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Deploying Nutanix Enterprise AI (NAI) NVD Reference Application

Version 2.0.0

This version of the NAI deployment is based on the Nutanix Enterprise AI (NAI) v2.0.0 release.

stateDiagram-v2
    direction LR

    state DeployNAI {
        [*] --> DeployNAIAdmin
        DeployNAIAdmin -->  InstallSSLCert
        InstallSSLCert --> DownloadModel
        DownloadModel --> CreateNAI
        CreateNAI --> [*]
    }

    [*] --> PreRequisites
    PreRequisites --> DeployNAI 
    DeployNAI --> TestNAI : next section
    TestNAI --> [*]

Prepare for NAI Deployment

  1. Login to VSC on the jumphost VM, Click on New Folder and name it: nai

  2. Create a new .env file add the following environment variables to the and save it

    export ISTIO_VERSION=_your_istio_version
export KNATIVE_VERSION=_your_knative_version
export KSERVE_VERSION=_your_kserve_version
export KUBE_PROMETHEUS_STACK_VERSION=_your_kube_prometheus_stack_version
export NAI_CORE_VERSION=_your_nai_core_version
export NAI_API_VERSION=_your_nai_api_version

    export ISTIO_VERSION=1.20.8
export KNATIVE_VERSION=1.13.1
export KSERVE_VERSION=v0.14.0
export KUBE_PROMETHEUS_STACK_VERSION=61.3.1
export NAI_CORE_VERSION=v2.0.0
export NAI_API_VERSION=v2.0.0

  3. Run the following commands to source the environment variables

    source $HOME/nai/.env

  4. In VSCode, under the newly created nai folder, click on New File and create file with the following name:

    nai-prepare.sh

    with the following content:

    #!/usr/bin/env bash

set -ex
set -o pipefail

## Deploy Istio
#
helm --insecure-skip-tls-verify=true upgrade --install istio-base base --repo ${INTERNAL_REPO} --version=${ISTIO_VERSION} -n istio-system --create-namespace --wait

helm --insecure-skip-tls-verify=true upgrade --install istiod istiod --repo ${INTERNAL_REPO} --version=${ISTIO_VERSION} -n istio-system \
--set gateways.securityContext.runAsUser=0 \
--set gateways.securityContext.runAsGroup=0 --wait

helm --insecure-skip-tls-verify=true upgrade --install istio-ingressgateway gateway --repo ${INTERNAL_REPO} --version=${ISTIO_VERSION} -n istio-system \
--set securityContext.runAsUser=0 --set securityContext.runAsGroup=0 \
--set containerSecurityContext.runAsUser=0 --set containerSecurityContext.runAsGroup=0 --wait

## Deploy Knative 
#
helm --insecure-skip-tls-verify=true upgrade --install knative-serving-crds nai-knative-serving-crds --repo ${INTERNAL_REPO} --version=${KNATIVE_VERSION} -n knative-serving --create-namespace --wait

helm --insecure-skip-tls-verify=true upgrade --install knative-serving nai-knative-serving --repo ${INTERNAL_REPO} -n knative-serving --version=${KNATIVE_VERSION} --wait


helm --insecure-skip-tls-verify=true upgrade --install knative-istio-controller nai-knative-istio-controller --repo ${INTERNAL_REPO} -n knative-serving --version=${KNATIVE_VERSION} --wait

# Patch configurations stored in configmaps
#
kubectl patch configmap config-features -n knative-serving -p '{"data":{"kubernetes.podspec-nodeselector":"enabled"}}'

kubectl patch configmap config-autoscaler -n knative-serving -p '{"data":{"enable-scale-to-zero":"false"}}'

kubectl patch configmap  config-domain -n knative-serving --type merge -p '{"data":{"example.com":""}}'

## Deploy Kserve
#
helm --insecure-skip-tls-verify=true upgrade --install kserve-crd kserve-crd --repo ${INTERNAL_REPO} --version=${KSERVE_VERSION} -n kserve --create-namespace

  5. Run the script from the Terminal

    chmod +x $HOME/nai/nai-prepare.sh
$HOME/nai/nai-prepare.sh

    Release "istiod" has been upgraded. Happy Helming!
NAME: istiod
LAST DEPLOYED: Tue Oct 15 02:01:58 2024
NAMESPACE: istio-system
STATUS: deployed
REVISION: 2
TEST SUITE: None
NOTES:
"istiod" successfully installed!

