Dipen Chawla, Episource LLC
This talk is a synopsis of how we built a self-serving workbench for the team of data scientists at Episource and designed it to be scalable, secure, and cost-efficient. The talk will also include the challenges we faced while navigating the architecture, the lessons learned, and the impact the workbench has had on Episource's ML dev workflows. If you are an organization looking to improve autonomy and promote rapid experimentation within your data science ranks, this talk will help you in your journey.
Dipen Chawla, Episource
Dipen is a member of the MLOps and Engineering team at Episource, where he works on the deployment of scalable and secure architectures to the cloud. His primary areas of interest include container tech and ML in production.
SREcon21 Open Access Sponsored by Indeed
author = {Dipen Chawla},
title = {Designing an Autonomous Workbench for Data Science on {AWS}},
year = {2021},
publisher = {USENIX Association},
month = oct
}
