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This is a work in progress. Do not publish it publicly yet.

Prerequisite

In order to complete the onboarding process, you will need to execute a script on your machine. This script requires:

  • cluster-admin access to the Kubernetes cluster

  • kubectl

  • Python 3.7+

Instructions

Download the onboarding script

TODO: provide static link to script

The script is written in Python. It works with Python 3.7+ on macOS and Linux.

The script will:

  • create a service account for Data Theorem

  • add a security audit role (with read-only access)

  • link the security audit role to the service account

  • generate a kube config file which contains a token which never expires

The script calls kubectl, which must be set on the cluster you want to onboard.

Onboarding Kubernetes cluster on Amazon (EKS)

First we need to retrieve the role ARN of the Kubernetes cluster:

  1. Go to the AWS Console

  2. Go to EKS

  3. On the left hand side, click on Clusters, under Amazon EKS

  4. In the list of clusters, search for the cluster name you want to onboard and click on it

  5. Then click on the Configuration tab

  6. Finally copy the Cluster IAM Role ARN

Then run the script as follows:

python3 datatheorem-k8s-onboarding.py -p aws -o <CONFIG_OUTPUT_PATH> --rolearn <ROLE_ARN>

Onboarding Kubernetes cluster on Azure (AKS)

In order to onboard the cluster, it must have the RBAC setting enabled. You can make sure of that by going to the Azure Console and:

  1. Kubernetes Services

  2. Search for the name of the cluster you want to onboard and click on it

  3. Under Settings, click on Cluster configuration

  4. Role-based access control (RBAC) must be Enabled

python3 datatheorem-k8s-onboarding.py -p azure -o <CONFIG_OUTPUT_PATH>

Onboarding Kubernetes cluster on GCP (GKE)

The gcloud user that runs the script must have the Kubernetes Engine Admin role or higher.

python3 datatheorem-k8s-onboarding.py -p gcp -o <CONFIG_OUTPUT_PATH>

Onboarding on-premises Kubernetes cluster

python3 datatheorem-k8s-onboarding.py -p onprem -o <CONFIG_OUTPUT_PATH>
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