NAME: istio-ingressgateway
LAST DEPLOYED: Tue Oct 15 02:02:01 2024
NAMESPACE: istio-system
STATUS: deployed

NAME: knative-serving-crds
LAST DEPLOYED: Tue Oct 15 02:02:03 2024
NAMESPACE: knative-serving
STATUS: deployed

NAME: knative-serving
LAST DEPLOYED: Tue Oct 15 02:02:05 2024
NAMESPACE: knative-serving
STATUS: deployed

NAME: kserve-crd
LAST DEPLOYED: Tue Oct 15 02:02:16 2024
NAMESPACE: kserve
STATUS: deployed

NAME: kserve
LAST DEPLOYED: Tue Oct 15 02:02:19 2024
NAMESPACE: kserve
STATUS: deployed
    Check helm deployment status

    Check the status of the nai helm deployments using the following command:

    helm list -n istio-system
helm list -n kserve
helm list -n knative-serving

  6. Validate if the resources are running in the following namespaces.

    • istio-system,
    • knative-serving, and
    • kserve
    kubectl get po -n istio-system
k get po -n kserve
k get po -n knative-serving

    $ k get po -n istio-system
NAME                                    READY   STATUS    RESTARTS   AGE
istio-ingressgateway-6675867d85-qzrpq   1/1     Running   0          26d
istiod-6d96569c9b-2dww4                 1/1     Running   0          26d

$ k get po -n kserve
NAME                                         READY   STATUS    RESTARTS   AGE
kserve-controller-manager-6654f69d5c-45n64   2/2     Running   0          26d

$ k get po -n knative-serving
NAME                                   READY   STATUS    RESTARTS   AGE
activator-58db57894b-g2nx8             1/1     Running   0          26d
autoscaler-76f95fff78-c8q9m            1/1     Running   0          26d
controller-7dd875844b-4clqb            1/1     Running   0          26d
net-istio-controller-57486f879-85vml   1/1     Running   0          26d
net-istio-webhook-7ccdbcb557-54dn5     1/1     Running   0          26d
webhook-d8674645d-mscsc                1/1     Running   0          26d

Deploy NAI

We will use the Docker login credentials we created in the previous section to download the NAI Docker images.

Change the Docker login credentials

The following Docker based environment variable values need to be changed from your own Docker environment variables to the credentials downloaded from Nutanix Portal.

  • $DOCKER_USERNAME
  • $DOCKER_PASSWORD

  1. Open $HOME/.env file in VSCode

  2. Add (append) the following environment variables and save it

    export DOCKER_USERNAME=_GA_release_docker_username
export DOCKER_PASSWORD=_GA_release_docker_password
export NAI_CORE_VERSION=_GA_release_nai_core_version

    export DOCKER_USERNAME=ntnxsvcgpt
export DOCKER_PASSWORD=dckr_pat_xxxxxxxxxxxxxxxxxxxxxxxx
export NAI_CORE_VERSION=v2.0.0

  3. Source the environment variables (if not done so already)

    source $HOME/.env

  4. In VSCode Explorer pane, browse to $HOME/nai folder

  5. Click on New File and create file with the following name:

    iep-values-nkp.yaml

    with the following content:

    # nai-monitoring stack values for nai-monitoring stack deployment in NKE environment
naiMonitoring:
  ## Component scraping node exporter
  ##
  nodeExporter:
    serviceMonitor:
      enabled: true
      endpoint:
        port: http-metrics
        scheme: http
        targetPort: 9100
      namespaceSelector:
        matchNames:
        - kommander
      serviceSelector:
        matchLabels:
          app.kubernetes.io/name: prometheus-node-exporter
          app.kubernetes.io/component: metrics
          app.kubernetes.io/version: 1.8.1
  ## Component scraping dcgm exporter
  ##
  dcgmExporter:
    podLevelMetrics: true
    serviceMonitor:
      enabled: true
      endpoint:
        targetPort: 9400
      namespaceSelector:
        matchNames:
        - kommander
      serviceSelector:
        matchLabels:
          app: nvidia-dcgm-exporter

  6. In VSCode, Under $HOME/nai folder, click on New File and create a file with the following name:

    nai-deploy.sh

    with the following content:

