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William Benton

Red Hat

Michael McCune

Red Hat

Adding intelligence to stream-processing applications

Stream procesing

Description

For many applications, it’s not enough to be able to process big data at rest; you also need to be able to process streams of data in motion. In this workshop, you’ll learn how to use open-source tools and frameworks including Apache Spark, Apache Kafka, and radanalytics.io to develop and deploy intelligent event-processing applications in containers on Kubernetes. We’ll start by explaining some of the concepts behind stream processing and streaming algorithms. We’ll show you how to develop a basic stream-processing application and refine it by adding scalable summarization and query processing, anomaly detection, and natural language processing. Finally, we’ll show how to incorporate pretrained models to add computer vision capabilities. The entire workshop will be hands-on: we’ll use Jupyter notebooks to learn and experiment with techniques and OpenShift Origin to provide a great application development experience on Kubernetes.

All of our workshop materials and dependencies are open-source, so attendees will be able to revisit the work we do in the workshop on their own time, whether using laptops or datacenters. There are no prerequisites for this workshop beyond basic familiarity with Python.

Requirements

·A laptop with a web browser
·A GitHub account and text editor will be helpful but not necessary.

Nature of the training

Learn to build intelligent streaming applications from the ground up with Apache Kafka, Apache Spark, and Kubernetes.

Certificate

Big Data Spain will issue the certificate for this course to prove subject matter competency

Audience

Application developers, data engineers and data scientists

Bio of the instructor - William Benton

William Benton leads a team of data scientists and engineers at Red Hat, where he has applied analytic techniques to problems ranging from forecasting cloud infrastructure costs to designing better cycling workouts. His current focus is investigating the best ways to build and deploy intelligent applications in cloud-native environments, but he has also conducted research and development in the areas of static program analysis, managed language runtimes, logic databases, cluster configuration management, and music technology.

Bio of the instructor - Michael McCune

Michael McCune is a software developer in Red Hat's emerging technology group. He is an active contributor to several radanalytics.io projects, as well as being a core reviewer for the OpenStack API Working Group. Since joining Red Hat three years ago, he has been developing and deploying applications for cloud platforms. Prior to his career at Red Hat, Michael developed Linux based software for embedded global positioning systems.