Minikube

Minikube is a tool that quickly sets up a local Kubernetes cluster on macOS, Linux, and Windows. It’s a great solution for trying out HPE Machine Learning Data Management locally.

Before You Start #

Kubernetes & Openshift Version Support

• Kubernetes: HPE Machine Learning Data Management supports the three most recent minor release versions of Kubernetes. If your Kubernetes version is not among these, it is End of Life (EOL) and unsupported. This ensures HPE Machine Learning Data Management users access to the latest Kubernetes features and bug fixes.
• Openshift: HPE Machine Learning Data Management is compatible with OpenShift versions within the “Full Support” window.

1. Install Docker #

brew install docker

See the official Docker getting started guide for the most up-to-date installation steps.

2. Install & Start Minikube #

Install #

brew install minikube

See the official Minikube getting started guide for the most up-to-date installation steps.

Start #

1. Launch Docker Desktop.
2. Start Minikube:

minikube start

3. Install Pachctl CLI #

4. Install & Configure Helm #

1. Install Helm:

   brew install helm

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2. Add the HPE Machine Learning Data Management repo to Helm:

   helm repo add pachyderm https://helm.pachyderm.com  
   helm repo update  

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3. Install Pachyderm:

This may take several minutes to complete.

5. Verify Installation #

1. Run the following command in a new terminal to check the status of your pods:

   kubectl get po -A

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   NAMESPACE              NAME                                         READY   STATUS    RESTARTS        AGE
   default                console-6b9bb8766d-f2gm4                     1/1     Running   0             41m
   default                etcd-0                                       1/1     Running   0             41m
   default                pachd-76896d6b5d-kmfvw                       1/1     Running   0             41m
   default                pachd-loki-0                                 1/1     Running   0             41m
   default                pachd-promtail-rm5ss                         1/1     Running   0             41m
   default                pachyderm-kube-event-tail-b9b554fb6-dpcsr    1/1     Running   0             41m
   default                pg-bouncer-5c9494c678-z57qh                  1/1     Running   0             41m
   default                postgres-0                                   1/1     Running   0             41m
   kube-system            coredns-6d4b75cb6d-jnl5f                     1/1     Running   3 (42m ago)   97d
   kube-system            etcd-minikube                                1/1     Running   4 (42m ago)   97d
   kube-system            kube-apiserver-minikube                      1/1     Running   3 (42m ago)   97d
   kube-system            kube-controller-manager-minikube             1/1     Running   4 (42m ago)   97d
   kube-system            kube-proxy-bngzv                             1/1     Running   3 (42m ago)   97d
   kube-system            kube-scheduler-minikube                      1/1     Running   3 (42m ago)   97d
   kube-system            storage-provisioner                          1/1     Running   5 (42m ago)   97d
   kubernetes-dashboard   dashboard-metrics-scraper-78dbd9dbf5-swttf   1/1     Running   3 (42m ago)   97d
   kubernetes-dashboard   kubernetes-dashboard-5fd5574d9f-c7ptx        1/1     Running   4 (42m ago)   97d

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2. Re-run this command after a few minutes if pachd is not ready.

6. Connect to Cluster #

1. Run minikube tunnel to start a tunnel.
2. In a separate terminal, get the external IP address of the pachyderm-proxy service:

   kubectl get all

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   service/pachyderm-proxy             LoadBalancer   10.110.148.228   127.0.0.1     80:32024/TCP   

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3. Run the following command to connect to your cluster:

pachctl connect 127.0.0.1:80 

Optionally open your browser and navigate to the Console UI.

Tip

You can check your HPE Machine Learning Data Management version and connection to pachd at any time with the following command:

pachctl version

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COMPONENT           VERSION  
pachctl             2.11.4  
pachd               2.11.4  

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