here Personalize your Recommendations lab

But you can't implement it until the service becomes generally available.

At night, I checked the status for the training/campaigns creation and was happy that it worked without unexpected issues.

You can see a demo of the app we built here a Realtime personalization example

All the AWS summit 2019 slides are available at this link AWS Summit 2019 slides