Installing

Procedure

1. Create an S3 bucket and set the permissions to allow image file conversion to AWS snapshots.

   1. Create the necessary environment variables. Open a shell prompt and run the following commands:

      $ export BUCKET=<CUSTOM_BUCKET_NAME>
      $ export RAW_AMI=nvidia-bootc.ami
      $ export AMI_NAME="rhel-ai"
      $ export DEFAULT_VOLUME_SIZE=1000

   2. Create the S3 bucket by running the following command:

      $ aws s3 mb s3://$BUCKET

   3. Create the trust-policy.json file with the necessary configuration for generating an S3 role for your bucket:

      $ printf '{
        "Version": "2012-10-17",
        "Statement": [
          {
            "Effect": "Allow",
            "Principal": {
              "Service": "vmie.amazonaws.com"
            },
            "Action": "sts:AssumeRole",
            "Condition": {
              "StringEquals": {
                "sts:Externalid": "vmimport"
              }
            }
          }
        ]
      }' > trust-policy.json

   4. Create the S3 role for your bucket. Run the following command:

      $ aws iam create-role --role-name vmimport --assume-role-policy-document file://trust-policy.json

   5. Create the role-policy.json file with the necessary configurations for generating a policy for your bucket:

      $ printf '{
        "Version": "2012-10-17",
        "Statement": [
          {
            "Effect": "Allow",
            "Action": [
              "s3:GetBucketLocation",
              "s3:GetObject",
              "s3:ListBucket"
            ],
            "Resource": [
              "arn:aws:s3:::%s",
              "arn:aws:s3:::%s/*"
            ]
          },
          {
            "Effect": "Allow",
            "Action": [
              "ec2:ModifySnapshotAttribute",
              "ec2:CopySnapshot",
              "ec2:RegisterImage",
              "ec2:Describe*"
            ],
            "Resource": "*"
          }
        ]
      }' $BUCKET $BUCKET > role-policy.json

   6. Create the policy for your bucket by running the following command:

      $ aws iam put-role-policy --role-name vmimport --policy-name vmimport-$BUCKET --policy-document file://role-policy.json

2. Copy the x86_64 RAW image URL from the Download Red Hat Enterprise Linux AI page and download the image using curl:

   $ curl -Lo disk.raw.gz <RAW_IMAGE_URL>

3. Unzip the raw.gz file:

   $ gunzip disk.raw.gz

4. Upload the image to the S3 bucket with the following command:

   $ aws s3 cp disk.raw s3://$BUCKET/$RAW_AMI

5. Convert the image to a snapshot and store it in the TASK_ID variable name by running the following commands:

   $ printf '{
      "Description":"rhelai-image",
      "Format":"raw",
      "UserBucket":{
         "S3Bucket":"%s",
         "S3Key":"%s"
      }
   }' $BUCKET $RAW_AMI > containers.json

   $ TASK_ID=$(aws ec2 import-snapshot --disk-container file://containers.json | jq -r .ImportTaskId)

6. Follow the progress of the disk image to snapshot conversion job with the following command:

   $ aws ec2 describe-import-snapshot-tasks --filters Name=task-state,Values=active

7. Get the snapshot ID and store it the SNAPSHOT_ID variable by running the following command:

   $ SNAPSHOT_ID=$(aws ec2 describe-import-snapshot-tasks | jq -r '.ImportSnapshotTasks[] | select(.ImportTaskId=="'${TASK_ID}'") | .SnapshotTaskDetail.SnapshotId')

8. Add a tag name to the snapshot by running the following command:

   $ aws ec2 create-tags --resources $SNAPSHOT_ID --tags Key=Name,Value="$AMI_NAME"

9. Register the AMI from the snapshot with the following command:

   $ AMI_ID=$(aws ec2 register-image \
   --name "$AMI_NAME" \
   --description "$AMI_NAME" \
   --architecture x86_64 \
   --root-device-name /dev/sda1 \
   --block-device-mappings "DeviceName=/dev/sda1,Ebs={VolumeSize=${DEFAULT_VOLUME_SIZE},SnapshotId=${SNAPSHOT_ID}}" \
   --virtualization-type hvm \
   --ena-support \
   | jq -r .ImageId)