    #!/usr/bin/env bash

set -ex
set -o pipefail

helm repo add ntnx-charts https://nutanix.github.io/helm-releases
helm repo update ntnx-charts

#NAI-core
helm upgrade --install nai-core ntnx-charts/nai-core --version=$NAI_CORE_VERSION -n nai-system --create-namespace --wait \
--set imagePullSecret.credentials.username=$DOCKER_USERNAME \
--set imagePullSecret.credentials.password=$DOCKER_PASSWORD \
--insecure-skip-tls-verify \
-f iep-values-nkp.yaml

  7. Run the following command to deploy NAI

    $HOME/nai/nai-deploy.sh

    $HOME/nai/nai-deploy.sh 

+ set -o pipefail
+ helm repo add ntnx-charts https://nutanix.github.io/helm-releases
"ntnx-charts" already exists with the same configuration, skipping
+ helm repo update ntnx-charts
Hang tight while we grab the latest from your chart repositories...
...Successfully got an update from the "ntnx-charts" chart repository
Update Complete. ⎈Happy Helming!⎈
helm upgrade --install nai-core ntnx-charts/nai-core --version=$NAI_CORE_VERSION -n nai-system --create-namespace --wait \
--set imagePullSecret.credentials.username=$DOCKER_USERNAME \
--set imagePullSecret.credentials.password=$DOCKER_PASSWORD \
--insecure-skip-tls-verify \
-f iep-values-nkp.yaml
Release "nai-core" has been upgraded. Happy Helming!
NAME: nai-core
LAST DEPLOYED: Mon Sep 16 22:07:24 2024
NAMESPACE: nai-system
STATUS: deployed
REVISION: 7
TEST SUITE: None

  8. Verify that the NAI Core Pods are running and healthy

    kubens nai-system
kubectl get po,deploy

    $ kubens nai-system
✔ Active namespace is "nai-system"

$ kubectl get po,deploy

NAME                                            READY   STATUS      RESTARTS   AGE
pod/nai-api-55c665dd67-746b9                    1/1     Running     0          5d1h
pod/nai-api-db-migrate-fdz96-xtmxk              0/1     Completed   0          40h
pod/nai-db-789945b4df-lb4sd                     1/1     Running     0          43h
pod/nai-iep-model-controller-84ff5b5b87-6jst9   1/1     Running     0          5d8h
pod/nai-ui-7fc65fc6ff-clcjl                     1/1     Running     0          5d8h
pod/prometheus-nai-0                            2/2     Running     0          43h

NAME                                       READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/nai-api                    1/1     1            1           5d8h
deployment.apps/nai-db                     1/1     1            1           5d8h
deployment.apps/nai-iep-model-controller   1/1     1            1           5d8h
deployment.apps/nai-ui                     1/1     1            1           5d8h

Install SSL Certificate

In this section we will install SSL Certificate to access the NAI UI. This is required as the endpoint will only work with a ssl endpoint with a valid certificate.

NAI UI is accessible using the Ingress Gateway.

The following steps show how cert-manager can be used to generate a self signed certificate using the default selfsigned-issuer present in the cluster.

If you are using Public Certificate Authority (CA) for NAI SSL Certificate

If an organization generates certificates using a different mechanism then obtain the certificate + key and create a kubernetes secret manually using the following command:

kubectl -n istio-system create secret tls nai-cert --cert=path/to/nai.crt --key=path/to/nai.key

Skip the steps in this section to create a self-signed certificate resource.

  1. Get the Ingress host using the following command:

    INGRESS_HOST=$(kubectl get svc -n istio-system istio-ingressgateway -o jsonpath='{.status.loadBalancer.ingress[0].ip}')

  2. Get the value of INGRESS_HOST environment variable

    echo $INGRESS_HOST

    10.x.x.216

  3. We will use the command output e.g: 10.x.x.216 as the IP address for NAI as reserved in this section

  4. Construct the FQDN of NAI UI using nip.io and we will use this FQDN as the certificate's Common Name (CN).

    nai.${INGRESS_HOST}.nip.io

    nai.10.x.x.216.nip.io

  5. Create the ingress resource certificate using the following command:

    cat << EOF | k apply -f -
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: nai-cert
  namespace: istio-system
spec:
  issuerRef:
    name: selfsigned-issuer
    kind: ClusterIssuer
  secretName: nai-cert
  commonName: nai.${INGRESS_HOST}.nip.io
  dnsNames:
  - nai.${INGRESS_HOST}.nip.io
  ipAddresses:
  - ${INGRESS_HOST}
EOF

