Tutorials
Get started with Kubeflow and Rok. Skill up with step by step tutorials designed to help you do more in less time.
Tutorial 3: Build an ML pipeline with hyperparameter tuning and serve the model starting from a notebook
Tutorial 2: Build An End-to-End ML Workflow: From Notebook to HP Tuning to Kubeflow Pipelines with Kale
In this tutorial, we will use Kale to unify the workflow across the above components, and present a seamless process to create ML pipelines for HP tuning, starting from your Jupyter Notebook. We will use Kale to convert a Jupyter Notebook to a Kubeflow Pipeline without any modification to the original Python code. Pipeline definition and deployment is achieved via an intuitive GUI, provided by Kale’s JupyterLab extension.
Tutorial 1: An End-to-End ML Workflow: From Notebook to Kubeflow Pipelines with MiniKF & Kale
Kubeflow is the de facto standard for running Machine Learning workflows on Kubernetes. Jupyter Notebook is a very popular tool that data scientists use every day to write their ML code, experiment, and visualize the results. However, when it comes to converting a Notebook to a Kubeflow Pipeline, data scientists struggle a lot.
Legacy: An end-to-end ML pipeline on-prem: Notebooks & Kubeflow Pipelines on the new MiniKF
Update (August 14, 2020): This tutorial has been updated to showcase the Taxi Cab end-to-end example using the new MiniKF (v20200812.0.0) Today, at Kubecon Europe 2019, Arrikto announced the release of the new MiniKF, which features Kubeflow v0.5. The...
Run Apache Cassandra on Kubernetes 15x Faster with Arrikto and DataStax
Response times for applications impact revenue and customer satisfaction, and are therefore mission critical. Whether your application is user facing, performing computational analysis, or providing integration between services no one wants to wait any longer than...
Why your Cassandra needs local NVMe and Rok
Do you run a NoSQL database, like Cassandra or MongoDB, on the cloud or on-prem and it is terribly slow? Probably, you are already paying a lot of money for the infrastructure, and slow is definitely something you don’t need. Cassandra is a very popular NoSQL...
Data management for hybrid/multi-cloud Kubernetes
Kubernetes simplifies the way people build and deploy scalable, distributed applications on-prem and on the cloud. Moreover, when your apps run inside containers it doesn’t really matter whether they run on a public cloud, or on-prem bare metal machines. It is exactly...
Disk = Volume = Snapshot = Image
Welcome to a world of Fisks Trying to build independent Data Services with a top-down approach, starting from the platform and moving towards Storage, presents us with a great challenge. There seems to be a strong coupling between the resources known to and handled by...
The Future of Storage != Storage
As highlighted in a previous post: One needs to stop thinking about Storage, to solve a Data problem. But how is this even possible? Data problems are solved by software implementing Data Services, and until now Data Services have been tightly coupled with Storage...
Storing everything, without storing anything
The value in Delivering, not Persisting Over the last decade, we have been experiencing an emergence of new technologies which resulted in dramatic changes in how IT infrastructure is managed, and a true revolution in the way production and development environments...