10. Add a tag name to identify the AMI by running the following command:

    $ aws ec2 create-tags --resources $AMI_ID --tags Key=Name,Value="$AMI_NAME"

Procedure

1. Configure the various AWS parameters.

   1. Set the AMI variable. Run the following command and copy the required AMI ID:

      $ aws ec2 describe-images --owners self

      $ AMI=<AMI_ID>

   2. Set the SECURITY_GROUP variable. Run the following command and copy the required security group ID:

      $ aws ec2 describe-security-groups

      $ SECURITY_GROUP=<SECURITY_GROUP_ID>

   3. Set the SUBNET variable. Run the following command and copy the required subnet:

      $ aws ec2 describe-subnets

      $ SUBNET=<SUBNET>

   4. Set the INSTANCE_TYPE variable:

      $ INSTANCE_TYPE=<INSTANCE_TYPE_SIZE>

   5. Set the INSTANCE_NAME variable:

      $ INSTANCE_NAME=rhel-ai-instance

   6. Set the disk size variable:

      $ DISK_SIZE=<REQUIRED_DISK_SIZE>

   7. Set the KEY_NAME variable:

      $ KEY_NAME=<KEY_PAIR_NAME>

2. Create the instance by running the following command:

   $ aws ec2 run-instances \
   --image-id $AMI \
   --instance-type $INSTANCE_TYPE \
   --key-name $KEY_NAME \
   --security-group-ids $SECURITY_GROUP \
   --subnet-id $SUBNET \
   --block-device-mappings DeviceName=/dev/sda1,Ebs='{VolumeSize='$DISK_SIZE'}' \
   --tag-specifications 'ResourceType=instance,Tags=[{Key=Name,Value='$INSTANCE_NAME'}]'

   Important

   The default user account in the RHEL AI AMI is cloud-user. The cloud-user account has passwordless sudo access.

Procedure

1. Log in to IBM Cloud. Run the following command:

   $ ibmcloud login

   When prompted, select the account to log in to.

2. Set up various required IBM Cloud configurations, create the COS bucket, and then generate the required QCOW2 image.

   1. Install the required IBM Cloud plugins by running the following command:

      $ ibmcloud plugin install cloud-object-storage infrastructure-service

   2. Set the preferred resource group, for example:

      $ ibmcloud target -g Default

   3. Set the preferred region, for example:

      $ ibmcloud target -r us-east

   4. Select a deployment plan for the service instance.

      1. You can list the available deployment plans by running the following command:

         $ ibmcloud catalog service cloud-object-storage --output json | jq -r '.[].children[] | select(.children != null) | .children[].name'

      2. Set the COS_DEPLOY_PLAN environment variable with the required deployment plan, for example:

         $ COS_DEPLOY_PLAN=premium-global-deployment

      3. Create a COS service instance. Run the following commands:

         $ COS_SI_NAME=<YOUR_SERVICE_INSTANCE>

         $ ibmcloud resource service-instance-create ${COS_SI_NAME} cloud-object-storage standard global -d ${COS_DEPLOY_PLAN}

   5. Create the Cloud Resource Name (CRN) COS_CRN variable and create the resource. Run the following commands:

      $ COS_CRN=$(ibmcloud resource service-instance ${COS_SI_NAME} --output json| jq -r '.[] | select(.crn | contains("cloud-object-storage")) | .crn')

      $ ibmcloud cos config crn --crn ${COS_CRN} --force

   6. Create the COS bucket:

      $ COS_BUCKET=<YOUR_BUCKET_NAME>

      $ ibmcloud cos bucket-create --bucket ${COS_BUCKET}

   7. Allow the infrastructure service to read the buckets that are in the service instance ${COS_SI_GUID} variable by running the following commands:

      $ COS_SI_GUID=$(ibmcloud resource service-instance ${COS_SI_NAME} --output json| jq -r '.[] | select(.crn | contains("cloud-object-storage")) | .guid')

