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Muvr is a real-time personal trainer system. It must be highly available, resilient and responsive, and so it relies on heavily on Spark, Mesos, Akka, Cassandra, and Kafka—the quintuple also known as the SMACK stack. In this talk, we are going to explore the architecture of the entire muvr system, exploring, in particular, the challenges of ingesting very large volume of data, applying trained models on the data to provide real-time advice to our users, and training & evaluating new models using the collected data. We will specifically emphasize on how we have used Cassandra for consuming lots of fast incoming biometric data from devices and sensors, and how to securely access the big data sets from Cassandra in Spark to compute the models.
We will finish by showing the mechanics of deploying such a distributed application. You will get a clear understanding of how Mesos, Marathon, in conjunction with Docker, is used to build an immutable infrastructure that allows us to provide reliable service to our users and a great environment for our engineers.