The Binx team attended re:Invent 2019 in Las Vegas. Bart Verlaat, Thijs de Vries and Bas Harenslak (GoDataDriven) took a few moments to share their experiences and main take-aways from Amazon Web Services’s main event of the year.
Embrace Cloud Top-Down
“Fantastic to be part of this with our team. It’s been an amazing week. For me personally, to meet our customers but also the other partners with whom we organized the BeNeLux drinks”, said Verlaat. The Benelux Drinks drew a crowd of a couple of hundreds of attendees.
“For the conference, one of my most important take-aways is from Andy Jassy’s keynote, who emphasizes that it’s not just about technology, make sure that your organization embraces cloud top-down as well.”
As Binx.io, this is exactly what we do for our customers.
Build Better Products More Easily with S3 Access Points, Transit Gateway and AWS Detective
At re:Invent, Amazon Web Services announced several tools that make securing data and access management a lot easier. Also, AWS Detective was announced, a service to do root cause analysis for all kinds of issues.
Thijs de Vries, cloud engineer at Binx.io sees immediate value:
“For me, there are a couple of highlights from the re:Invent. S3 Access points, a way to secure data more easily for different user profiles and data consumers. This is a service we can apply in our customer projects immediately.”
Although Thijs has been using Transit Gateway for a while already, he attended some really good sessions that provided loads of new insights that he can use at many of his projects.
Amazon Detective is a service that provides insights in available data.
“For example, something went wrong and you want to do a root cause analysis. That is already possible, but it takes a lot of effort as you need to use many techniques. With AWS Detective you have the result in just a few clicks”.
Full-Fledge Development Environment for Data Science – Sagemaker Studio
Bas Harenslak, Data Engineer at GoDataDriven, joined the Binx.io team on this conference trip. Bas attended many sessions around the latest services for data science and machine learning. For example, about Sagemaker, which until now was mostly a Jupyter notebook with a Sagemaker layer. With Sagemaker Studio, AWS introduces a full-fledge development environment that combines your data, results and code all in one interface and allows you to keep track of everything.
“For me it was good to see so many developments around AWS Sagemaker. Automated model development is now better facilitated by Sagemaker. But, also tools have been added to develop models yourself, with tools like Experiments and Debugger it becomes a lot easier to keep track of trained models and dive deep into errors and bugs to debug and improve their performance”, Bas explains.