      $ ibmcloud iam authorization-policy-create is cloud-object-storage Reader --source-resource-type image --target-service-instance-id ${COS_SI_GUID}

3. Copy the QCOW2 image URL from the Download Red Hat Enterprise Linux AI page.

4. Download the QCOW2 image:

   $ curl -Lo disk.qcow2 <QCOW2_IMAGE_URL>

5. Set the name you want to use as the RHEL AI IBM Cloud image. Run the following command:

   $ IMAGE_NAME=rhel-ai-3-2025v0

6. Upload the QCOW2 image to the COS bucket with your selected region:

   $ ibmcloud cos upload --bucket ${COS_BUCKET} --key ${IMAGE_NAME}.qcow2 --file disk.qcow2 --region <REGION>

7. Convert the QCOW2 image that you just uploaded to an IBM Cloud image and set the IBM Cloud image configuration IMAGE_ID variable:

   $ IMAGE_ID=$(ibmcloud is image-create ${IMAGE_NAME} --file cos://<REGION>/${COS_BUCKET}/${IMAGE_NAME}.qcow2 --os-name red-ai-9-amd64-nvidia-byol --output json | jq -r '.id')

Verification

1. View the progress of the job by running the following command:

   $ while ibmcloud is image --output json ${IMAGE_ID} | jq -r .status | grep -xq pending; do sleep 1; done

2. View information about the newly created image:

   $ ibmcloud is image ${IMAGE_ID}

Procedure

1. Log in to your IBM Cloud account, selecting the Account, Region and Resource Group by running the following command:

   $ ibmcloud login -c <ACCOUNT_ID> -r <REGION> -g <RESOURCE_GROUP>

2. Before launching the IBM Cloud instance, you need to create several configuration variables.

   1. Install the infrastructure-service plugin for IBM Cloud by running the following command:

      $ ibmcloud plugin install infrastructure-service

   2. Create an SSH public key for your IBM Cloud account. IBM Cloud supports RSA and ed25519 keys.

      $ ssh-keygen -f ibmcloud -t ed25519

   3. Upload the public key to your IBM Cloud account.

      $ ibmcloud is key-create <YOUR_IBMCLOUD_SSH_PUB_KEY> --key-type ed25519

   4. Create a floating IP for the IBM Cloud instance:

      $ ibmcloud is floating-ip-reserve my-public-ip --zone <PREFERRED_REGION>

3. Select the instance profile that you want to use for the deployment. List all the profiles by running the following command:

   $ ibmcloud is instance-profiles

   Make a note of your preferred instance profile.

4. Create environment variables for the IBM Cloud instance, for example:

   NAME=<INSTANCE_NAME>
   VPC=<YOUR_VPC>
   ZONE=<YOUR_IBM_CLOUD_ZONE>
   SUBNET=<ZONE_SUBNET>
   INSTANCE_PROFILE=<YOUR_CLOUD_INSTANCE_PROFILE>
   IMAGE=<YOUR_IBM_CLOUD_RHELAI_IMAGE>
   SSHKEY=<YOUR_IBMCLOUD_SSH_PUB_KEY>
   FLOATING_IP=<PUBLIC_IP>
   DISK_SIZE=250

5. You can now launch your instance, by running the following command:

   $ ibmcloud is instance-create \
       $NAME \
       $VPC \
       $ZONE \
       $INSTANCE_PROFILE \
       $SUBNET \
       --image $IMAGE \
       --keys $SSHKEY \
       --boot-volume '{"name": "'${NAME}'-boot", "volume": {"name": "'${NAME}'-boot", "capacity": '${DISK_SIZE}', "profile": {"name": "general-purpose"}}}' \
       --allow-ip-spoofing false

6. Link the Floating IP to the instance by running the following command:

   $ ibmcloud is floating-ip-update $FLOATING_IP --nic primary --in $NAME

Procedure

1. Create the NAME environment variable:

   $ NAME=rhelai-instance

2. Create the DATA_VOLUME_SIZE variable:

   $ DATA_VOLUME_SIZE=1000

3. Create the volume and attach it the instance by running the following command:

   $ ibmcloud is instance-volume-attachment-add data ${NAME} \
   --new-volume-name ${NAME}-data \
   --profile general-purpose \
   --capacity ${DATA_VOLUME_SIZE}

