Ripped Machine Learning with Distributed Computing
Machine Learning with Distributed Computing are both relatively complex software architectures to wrap your head around. Through the years the solution stack has taken various forms, most of which have been difficult to setup and maintain. Today with the advent of tools like TensorFlow and Kubernetes, we can combine these technologies and stand on the shoulders of giants. Your ML solutions will not just be running, but will also be easier to maintain and observe.
The session will present the fundamentals of how these two work together for a complementary solution stack. We walk through a hand-on demonstration that you can later take and exercise for yourself and show to your peers.
Prerequisite: Be sure to attend Kubernetes Koncepts (at least part 1) as this presentation builds on those ideas.
About Jonathan Johnson
Jonathan Johnson is an independent software architect with a concentration on helping others unpack the riches in the cloud native and Kubernetes ecosystems.
For 30 years Jonathan has been designing useful software to move businesses forward. His career began creating laboratory instrument software and throughout the years, his focus has been moving with industry advances benefitting from Moore’s Law. He was enticed by the advent of object-oriented design and applied it to financial software. As banking moved to the internet, enterprise applications took off and Java exploded onto the scene. Since then, he has inhabited that ecosystem. After a few years, he returned to laboratory software and leveraged Java-based state machines and enterprise services to manage the terabytes of data flowing out of DNA sequencing instruments. As a hands-on architect, he applied the advantages of microservices, containers, and Kubernetes with a laboratory management platform.
Today he enjoys sharing his experience with peers. He provides perspective on ways to modernize application architectures while adhering to the fundamentals of modularity - high cohesion and low coupling.microservices, containers, and Kubernetes to their laboratory management platform.
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