ML Workshop 1: A New Architecture for Machine Learning Logistics


Ted Dunning PhD

Chief Application Architect, MapR Technologies

Having heard the high-level rationale for the rendezvous architecture in the introduction to this series, we will now dig in deeper to talk about how and why the pieces fit together. In terms of components, we will cover why streams work, why they need to be persistent, performant and pervasive in a microservices design and how they provide isolation between components. From there, we will talk about some of the details of the implementation of a rendezvous architecture including discussion of when the architecture is applicable, key components of message content and how failures and upgrades are handled. We will touch on the monitoring requirements for a rendezvous system but will save the analysis of the recorded data for later.

At the end of the workshop, you should have a clear understanding of the fit and finish between the parts of the rendezvous model and should be able to evaluate its applicability in your situation.