Roni Kobrosly
Roni is a former academic epidemiology researcher who has spent a decade employing causal modeling around the population-level effects of harmful environmental exposures. Since leaving the academic world, he's been loving his second life in the tech industry as a data scientist, and is currently Director of Data Science at Capital One. He loves contributing in the open-source community, mentoring junior data folks, and explaining the magic of data analysis and modeling to non-technical audiences.
Sessions
The ability to quickly identify and resolve breakages among interconnected microservices is critical for any tech organization running production software. Unfortunately, in most organizations, identifying the root cause of a breakage can take engineers hours of manually sifting through logs and dashboards. In this talk, we’ll describe a fast, automated, and holistic approach to root cause analysis via an ensemble of structural causal models. This talk should be relevant to anyone interested in causal modeling, the field of observability, reliability engineering, or anyone wanting to troubleshoot production software issues faster.