Keynote: Adapting Kubernetes for Machine Learning Workflows - Ania Musial, Senior Software Engineer & Keith Laban, Senior Infrastructure Engineer, Bloomberg The Bloomberg Professional Service (aka "the Terminal") provides data, analytics, news, information and communication to professionals in business, finance, government, and philanthropy. Through our internal machine learning platform, Bloomberg is applying advanced AI and GPU-accelerated compute to dozens of domains such as NLP, computer vision, time-series analysis and personalization. In this talk, we'll discuss how we adapted Kubernetes to support a diverse set of machine learning workloads; how an ecosystem of data connectors enables rich collaboration; how we address multi- tenancy, data security and privacy; and finally, how we support heterogenous compute requirements and hardware acceleration. About Keith Laban Keith Laban is a senior compute infrastructure engineer at Bloomberg. He works on leveraging Kubernetes as the building blocks of a machine learning platform. Keith has given internal talks at Bloomberg about Kubernetes and building custom controllers (operators). Keith has worked on addressing problems such as multi-tenant environments and custom workflows using custom resources. For his last 6 years, Keith has worked on various other infrastructure projects, such as search infrastructure (Solr) and the news backend for bloomberg.com. About Ania Musial Ania Musial is a Senior Software Engineer in the ML Platform team at Bloomberg, focusing on components required for a more robust machine learning model development lifecycle. Previous projects in her 9 year tenure at Bloomberg include building recommendation system infrastructure, development of real-time news applications, and advocacy for developer needs. She has given internal talks ranging from model deployment logistics to showcasing engineering departments for new hire orientation. Resources/links: https://www.linkedin.com/in/aniamusial/
