Skip to main content
Redhat Developers  Logo
  • Products

    Platforms

    • Red Hat Enterprise Linux
      Red Hat Enterprise Linux Icon
    • Red Hat AI
      Red Hat AI
    • Red Hat OpenShift
      Openshift icon
    • Red Hat Ansible Automation Platform
      Ansible icon
    • View All Red Hat Products

    Featured

    • Red Hat build of OpenJDK
    • Red Hat Developer Hub
    • Red Hat JBoss Enterprise Application Platform
    • Red Hat OpenShift Dev Spaces
    • Red Hat OpenShift Local
    • Red Hat Developer Sandbox

      Try Red Hat products and technologies without setup or configuration fees for 30 days with this shared Openshift and Kubernetes cluster.
    • Try at no cost
  • Technologies

    Featured

    • AI/ML
      AI/ML Icon
    • Linux
      Linux Icon
    • Kubernetes
      Cloud icon
    • Automation
      Automation Icon showing arrows moving in a circle around a gear
    • View All Technologies
    • Programming Languages & Frameworks

      • Java
      • Python
      • JavaScript
    • System Design & Architecture

      • Red Hat architecture and design patterns
      • Microservices
      • Event-Driven Architecture
      • Databases
    • Developer Productivity

      • Developer productivity
      • Developer Tools
      • GitOps
    • Automated Data Processing

      • AI/ML
      • Data Science
      • Apache Kafka on Kubernetes
    • Platform Engineering

      • DevOps
      • DevSecOps
      • Ansible automation for applications and services
    • Secure Development & Architectures

      • Security
      • Secure coding
  • Learn

    Featured

    • Kubernetes & Cloud Native
      Openshift icon
    • Linux
      Rhel icon
    • Automation
      Ansible cloud icon
    • AI/ML
      AI/ML Icon
    • View All Learning Resources

    E-Books

    • GitOps Cookbook
    • Podman in Action
    • Kubernetes Operators
    • The Path to GitOps
    • View All E-books

    Cheat Sheets

    • Linux Commands
    • Bash Commands
    • Git
    • systemd Commands
    • View All Cheat Sheets

    Documentation

    • Product Documentation
    • API Catalog
    • Legacy Documentation
  • Developer Sandbox

    Developer Sandbox

    • Access Red Hat’s products and technologies without setup or configuration, and start developing quicker than ever before with our new, no-cost sandbox environments.
    • Explore Developer Sandbox

    Featured Developer Sandbox activities

    • Get started with your Developer Sandbox
    • OpenShift virtualization and application modernization using the Developer Sandbox
    • Explore all Developer Sandbox activities

    Ready to start developing apps?

    • Try at no cost
  • Blog
  • Events
  • Videos

Configure CodeReady Containers for AI/ML development

April 6, 2022
JooHo Lee
Related topics:
Artificial intelligenceContainers
Related products:
Developer ToolsRed Hat OpenShift Local

Share:

    Machine learning and artificial intelligence applications require substantial resources to run in production scenarios. But you can develop and test these applications on a cluster environment that runs on your laptop. In this article, you'll learn how to properly customize Red Hat OpenShift and Red Hat CodeReady Containers so that you can quickly set up a clustering environment where you can run open source machine learning tools from Open Data Hub.

    An AI environment on your laptop

    It may seem surprising to say that you can do serious work in the AI/ML space on your home computer. But these days, laptops are no longer just for internet surfing. Typical laptop resources are unbelievably high. For instance, the specifications of my laptop are on par with those of a typical server:

    • CPU: Intel 10th gen Comet Lake H Series Core i7 (12 cores)
    • Memory: 64GB
    • Disk: 1TB

    With such a great computer, you can now easily try hot technologies such as Kubernetes and deploy machine learning tools locally. This article discusses how to install Red Hat OpenShift, which is a Kubernetes-based environment, on a laptop, and how to prepare Red Hat OpenShift to install AI tools.

    Red Hat OpenShift provides a command-line interface (oc), a versatile graphical interface, and other conveniences. Red Hat offers a fully managed cloud environment based on OpenShift, but you can also download OpenShift to your local system and get essentially the same environment for development and testing. CodeReady Containers provides the easiest way to run a local version of Red Hat OpenShift. If you haven't already installed CodeReady Containers, check out Red Hat's Getting Started guide to learn how; it includes information on libvirt and other software packages you'll need to install to get CodeReady Containers up and running.

    To obtain machine learning tools, you can visit Open Data Hub, an open source project based on Kubeflow. Open Data Hub provides open source tools that can run large, distributed AI workloads on Red Hat OpenShift.

    What resources do you need to run Open Data Hub tools?

