Infrastructure Agnostic Machine Learning Workload Deployment
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment.
Connect with us:
Website: https://databricks.com
Facebook: / databricksinc
Twitter: / databricks
LinkedIn: / databricks
Instagram: / databricksinc Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-nam...
Смотрите видео Infrastructure Agnostic Machine Learning Workload Deployment онлайн без регистрации, длительностью часов минут секунд в хорошем качестве. Это видео добавил пользователь Databricks 12 Июль 2021, не забудьте поделиться им ссылкой с друзьями и знакомыми, на нашем сайте его посмотрели 39 раз и оно понравилось 1 людям.