Product Demo: Building Secure ML Runtimes for Cloudera Machine Learning

We have partnered with Cloudera on a joint mission to secure open-source ML runtimes.

Cloudera Machine Learning, Securely Extended

With the ActiveState Platform, you can easily generate ML Runtimes to securely extend your Cloudera Machine Learning (CML) environment with the latest Data Science and Machine Learning tools and frameworks.

How it works

Step one of setting up your cloudera project

Step One

Sign up for a free ActiveState Platform account using your GitHub credentials, create a new Python project and select Linux as the operating system. Add the cloudera-ml-runtime package to your project to ensure your Python runtime is set up properly. Add any additional dependencies you want to bring to CML.

Step Two

Enable the Docker Image deployment option from the Platforms Modal on your project’s configuration tab. Your ML Runtime will be packaged in a CML-compatible docker image before import.

Step Three

Go to the downloads builds tab and follow the instructions to download your docker image and upload the image to your docker registry.

Step Four

Import your docker image into CML to use your new ML Runtime.

At Cloudera and ActiveState, we strongly believe that open source security and innovation can coexist. This joint mission is why we have partnered to bring trusted, open-source ML Runtimes to Cloudera Machine Learning (CML). Unlike other ML platforms, which rely solely on insecure public sources like PyPI or Conda Forge for extensibility, Cloudera customers can now enjoy supply chain security across the entire open source Python ecosystem. CML customers can be confident that their AI projects are secure from concept to deployment by leveraging the ActiveState Platform. Try the Cloudera ML and ActiveState integration today. Contact Sales

Recent Posts

Scroll to Top