We are on a journey here to operationalise machine learning using Kubernetes. Call it MLOps, AIOPs, DataOps, DevOps, as you will. Next stop is to lay the foundation for implementing CI/CD pipelines to move our assets safely through development, canary testing and production environments. Let’s show that here by laying out a build/tag/promote cycle with […]
As a Data Scientist, I want to work on an RStudio Server image managed by Kubernetes with GPU capability. The motivation for doing this is that I can then access a machine learning rig that is 1) scale invariant (same from desktop to Cloud), 2) leverages Kubernetes for scheduling and 3) taps me into the […]
Kubernetes scheduling a pod to a node with GPU resources to run a Jupyter notebook container demonstrating a python/tensorflow-gpu based application. All from a local Intel NUC machine using an eGPU. Yeah, we can do that. In this blog we take the NUC with eGPU – a Big Little ML Rig which we built earlier to the […]
Everyone’s talking about Istio. Let’s mess around with Kubernetes’ Minikube to show off Istio and see what all the fuss is about. We will do this by reworking the OpenShift MiniLabs A/B Deployment example to work with Istio. Once completed invoking a URL such as http://192.168.86.66:31329 will alternate between the A/B versions of the application.
Let’s mess around with Kubernetes’ Minikube and learn how to use it to launch an application with an ingress point, external configuration and volume claims. We will do this by reproducing a bunch of OpenShift MiniLabs and hack around with a bunch of kubectl commands and Kubernete’s yaml resource files in the process. Now for a […]