Ryan Jarvinen outlines the processes, tools, and techniques that Red Hat is adopting in order to help improve security for building, running, and maintaining container images. Ryan covers topics such as OpenShift templates and Source-to-Image builds and includes a workflow demonstration showing how operations teams can distribute security patches throughout a Kubernetes cluster.

AWS, Azure, and GCP all provision clusters differently. Docker, Kubernetes, and Mesos are seeking to simplify that process but haven't fully delivered on that promise. Ben Lackey and Boris Baryshnikov explain the best way to provision with the tools available today as we wait for the perfect orchestration layer to arrive.

Chad Bailey demonstrates how to put the combination of static and dynamic data to work in your own apps.

There is much more to Docker than just deploying your flagship application. Carolyn VanSlyck, Ash Wilson, and Nick Silkey look at three use cases for Docker that go beyond the typical software development pipeline. You'll leave knowing how you can use Docker on the side, even if you haven't tackled Dockerizing your application.

Artifactorys use of hybrid storage has clear benefits, but what are the drawbacks? Fred Simon describes Artifactorys journey to find harmony between ACID and CAP. Fred reviews the challenges in building a reliable and atomic system on top of eventually consistent storage and explains how Artifactory solved them for both standalone and clustered architectures.

In this full-day tutorial, participants will get an overview of all aspects of successfully managing Hadoop clustersfrom installation to configuration management, service monitoring, troubleshooting, and support integrationwith an emphasis on production systems.

Spark has been growing in deployments for the past year. Neelesh Srinivas Salian explores common issues observed in a cluster environment setup with Apache Spark and offers guidelines to help setup a real-world environment when planning an Apache Spark deployment in a cluster. Attendees can use these observations to improve the usability and supportability of Apache Spark in their projects.

Jayant Shekhar, Amandeep Khurana, Krishna Sankar, and Vartika Singh guide participants through techniques for building machine-learning apps using Spark MLlib and Spark ML and demonstrate the principles of graph processing with Spark GraphX.

Moty Fania shares Intels IT experience implementing an on-premises big data IoT platform for internal use cases. This unique platform was built on top of several open source technologies and enables highly scalable stream analytics with a stack of algorithms such as multisensor change detection, anomaly detection, and more.

Martin Yip and Justin Murray explore the benefits of virtualization of Hadoop on vSphere and delve into three different examples of real-world deploymentsat small, medium, and large scalesto demonstrate how enterprises are currently deploying Hadoop differently on virtual machines.

Benedikt Koehler offers approaches to analyzing and visualizing bitcoin dataaccessing and downloading the blockchain, transforming the data into a networked data format, identifying hubs and clusters, and visualizing the results as dynamic network graphsso that typical patterns and anomalies can quickly be identified.

It's one thing to create a sample RESTful API using Node.js, but it's quite another to horizontally scale your architecture to hundreds of thousands of concurrent connections while trying to ensure redundancy and high availability. Volkan zelik shows what it takes to create real-life, scalable, highly available, and highly responsive Node.js applications.

The ability to visualize millions of data points opens up a world of applications. But its hard to quickly render that much data, let alone compute anything with it. Thibaud Hottelier shares the GPU technologya hybrid client/server GPU engine using Node-OpenCL and a new library, CL.jsthat Graphistry used to break the million datapoint barrier for fast, interactive visualizations.