Version v0.7 of the documentation is no longer actively maintained. The site that you are currently viewing is an archived snapshot. For up-to-date documentation, see the latest version.

Deploy using MiniKF on GCP

Instructions for using the Google Cloud Marketplace to deploy MiniKF (mini Kubeflow) on Google Cloud Platform (GCP).

This guide describes how to launch a MiniKF virtual machine (VM) on GCP. MiniKF is a single VM solution on the Google Cloud Marketplace, and installs:

  • Kubernetes (using Minikube)
  • Kubeflow
  • Kale, a tool to convert general purpose Jupyter Notebooks to Kubeflow Pipelines workflows (GitHub)
  • Arrikto’s Rok, a data management software for data versioning and reproducibility

MiniKF installs Kubeflow 0.7.0 and supports NVIDIA GPUs.

Before you start

Before installing MiniKF, make sure that your GCP project meets the minimum requirements described below:

  1. Select or create a project on the GCP Console.
  2. Make sure that you have the editor role role for the project. You can add a member to a project and grant them a Cloud IAM role using the Cloud Console.
  3. Make sure that billing is enabled for your project. For more info, see the Modify a Project’s Billing Settings guide.
  4. If you are using the GCP Free Tier or the 12-month trial period with $300 credit, note that you can’t run the default GCP installation of MiniKF, because the free tier does not offer enough resources. You need to upgrade to a paid account.
  5. Read the GCP guide to resource quotas to understand the quotas on resource usage that Compute Engine enforces, and to learn how to check your quota and how to request an increase in quota.

Installing MiniKF on GCP

To install MiniKF on GCP, follow the steps below:

  1. Go to the MiniKF page on Google Cloud Marketplace.

  2. Click on the Launch on Compute Engine button

    Launch MiniKF on GCP

  3. In the Configure & Deploy window, choose:

    • name: a name for your MiniKF instance
    • zone: the GCP zone that you will deploy MiniKF
    • machine type: a machine type with at least 2 vCPUs and 16 GB of RAM. If in doubt, use the default machine type, n1–standard-8, which has 8 vCPUs and 30 GB of RAM.
    • boot disk: A boot disk. This is the disk that holds the images that MiniKF needs. Use the default value of 200 GB SSD Persistent Disk.
    • data disk: A data disk. This is the disk that holds your snapshots. Use an SSD Persistent Disk of at least 500 GB capacity.

    Then click Deploy:

    Configure and deploy MiniKF

  4. Now wait for the VM to boot.

    MiniKF on GCP has been deployed

  5. When the VM is up, ensure that MiniKF is up and running. Before visiting the MiniKF dashboard, ensure that Minikube, Kubeflow, and Rok (Snapshot Store) are up and running. To do so, click on the SSH button to connect to the MiniKF VM and follow the on-screen instructions.

    Connect to the MiniKF VM

  6. MiniKF dashboard, username, and password. Now that Minikube, Kubeflow, and Rok are up-and-running, close the SSH browser window, as you will not need it anymore. On your current view, please find the MiniKF dashboard URL, MiniKF username, and MiniKF password. You will need them to log in to Kubeflow and Rok. You should see a table like the one below:

    MiniKF dashboard, username, and password

  7. Log in to Kubeflow. Visit the MiniKF dashboard URL and log in to Kubeflow using the MiniKF username and password.

    Log in to Kubeflow

  8. Log in to Snapshot Store (Rok). After logging in to Kubeflow, navigate to the Snapshot Store:

    Navigate to the Snapshot Store

    And log in to Snapshot Store (Arrikto’s Rok) using the MiniKF username and password.

    Log in to Rok

Congratulations! You have successfully deployed MiniKF on GCP. You can now create notebooks, write your ML code, and run Kubeflow Pipelines.