Introducing Kubeflow as a Service Giving Data Scientists Instant Access to a Complete MLOps Platform

We’re excited to announce the availability of our new Kubeflow as a Service offering! The goal of the service is to significantly accelerate the development and scaling of machine learning models while eliminating infrastructure complexities. This on-demand MLOps platform turns complex machine learning workloads on Kubernetes into a simple point-and-click operation. This means that data scientists can now gain access to a complete MLOps platform, in just minutes.

Most machine learning projects don’t deliver on their promised ROI and about half fail before they even make it to production. Why? Machine learning workflows require specialized, technical skills and complex software to manage the underlying infrastructure, data, model training, hyperparameter tuning, metadata tracking, serving and security needs of the workload. As a result, data scientists are often asked to become DevOps experts in order to move models into production, and vice versa. 



Arrikto’s Kubeflow as a Service abstracts away the complexity of running an MLOps platform on Kubernetes. This allows data scientists and DevOps teams to work from a common toolset, reduce development times, streamline technical collaboration, and harness the power of Kubernetes to scale models from the local laptop to a global GPU-powered cluster.

We’ve made it easy to get started with Kubeflow. Have a look!



FREE 14-day trial, no credit card required

No need to worry about dealing with IT or paying for instances while you experiment with Kubeflow. Sign up and start developing and serving models right away. Need more time or more resources to work through our tutorials or to develop your own models? Just let us know through your KFaaS dashboard and we can extend your trial.


Zero-touch deployment process

You only need to click a button and wait ~20 mins for your Kubeflow cluster to be up and running. Behind the scenes we’ll perform all the required software configurations for you.


Deploy a Kubeflow Pipeline in 5 minutes

Our quickstart guides you through the deployment of a Notebook Server, downloading the necessary notebook, files and data, plus running a Kaggle competition-based Kubeflow Pipeline, all in under 5 mins!

Plenty of development resources

Signing up gets you a dedicated VM running a Kubeflow cluster with the following specifications:

  • 16 CPUs
  • 60 GB RAM
  • 700 GB disk space

You can create up to 3 clusters during your FREE trial.


Let’s do this!

What are you waiting for? Developing, training and serving machine learning models with Kubeflow has never been easier, click to sign up.


Free Technical Workshop

Turbocharge your team’s Kubeflow and MLOps skills with a free workshop.