Implementing an Automated X-Ray Images Data Pipelines, the Cloud-native Way!


Data is becoming the bread and butter of many organizations, or at least something most couldn't live without. And many applications or solutions, from storage to platforms and middleware, can help support the whole lifecycle of the data throughout its acquisition, transformation, storage, and consumption. In this Lab, you’ll see how you can create a data pipeline that is able to automatically ingest X-Ray chest images, classify them according to the pneumonia risk using AI inferencing, anonymize them, retrain the model using machine learning, and finally automatically redeploy this new model! All of this using various open-source tools like Rook-Ceph, KNative, Kafka, & Grafana.


Guillaume Moutier is a Senior Principal Technical Evangelist at Red Hat, focusing his work on AI/ML workloads and data science platforms. Former CTO of Laval University in Canada, he is constantly looking for and promoting new and innovative solutions, but always with a focus on usability and business alignment brought by 20 years of IT management.