I gave a presentation at the Big Data Tech conference in Minneapolis on June 5th 2018. This is the link to my slide deck
These are my key takeaways:
• There is a major shift in web and mobile application architecture from the ‘old-school’ one to a modern ‘micro- services’ architecture based on containers. Kubernetes has been quite successful in managing those containers and running them in distributed computing environments.
• Now enabling Big Data and Machine Learning on Kubernetes will allow IT organizations to standardize on the same Kubernetes infrastructure. This will propel adoption and reduce costs.
• Kubeflow is an open source framework dedicated to making it easy to use the machine learning tool of your choice and deploy your ML applications at scale on Kubernetes. Kubeflow is becoming an industry standard as well!
• Both Kubernetes and Kubeflow will enable IT organizations to focus more effort on applications rather than infrastructure.
What are your thoughts?