Pre-provisioned Air-gapped GPU: Configure Environment

If the NVIDIA runfile installer has not been downloaded, then retrieve and install the download first by running the following command. The first line in the command below downloads and installs the runfile and the second line places it in the artifacts directory.

CODE

curl -O https://download.nvidia.com/XFree86/Linux-x86_64/470.82.01/NVIDIA-Linux-x86_64-470.82.01.run
mv NVIDIA-Linux-x86_64-470.82.01.run artifacts

The instructions below outline how to fulfill the requirements for a pre-provisioned infrastructure when using an air-gapped environment. In order to create a cluster, you must first setup the environment with necessary artifacts. All artifacts for Pre-provisioned Air-gapped environments need to get onto the bastion host. Artifacts needed by nodes must be unpacked and distributed on the bastion before other provisioning will work in the absence of an internet connection.

There is a new complete DKP air-gapped bundle available to download which contains all the DKP components needed for air-gapped installation. (i.e. dkp-air-gapped-bundle_v2.5.2_linux_amd64.tar.gz)

Setup Process:

The bootstrap image must be extracted and loaded onto the bastion host.
Artifacts must be copied onto cluster hosts for nodes to access.
If using GPU, those artifacts must be positioned locally.
Docker Registry seeded with images locally.

Load the Bootstrap Image

Assuming you have downloaded dkp-air-gapped-bundle_v2.5.2_linux_amd64.tar.gz from the download site mentioned above, extract the tarball to a local directory:
CODE
```
tar -xzvf dkp-air-gapped-bundle_v2.5.2_linux_amd64.tar.gz && cd dkp-v2.5.2
```
Load the bootstrap Docker image on your bastion machine:
CODE
```
docker load -i konvoy-bootstrap-image-v2.5.2.tar
```

Copy Air-gapped Artifacts onto Cluster Hosts

Using the Konvoy Image Builder, you can copy the required artifacts onto your cluster hosts.

Assuming you have downloaded dkp-air-gapped-bundle_v2.5.2_linux_amd64.tar.gz , continue below:

The Kubernetes image bundle will be located in kib/artifacts/images and you will want to verify image and artifacts.

Verify the image bundles exist in artifacts/images:

CODE

$ ls artifacts/images/
kubernetes-images-1.25.4-d2iq.1.tar kubernetes-images-1.25.4-d2iq.1-fips.tar

Verify the artifacts for your OS exist in the artifacts/ directory and export the appropriate variables:

CODE

$ ls artifacts/
1.25.4_centos_7_x86_64.tar.gz	    1.25.4_redhat_8_x86_64_fips.tar.gz			    containerd-1.6.17-d2iq.1-rhel-7.9-x86_64.tar.gz	  containerd-1.6.17-d2iq.1-rhel-8.6-x86_64_fips.tar.gz	pip-packages.tar.gz
1.25.4_centos_7_x86_64_fips.tar.gz  1.25.4_rocky_9_x86_64.tar.gz			    containerd-1.6.17-d2iq.1-rhel-7.9-x86_64_fips.tar.gz  containerd-1.6.17-d2iq.1-rocky-9.0-x86_64.tar.gz
1.25.4_redhat_7_x86_64.tar.gz	    1.25.4_ubuntu_20_x86_64.tar.gz			    containerd-1.6.17-d2iq.1-rhel-8.4-x86_64.tar.gz	  containerd-1.6.17-d2iq.1-rocky-9.1-x86_64.tar.gz
1.25.4_redhat_7_x86_64_fips.tar.gz  containerd-1.6.17-d2iq.1-centos-7.9-x86_64.tar.gz	    containerd-1.6.17-d2iq.1-rhel-8.4-x86_64_fips.tar.gz  containerd-1.6.17-d2iq.1-ubuntu-20.04-x86_64.tar.gz  NVIDIA-Linux-x86_64-470.82.01.run
1.25.4_redhat_8_x86_64.tar.gz	    containerd-1.6.17-d2iq.1-centos-7.9-x86_64_fips.tar.gz  containerd-1.6.17-d2iq.1-rhel-8.6-x86_64.tar.gz	  images