4. Review the disks attached to the instance:

   $ lsblk

5. Create a DISK variable for the newly provisioned disk path, for example:

   $ DISK=/dev/vdb

6. Create a partition on the disk by running the following command:

   $ sgdisk -n 1:0:0 $DISK

7. Format and label the partition:

   $ mkfs.xfs -L rhelai-data ${DISK}1

8. Optional: Configure the system to auto-mount to the directory. To mount the disk to the /mnt folder, run the following command:

   $ echo LABEL=rhelai-data /mnt xfs defaults 0 0 >> /etc/fstab

9. Reload the systemd service:

   $ systemctl daemon-reload

10. Mount the disk:

    $ mount -a

11. Grant write permissions to all users in the new file system by running the following command:

    $ chmod 1777 /mnt/

Procedure

1. Log in to gcloud. Run the following command:

   $ gcloud auth login

2. Configure gcloud and create your Google Cloud storage container.

   1. Configure the gcloud CLI to use your project.

      $ GCLOUD_PROJECT=rhelai-gcloud-project

      $ gcloud config set project $GCLOUD_PROJECT

   2. Create an environment variable defining the region where you want to operate. For example:

      $ gcloud_region=us-central1

   3. Create a storage container. Run the following commands:

      $ GCLOUD_BUCKET=<YOUR_BUCKET_NAME>

      $ gsutil mb -l $gcloud_region gs://$GCLOUD_BUCKET

3. Download the tar.gz image from the Download Red Hat Enterprise Linux AI page.

4. Unzip the tar.gz file with the following command:

   $ gunzip <DOWNLOADED_TAR_GZ_FILE>

5. Configure the IMAGE_NAME variable:

   $ IMAGE_NAME=rhel-ai-gcloud

6. Upload the tar.gz file to the Google Cloud Storage Container by running the following command:

   $ gsutil cp <DOWNLOADED_TAR_GZ_FILE> "gs://${GCLOUD_BUCKET}/$IMAGE_NAME.tar.gz"

7. Create a Google Cloud image from the tar.gz file:

   $ gcloud compute images create \
   "$IMAGE_NAME" \
   --source-uri="gs://${GCLOUD_BUCKET}/$IMAGE_NAME.tar.gz" \
   --family "rhel-ai" \
   --guest-os-features=GVNIC

Procedure

1. Log in to your Google Cloud account by running the following command:

   $ gcloud auth login

2. Create several gcloud configuration variables for the deployment.

3. Select the instance profile that you want to use for the deployment. List all the profiles in the required region by running the following command:

   $ gcloud compute machine-types list --zones=<ZONE>

   Make a note of the preferred machine type.

4. Create Google Cloud instance variables, for example:

   NAME=rhelai-instance
   ZONE=us-central1-a
   MACHINE_TYPE=a3-highgpu-8g
   ACCELERATOR="type=nvidia-h100-80gb,count=8"
   IMAGE=custom-rhelai-image
   DISK_SIZE=1024
   SUBNET=default

5. Configure the zone.

   $ gcloud config set compute/zone $ZONE

6. Launch the Google Cloud instance:

   $ gcloud compute instances create \
       ${name} \
       --machine-type ${MACHINE_TYPE} \
       --image $IMAGE \
       --zone $ZONE \
       --subnet $SUBNET \
       --boot-disk-size ${DISK_SIZE} \
       --boot-disk-device-name ${NAME} \
       --accelerator=$ACCELERATOR

Procedure

1. Log in to Azure by running the following command:

   $ az login

2. Log in with the azcopy tool:

   $ keyctl new_session

   $ azcopy login

3. Configure various Azure environment variables and create your Azure storage container.

   1. Create an environment variable defining the location of your instance with the following command:

      $ AZ_LOCATION=eastus

   2. Create the AZ_RESOURCE_GROUP environment variable. For example:

      $ AZ_RESOURCE_GROUP=Default
      $ az group create --name ${AZ_RESOURCE_GROUP} --location ${AZ_LOCATION}

