What We Learned at AWS re:Invent 2019

A Candid look at key announcements, product launches, and takeaways from another jam-packed week with the cloud computing giant out in Las Vegas 

re:Invent wrapped up yet another busy week and here are our favorite launches out of the vast amount of announcements made throughout the event. 

Bright and early on a colder than usual day in Vegas, Andy Jassy, CEO of AWS took the main stage and what we heard was not about technology but instead, focused on leadership, innovation and the components of digital transformation. 

This year marks the 8th annual event coming to Vegas and with that Andy spoke to its namesake. Re:Invent was born out of the result of the rate of invention among its users. A simple question started the session off strong and left you to ponder exactly how should we think about transforming ourselves? How can we re:Invent our businesses and our customer’s experiences so we can be meaningful and sustainable over a long period of time?

Re:Invent never ceases to provide compelling keynotes, discussions, and sessions and this year was no different.  Enterprise adoption of the cloud opportunity is only getting started and they need all the help they can get, including prescriptive advice on how to successfully navigate this limitless environment. We are excited to share how Matter compliance paired with reusable architectural patterns is prepared to be that guide. Matter on AWS Marketplace

Our Takeaways
AWS Outposts 

Enterprise adoption of the public cloud is in its infant stage with Jassy calling out that of the $3.7T IT market, 97% remains on-prem. “Some customers have certain workloads that will likely need to remain on-premises for several years, such as applications that are latency-sensitive and need to be in close proximity to on-premises assets,” Amazon stated. 

AWS Outposts is a fully managed service that provides customers with AWS designed hardware that allows them to run compute and storage on-prem while still utilizing the cloud services. With AWS Outposts you can run Amazon EC2, Amazon EBS, Amazon Elastic Container Service (ECS), Amazon Elastic Kubernetes Service (EKS) and Amazon Relational Database Service (RDS), Amazon S3 will be made available in 2020. 

The idea is that customers are able to utilize the same AWS infrastructure, services, API’s and tools to build and run applications on-prem and in the cloud to provide a consistent hybrid experience across both environments. Just like in the cloud, all services are managed, monitored and updated by AWS. 

Candid Helps to Support AWS Outposts

AWS Sagemaker Autopilot

On Tuesday AWS announced SageMaker Autopilot, a new tool for SageMaker ML platform that automates the machine learning modeling. This includes tasks like data preprocessing, training parameters and classification. 

SageMaker is Amazon’s service for ML. By using this service within the SageMaker Studio IDE  organizations are able to integrate various tools like SageMaker Augmented AI, SageMaker Model Tuning for automated optimization and now, SageMaker Autopilot for automating the building and training process for machine learning modules. 

As for how it works, AWS emphasized that Autopilot allows inspection of what’s happening underneath, unlike with a black box set of other tools. Amazon also shared the following on its capabilities. 

“SageMaker Autopilot first inspects your data set and runs a number of candidates to figure out the optimal combination of data preprocessing steps, machine learning algorithms, and hyperparameters. Then, it uses this combination to train an Inference Pipeline, which you can easily deploy either on a real-time endpoint or for batch processing. As usual with Amazon SageMaker, all of this takes place on fully-managed infrastructure.

Last but not least, SageMaker Autopilot also generates Python code showing you exactly how data was preprocessed: not only can you understand what SageMaker Autopilot did, you can also reuse that code for further manual tuning if you're so inclined.”

AWS Contact Lens

Contact centers can sometimes be the only personal interaction a customer gets with an organization and these conversations have a profound effect on customer satisfaction, trust, and loyalty. There are millions of hours of recorded calls that contain valuable information and feedback but given the volume, some organizations are unable to or struggle with the task of extracting and analyzing the collected information. 

Those that are able to analyze this data do so by using existing contact center analytics services which tend to be expensive, slow and lack the ability to give accurate call transcriptions. All of which makes it difficult to quickly detect customer experience and provide useful feedback. These existing solutions are also unable to provide real-time analytics on in-progress calls, which prevents identifying and helping customers that are becoming frustrated with their experience. 

AWS Contact Lens makes it possible for organizations to understand the feedback they’re receiving by giving their users access to fully managed machine learning capabilities that are all available with AWS Connect and don’t require coding or ML experience. Contact Lens’ highly accurate speech transcription technology transcribes a customers call, then automatically indexes it with chat transcription so the conversation can be searched within the Amazon Connect console. 

Final Thoughts 

During this year’s event, we had the chance to learn about the innovation our cloud computing peers are implementing to solve big problems with simple solutions. We spoke with some of the largest and fastest-moving organizations in the world and we came out the other end eager to get a jump on 2020 by answering Jassy’s question ourselves and to our clients. 

How should we think about transforming ourselves?

Through integrity, culture, leadership, intelligence, and experience Candid provides actions over advice by making it easier for organizations to build and manage their applications in the cloud.