The life sciences field has rapidly become data rich, but longs to be data driven. At Bayer Crop Science, it’s vital that our company can easily identify, access and utilize the enterprise data sets necessary to enable our vision of “science for a better life”. In this session we present a real-life approach to building an enterprise ready data asset to serve hybrid workloads, both analytical and transactional, powering enterprise applications and data scientists alike within the Crop Science R&D pipeline. We present a case study that pairs principled design using concepts from Google’s Resource Oriented Design guidelines with an array of Google Cloud Platform technologies like Kubernetes and Cloud Spanner to build a platform which has served 3B+ API requests to date in production. We also detail how our approach helps our consumers minimize data time-to-use by presenting humane, domain-centric APIs to our internal enterprise consumers.
Build with Google Cloud → https://bit.ly/2KaULOo
Next ’19 Application Development Sessions here → https://bit.ly/Next19AppDev
Next ‘19 All Sessions playlist → https://bit.ly/Next19AllSessions
Subscribe to the GCP Channel → https://bit.ly/GCloudPlatform
Speaker(s): Jason Clark
Session ID: DEV218
product:Cloud Datastore,Stackdriver,Kubernetes Engine;
Publisher: Google Cloud
You can watch this video also at the source.