Docker Desktop

Before You Start #

You must have Homebrew installed.

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

You must have WSL enabled (wsl --install) and a Linux distribution installed; if Linux does not boot in your WSL terminal after downloading from the Microsoft store, see the manual installation guide.

Manual Step Summary:

Open a Powershell terminal.
Run each of the following:

dism.exe /online /enable-feature /featurename:Microsoft-Windows-Subsystem-Linux /all /norestart

dism.exe /online /enable-feature /featurename:VirtualMachinePlatform /all /norestart

Download the latest WSL2 Linux Kernel for x64 machines.
Run each of the following:

wsl --set-default-version 2

wsl --install -d Ubuntu

Restart your machine.
Start a WSL terminal and set up your first Ubuntu user.
Update Ubuntu.

sudo apt update
sudo apt upgrade -y

Install Homebrew in Ubuntu so you can complete the rest of this guide:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

All installation steps after 1. Install Docker Desktop must be run through the WSL terminal (Ubuntu) and not in Powershell.

You are now ready to continue to Step 1.

You can optionally install Homebrew to easily install tools like Helm.

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

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 Desktop #

Install Docker Desktop for your machine.
Navigate to Settings for Mac, Windows, or Linux.
- Adjust your resources (~4 CPUs and ~12GB Memory)
- Enable Kubernetes
Select Apply & Restart.

2. Install Pachctl CLI #

brew tap pachyderm/tap && brew install pachyderm/tap/pachctl@2.11

curl -o /tmp/pachctl.deb -L https://github.com/pachyderm/pachyderm/releases/download/v2.11.4/pachctl_2.11.4_amd64.deb && sudo dpkg -i /tmp/pachctl.deb

AMD

curl -L https://github.com/pachyderm/pachyderm/releases/download/v2.11.4/pachctl_2.11.4_linux_amd64.tar.gz | sudo tar -xzv --strip-components=1 -C /usr/local/bin

ARM

curl -L https://github.com/pachyderm/pachyderm/releases/download/v2.11.4/pachctl_2.11.4_linux_arm64.tar.gz | sudo tar -xzv --strip-components=1 -C /usr/local/bin

3. Install & Configure Helm #

Install Helm:
```
brew install helm
```

Add the Pachyderm repo to Helm:

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

Install PachD:

Tip

Open your browser and check http://localhost before installing. If any other tools are using the same port as HPE Machine Learning Data Management, add the following argument to the below command: --set proxy.service.httpPort=8080

helm install pachyderm pachyderm/pachyderm \
   --set deployTarget=LOCAL \
   --set proxy.enabled=true \
   --set proxy.service.type=LoadBalancer

Are you using an Enterprise trial key? If so, you can set up Enterprise Pachyderm locally by storing your trial key in a license.txt file and passing it into the following Helm command:

helm install pachyderm pachyderm/pachyderm \
   --set deployTarget=LOCAL \
   --set proxy.enabled=true \
   --set proxy.service.type=LoadBalancer \
   --set pachd.enterpriseLicenseKey=$(cat license.txt) \
   --set ingress.host=localhost \
   --set pachd.storage.backend=AMAZON \

A mock user is created by default to get you started, with the username: admin and password: password.

This may take several minutes to complete.

4. Verify Installation #

In a new terminal, run the following command to check the status of your pods:

kubectl get pods

NAME                                           READY   STATUS      RESTARTS   AGE
pod/console-5b67678df6-s4d8c                   1/1     Running     0          2m8s
pod/etcd-0                                     1/1     Running     0          2m8s
pod/pachd-c5848b5c7-zwb8p                      1/1     Running     0          2m8s
pod/pg-bouncer-7b855cb797-jqqpx                1/1     Running     0          2m8s
pod/postgres-0                                 1/1     Running     0          2m8s

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

5. Connect to Cluster #

pachctl connect http://localhost:80

Warning

If you set the httpPort to a new value, such as 8080, use that value in the command. pachctl connect http://localhost:8080

Optionally open your browser and navigate to the Console UI.

Tip

You can check your Pachyderm version and connection to pachd at any time with the following command:

pachctl version

COMPONENT           VERSION  

pachctl             2.11.4  
pachd               2.11.4