For example, for RHEL 8.4 you would set:

CODE

export OS_PACKAGES_BUNDLE=1.25.4_redhat_8_x86_64.tar.gz
export CONTAINERD_BUNDLE=containerd-1.6.17-d2iq.1-rhel-8.4-x86_64.tar.gz

Export the following environment variables, ensuring that all control plane and worker nodes are included:

CODE

export CONTROL_PLANE_1_ADDRESS="<control-plane-address-1>"
export CONTROL_PLANE_2_ADDRESS="<control-plane-address-2>"
export CONTROL_PLANE_3_ADDRESS="<control-plane-address-3>"
export WORKER_1_ADDRESS="<worker-address-1>"
export WORKER_2_ADDRESS="<worker-address-2>"
export WORKER_3_ADDRESS="<worker-address-3>"
export WORKER_4_ADDRESS="<worker-address-4>"
export SSH_USER="<ssh-user>"
export SSH_PRIVATE_KEY_FILE="<private key file>"

SSH_PRIVATE_KEY_FILE must be either the name of the SSH private key file in your working directory or an absolute path to the file in your user’s home directory.

Generate an inventory.yaml for GPU nodes which is automatically picked up by the konvoy-image upload in the next step.

CODE

cat <<EOF >  gpu_inventory.yaml 
all:
  vars:
    ansible_port: 22
    ansible_ssh_private_key_file: $SSH_PRIVATE_KEY_FILE
    ansible_user: $SSH_USER

  hosts:
    $GPU_WORKER_1_ADDRESS:
      ansible_host: $GPU_WORKER_1_ADDRESS
EOF

cat <<EOF > inventory.yaml
all:
  vars:
    ansible_user: $SSH_USER
    ansible_port: 22
    ansible_ssh_private_key_file: $SSH_PRIVATE_KEY_FILE
  hosts:
    $CONTROL_PLANE_1_ADDRESS:
      ansible_host: $CONTROL_PLANE_1_ADDRESS
    $CONTROL_PLANE_2_ADDRESS:
      ansible_host: $CONTROL_PLANE_2_ADDRESS
    $CONTROL_PLANE_3_ADDRESS:
      ansible_host: $CONTROL_PLANE_3_ADDRESS
    $WORKER_1_ADDRESS:
      ansible_host: $WORKER_1_ADDRESS
    $WORKER_2_ADDRESS:
      ansible_host: $WORKER_2_ADDRESS
    $WORKER_3_ADDRESS:
      ansible_host: $WORKER_3_ADDRESS
    $WORKER_4_ADDRESS:
      ansible_host: $WORKER_4_ADDRESS
EOF

Upload the artifacts to the gpu nodepool with the nvidia-runfile flag with the following command:

CODE

konvoy-image upload artifacts --inventory-file=gpu_inventory.yaml \
              --container-images-dir=./artifacts/images/ \
              --os-packages-bundle=./artifacts/$OS_PACKAGES_BUNDLE \
              --containerd-bundle=artifacts/$CONTAINERD_BUNDLE \
              --pip-packages-bundle=./artifacts/pip-packages.tar.gz \
              --nvidia-runfile=./artifacts/NVIDIA-Linux-x86_64-470.82.01.run

KIB uses variable overrides to specify base image and container images to use in your new machine image. The variable overrides files for NVIDIA and FIPS can be ignored unless adding an overlay feature.

Use the --overrides overrides/fips.yaml,overrides/offline-fips.yaml flag with manifests located in the overrides directory or see these pages in the documentation:
- FIPS Overrides
- Create FIPS 140 Images

Next Step:

Pre-provisioned Air-gapped GPU: Load the Registry