DRAFT.md

Exposing Red Hat Mobile Services in OpenShift through the Service Catalog

with John Matthews (Ansible Service Broker)

Mobile application development and continuous iteration and deployment have fueled the need to rethink software architecture, technologies, development methodologies, roles, and responsibilities in order to achieve success.

By leveraging the OpenShift Service Catalog and OpenShift Ansible Broker, the Red Hat Mobile team has been able to bring Mobile Backend-as-a-Service (MBaaS) closer to the OpenShift Mobile application developer.

In this session, we will show how the Red Hat Mobile team was able to take advantage of this technology to easily make these services available on OpenShift. Attendees will learn how the OpenShift Ansible Broker and Ansible Automation were used to orchestrate the provisioning of these services including a deep dive on the application definition constructs used to expose these services to the Service Catalog. After this session, the attendee will have a good high level understand of how to create and expose their own services to the OpenShift Service Catalog.

Delivering Mobile Push Notifications with Apache Kafka (on Openshift)

Apache Kafka is becoming more an more an interesting option for messaging of could enabled application. Kafka promises great performance and throughput due to its unique architecture, which fits well on Openshift's elastic scalablitly model. After a short introduction to Apache Kafka, the session gives insights on the revamp of the AeroGear Unified Push Server (UPS), a classic Java EE application, for delivering mobile push notifications. The UPS was rewritten to leverage Apache Kafka running on Openshift. You will learn how to use Apache Kafka's API from a standardized Java EE environment, to build scalable systems. The session demonstrates the approach that was taken for the UPS to deliver Push Notifications as well processing mobile metrics for further analytic use-cases.

BOF: Let's talk about stream processing (, baby!)

with Marius Bogoevici (Data Streaming Lead)

Stream processing and big data analytics are a very important aspect of many modern cloud based services. Lot's of frameworks and toolkits exist for that. In this BOF session we want to share stories about stream processing and big data analytics, whether it is based on Apache Kafka, Apache Spark, Apache Flink or even Apache Hadoop! We will discuss the pros and cons of different libraries, such as Apache Kafka Streams API versus Apache Spark distributed jobs. Besides the actual frameworks we also want to cover the application aspect for consuming the results, be it Spring Boot, Eclipse Vert.x, WildFly Swarm or Node.js as the solution of choice for your backend! Join us and discuss stories from the trenches of stream processing and big data analytics! It will be fun!

Break-out session

Or Scaling Mobile Push Notifications

"After a short introduction to Apache Kafka, the session gives insights on the revamp of the AeroGear Unified Push Server (UPS), a classic Java EE application, for delivering mobile push notifications" -> Maybe throwing in something like Wildfly/microservices would help?

"After a short introduction to Apache Kafka, the session gives insights on the revamp of the AeroGear Unified Push Server (UPS), a classic Java EE application, for delivering mobile push notifications" -> Maybe throwing in something like Wildfly/microservices would help?

@mbogoevici good idea :-) the more buzz, the better

"We'll also discuss the role of in-memory data grids, such as Red Hat JBoss Data Grid, which are a very userful tool from a streaming analysis point of view since our goal is to be able to take action on the data in real-time, when an event occurs. To be able to make this type of decision we need the current and recent data to be accessible in real-time, we need it in-memory."