This is a guest post by Stephen Carrad, Vice President at JP Morgan Chase & Co.
JPMorgan & Chase Co. started its cloud journey four years ago, building the integrations required to deploy cloud-native applications into the cloud in a resilient and secure manner. In the first year, three applications tentatively dipped their toes into the cloud, and today, we have an ambitious cloud-first agenda.
Operating in the cloud requires a change in culture and a fundamental reeducation towards a new normal. An on-premises server is like your car: you own it, power it, maintain it, and upgrade it. In the cloud, a server is like a rideshare: you press a few buttons, the car appears, you use it for a certain time, and when you’ve finished with it you walk away and someone else uses it. To adapt to a cloud first agenda, our engineers are learning a new operating model, new tools, and new processes.
JPMorgan Chase’s AWS DeepRacer learning program was born in Chicago in 2019. A child of the Chicago Innovation team led, it’s designed to upskill our employees in an enjoyable way by allowing them to compete internally with their local peer groups, globally against other cities, and externally against other firms, universities, and individuals. We started with physical tracks in Chicago and London, and now have tracks in most of our 20+ technology centers around the globe and several racers participating in the DeepRacer Championship Cup at AWS re:Invent.
It started small, but immediately provided value and, more importantly, entertainment to the participants of the program. People who had never used the AWS Management Console before logged on and learned how it worked, played with AWS DeepRacer, and started to write code and learn about reinforcement learning. They also started to collaborate with one another—someone would have an idea to reduce costs or provide visualization of the log analysis, and other people would partner with them to build new tools. It grew beyond teaching people about AWS products and machine learning to people across the world collaborating, building tools, and creating quizzes. We also have the JPMorgan Chase International Speedway, developed in Tampa, where we host our companywide annual finals.
Our AWS DeepRacer learning program now runs in 20 cities and 3,500 people have participated over the past two years. They have gained knowledge of the AWS console, Python, Amazon SageMaker, Jupyter notebooks, and reinforcement learning. Our biggest success is watching people change roles due to their participation.
We recently introduced the AWS DeepRacer Driving License, so hiring managers can see that applicants have attained a recognized standard. It includes a training curriculum that people can follow that enables them to both be knowledgeable and competitive. They also need to attain a certain lap time to prove they have been able to apply the knowledge they have gained.
JPMorgan Chase is now a cloud first organization. With the excitement and interest in the Drivers License, application teams have started to look towards the cloud and have found they are more likely to have technologists in their team with AWS skills. These individuals have then been able to apply their new skills in their day-to-day work.
In 2021, more than 80,000 participants from over 150 countries participated in AWS DeepRacer. As a testament to the work our employees have done with AWS DeepRacer, seven of the 40 racers in AWS’s global championships were JPMorgan Chase technologists. When the dust had settled, our employees topped the podium with first, second, and seventh place finishes. This was a huge achievement against some excellent competitors, and I apologize to anyone sitting near us in the arena at AWS re:Invent for all the shouting and screams of excitement.
This year’s entry to the AWS Championship finals can be achieved by racing on either virtual or physical tracks. We’re looking to get our tracks out and invite our competitors to come and learn, share ideas, enjoy pizza and practice on our tracks. We have also open-sourced two tools that we have created:
DeepRacer on the Spot – This tool placed third in our Annual Hackathon in Houston. It allows teams to train models on Amazon Elastic Compute Cloud (Amazon EC2) instances using Spot pricing, which can be up to 90% cheaper than training on the console.
Guru – Developed by one of our participants in London, this log analysis tool provides visualization of what the car is doing on the track at any point and how it is being rewarded.
Racing this year is going to be particularly interesting we continue to expand our presence with top racers. Yousef, Roger, and Tyler will be trying to knock Sairam off the podium, and a couple of groups of MDs are forming their own teams—look out for Managing Directions! I would say that my money is on our graduate talent, but that might be career limiting. We look forward to collaborating with our fellow racers on the tools we are releasing and invite you to race on our tracks.
AWS DeepRacer is at the forefront of making us a cloud-ready organization. To learn more about how you can drive collaboration and ML learning like JPMorgan Chase with AWS DeepRacer, join my session on Wednesday, November 30th at 2:30 PM.
About the author
Stephen Carrad is a DevOps Manager at JPMorgan Chase. He also leads the JPMorgan Chase DeepRacer Learning Program to grow his team building skills and support the firm’s widespread public cloud adoption. Outside of work, Stephen enjoys trying to keep up with his teenage children whilst skiing or cycling and coaching his local under-16 rugby team.
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