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More than 300,000 globally connected Scania vehicles, trucks and buses, are continuously submitting their GPS positions. In this presentation we will show how Scania analyses these positions to obtain valuable information about the operation of the vehicles. The algorithms have been developed in a research project, FUMA, that is run as a joint venture between Fraunhofer Chalmers Centre and Scania. In the project we build a continuous delivery pipeline that enables us to iteratively improve our code, our algorithms and the data deliverables. The pipeline runs on a Hortonworks platform using Apache Spark Streaming. In the build pipeline we use Jenkins, Nexus and Ansible to test, deploy and run Apache Spark Streaming jobs and the results are pushed to Apache Kafka. We will highlight and present some of the steps we have taken in order to put a streaming big data application in production at a manufacturing company. We think that people with a general awareness of the challenges with big data, the possibilities of the streaming paradigm and the need for continuous delivery will find this talk very intriguing. In this presentation you will learn how we develop and run the code and how we ensure that we are creating value for Scania.