    By default, CodeReady Containers reserves the following system resources for Red Hat OpenShift:

    • 4 virtual CPUs
    • 8GB of memory
    • 35GB of storage space

    These allocations are insufficient for running tools from Open Data Hub, which require a minimum of 6 CPUs and 16GB of RAM. In addition to this default requirement, you need a bit more resources to deploy popular AI tools. My testing has determined that the following system resources will allow you to deploy the Open Data Hub Operator, the Open Data Hub dashboard, the NFS Provisioner, JupyterHub, Ceph Nano, and Pachyderm:

    • 8 virtual CPUs
    • 20GB of memory
    • 70GB of storage space

    You'll need to configure CodeRead Containers to make sure your development environment has access to these resources. Now let's get your hands dirty making to get that all set up properly.

    Configure CodeReady Containers

    If you previously deployed a CodeReady Containers image, remove it with the following command:

    $ crc delete

    Update the CPU, memory, disk space, and kubeadmin password configuration for CodeReady Containers as follows:

    $ crc setup
    $ crc config set memory 20000
    $ crc config set cpus 8
    $ crc config set disk-size 70
    $ crc config set kubeadmin-password kubeadmin
    

    Start CodeReady Containers. The information displayed should show that Red Hat OpenShift is installed:

    $ crc start
    WARN A new version (2.0.1) has been published on https://developers.redhat.com/content-gateway/file/pub/openshift-v4/clients/crc/2.0.1/crc-linux-amd64.tar.xz 
    INFO A CodeReady Containers VM for OpenShift 4.9.15 is already running 
    Started the OpenShift cluster.
    
    The server is accessible via web console at:
      https://console-openshift-console.apps-crc.testing
    
    Log in as administrator:
      Username: kubeadmin
      Password: kubeadmin
    
    Log in as user:
      Username: developer
      Password: developer
    
    Use the 'oc' command line interface:
      $ eval $(crc oc-env)
      $ oc login -u developer https://api.crc.testing:6443
    

    The following screenshots illustrate how you can verify that you've correctly configured your OpenShift environment using the virt-manager package, which is a desktop user interface for managing virtual machines through libvirt. You can install virt-manager with the following command:

    
    sudo dnf install virt-manager -y
    
    

    These screenshots from the virt-viewer UI shows that the virtualized cluster has 8 virtual CPUs (Figure 1), 20,000MiB of allocated memory (Figure 2), and 70GiB of virtual storage (Figure 3).

    OpenShift has 8 virtual CPUs.
    Figure 2: OpenShift has 8 virtual CPUs.
    Figure 1: Red Hat OpenShift has 8 virtual CPUs.
    OpenShift has 20,000MiB of allocated memory.
    Figure 3: OpenShift has 20,000MiB of allocated memory.
    Figure 2: Red Hat OpenShift has 20,000MiB of allocated memory.
    OpenShift has 70GiB of virtual storage.
    Figure 4: OpenShift has 70GiB of virtual storage.
    Figure 3: OpenShift has 70GiB of virtual storage.

    Congratulations—you now have an OpenShift cluster that can play with Open Data Hub. Have fun exploring the possibilities of machine learning and artificial intelligence! For help getting started doing work with AI/ML and data science on Red Hat OpenShift, check out the learning paths on Red Hat OpenShift Data Science from Red Hat Developer.

    Last updated: November 8, 2023

    Recent Posts

    • Migrating Ansible Automation Platform 2.4 to 2.5

    • Multicluster resiliency with global load balancing and mesh federation

    • Simplify local prototyping with Camel JBang infrastructure

    • Smart deployments at scale: Leveraging ApplicationSets and Helm with cluster labels in Red Hat Advanced Cluster Management for Kubernetes

    • How to verify container signatures in disconnected OpenShift

    Red Hat Developers logo LinkedIn YouTube Twitter Facebook

    Products

    • Red Hat Enterprise Linux
    • Red Hat OpenShift
    • Red Hat Ansible Automation Platform

    Build

    • Developer Sandbox
    • Developer Tools
    • Interactive Tutorials
    • API Catalog

    Quicklinks

    • Learning Resources
    • E-books
    • Cheat Sheets
    • Blog
    • Events
    • Newsletter

    Communicate

    • About us
    • Contact sales
    • Find a partner
    • Report a website issue
    • Site Status Dashboard
    • Report a security problem

    RED HAT DEVELOPER

    Build here. Go anywhere.

    We serve the builders. The problem solvers who create careers with code.

    Join us if you’re a developer, software engineer, web designer, front-end designer, UX designer, computer scientist, architect, tester, product manager, project manager or team lead.

    Sign me up

    Red Hat legal and privacy links

    • About Red Hat
    • Jobs
    • Events
    • Locations
    • Contact Red Hat
    • Red Hat Blog
    • Inclusion at Red Hat
    • Cool Stuff Store
    • Red Hat Summit
    © 2025 Red Hat

    Red Hat legal and privacy links

    • Privacy statement
    • Terms of use
    • All policies and guidelines
    • Digital accessibility

    Report a website issue