   3. Create the Azure storage account:

      $ AZ_STORAGE_ACCOUNT=<YOUR_STORAGE_ACCOUNT_NAME>

      $ az storage account create \
      --name ${AZ_STORAGE_ACCOUNT} \
      --resource-group ${AZ_RESOURCE_GROUP} \
      --location ${AZ_LOCATION} \
      --sku Standard_LRS

   4. Create the Azure storage container. Run the following commands:

      $ AZ_STORAGE_CONTAINER=<BUCKET_NAME>

      $ az storage container create \
      --name ${AZ_STORAGE_CONTAINER} \
      --account-name ${AZ_STORAGE_ACCOUNT} \
      --public-access off

   5. Get the Subscription ID from the Azure account list by running the following command:

      $ az account list --output table

   6. Create the AZ_SUBSCRIPTION_ID variable. For example:

      $ AZ_SUBSCRIPTION_ID=46c08fb3-83c5-4b59-8372-bf9caf15a681

   7. Grant azcopy write permission to user into the storage container. For example:

      $ az role assignment create \
      --assignee user@example.com \
      --role "Storage Blob Data Contributor" \
      --scope /subscriptions/${AZ_SUBSCRIPTION_ID}/resourceGroups/${AZ_RESOURCE_GROUP}/providers/Microsoft.Storage/storageAccounts/${AZ_STORAGE_ACCOUNT}/blobServices/default/containers/${AZ_STORAGE_CONTAINER}

4. Download the Azure VHD image from Download Red Hat Enterprise Linux AI page.

5. Unzip the vhd.gz file with the following command:

   $ gunzip <DOWNLOADED_AZURE_GZ_IMAGE>

6. Set the Azure image name:

   $ IMAGE_NAME=rhel-ai-azure

7. Upload the VHD file to the Azure storage container by running the following command:

   $ AZ_VHD_URL="https://${AZ_STORAGE_ACCOUNT}.blob.core.windows.net/${AZ_STORAGE_CONTAINER}/$(basename ${vhd_file})"
   $ azcopy copy "$vhd_file" "$AZ_VHD_URL"

8. Create an Azure image from the uploaded VHD file. Run the following command:

   $ az image create --resource-group $AZ_RESOURCE_GROUP \
   --name "$IMAGE_NAME" \
   --source "${AZ_VHD_URL}" \
   --location ${AZ_LOCATION} \
   --os-type Linux \
   --hyper-v-generation V2

Procedure

1. Log in to your Azure account:

   $ az login

2. Select the instance profile that you want to use for the deployment. List all the profiles in the required region by running the following command:

   $ az vm list-sizes --location <REGION> --output table

3. Creating the Azure instance.#

   1. Configure environment variables for the instance.

      NAME=my-rhelai-instance
      AZ_LOCATION=eastus
      AZ_RESOURCE_GROUP=<YOUR_AZURE_RESOURCE_GROUP>
      AZ_ADMIN_USERNAME=azureuser
      AZ_VM_SIZE=Standard_ND96isr_H100_v5
      AZ_IMAGE=my-rhelai-image
      SSHPUBKEY=$HOME/.ssh/id_rsa.pub
      DISK_SIZE=1024

4. Launch the RHEL AI instance by running the following command:

   $ az vm create \
   --resource-group $AZ_RESOURCE_GROUP \
   --name ${NAME} \
   --image ${AZ_IMAGE} \
   --size ${AZ_VM_SIZE} \
   --location ${AZ_LOCATION} \
   --admin-username ${AZ_ADMIN_USERNAME} \
   --ssh-key-values @$SSHPUBKEY \
   --authentication-type ssh \
   --nic-delete-option Delete \
   --accelerated-networking true \
   --os-disk-size-gb 1024 \
   --os-disk-name ${NAME}-${AZ_LOCATION}