  6. Create the certificate using the following command

    kubectl apply -f $HOME/airgap-nai/nai-cert.yaml

  7. Patch the ingress gateway's IP address to the certificate file.

    kubectl patch gateway -n knative-serving knative-ingress-gateway --type merge --patch-file=/dev/stdin <<EOF
spec:
  servers:
  - hosts:
    - '*'
    port:
      name: https
      number: 443
      protocol: HTTPS
    tls:
      mode: SIMPLE
      credentialName: nai-cert
EOF

    gateway.networking.istio.io/knative-ingress-gateway patched

Accessing the UI

  1. In a browser, open the following URL to connect to the NAI UI

    https://nai.10.x.x.216.nip.io

  2. Change the password for the admin user

  3. Login using admin user and password.

Download Model

We will download and user llama3 8B model which we sized for in the previous section.

  1. In the NAI GUI, go to Models
  2. Click on Import Model from Hugging Face
  3. Choose the meta-llama/Meta-Llama-3.1-8B-Instruct model

  4. Input your Hugging Face token that was created in the previous section and click Import

  5. Provide the Model Instance Name as Meta-Llama-3.1-8B-Instruct and click Import

  6. Go to VSC Terminal to monitor the download

    Get jobs in nai-admin namespace
    kubens nai-admin

kubectl get jobs
    Validate creation of pods and PVC
    kubectl get po,pvc
    Verify download of model using pod logs
    kubectl logs -f _pod_associated_with_job

    Get jobs in nai-admin namespace
    kubens nai-admin

✔ Active namespace is "nai-admin"

kubectl get jobs

NAME                                       COMPLETIONS   DURATION   AGE
nai-c0d6ca61-1629-43d2-b57a-9f-model-job   0/1           4m56s      4m56
    Validate creation of pods and PVC
    kubectl get po,pvc

NAME                                             READY   STATUS    RESTARTS   AGE
nai-c0d6ca61-1629-43d2-b57a-9f-model-job-9nmff   1/1     Running   0          4m49s

NAME                                       STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS      VOLUMEATTRIBUTESCLASS   AGE
nai-c0d6ca61-1629-43d2-b57a-9f-pvc-claim   Bound    pvc-a63d27a4-2541-4293-b680-514b8b890fe0   28Gi       RWX            nai-nfs-storage   <unset>                 2d
    Verify download of model using pod logs
    kubectl logs -f nai-c0d6ca61-1629-43d2-b57a-9f-model-job-9nmff 

/venv/lib/python3.9/site-packages/huggingface_hub/file_download.py:983: UserWarning: Not enough free disk space to download the file. The expected file size is: 0.05 MB. The target location /data/model-files only has 0.00 MB free disk space.
warnings.warn(
tokenizer_config.json: 100%|██████████| 51.0k/51.0k [00:00<00:00, 3.26MB/s]
tokenizer.json: 100%|██████████| 9.09M/9.09M [00:00<00:00, 35.0MB/s]<00:30, 150MB/s]
model-00004-of-00004.safetensors: 100%|██████████| 1.17G/1.17G [00:12<00:00, 94.1MB/s]
model-00001-of-00004.safetensors: 100%|██████████| 4.98G/4.98G [04:23<00:00, 18.9MB/s]
model-00003-of-00004.safetensors: 100%|██████████| 4.92G/4.92G [04:33<00:00, 18.0MB/s]
model-00002-of-00004.safetensors: 100%|██████████| 5.00G/5.00G [04:47<00:00, 17.4MB/s]
Fetching 16 files: 100%|██████████| 16/16 [05:42<00:00, 21.43s/it]:33<00:52, 9.33MB/s]
## Successfully downloaded model_files|██████████| 5.00G/5.00G [04:47<00:00, 110MB/s] 

Deleting directory : /data/hf_cache

  7. Optional - verify the events in the namespace for the pvc creation 

    k get events | awk '{print $1, $3}'

    $ k get events | awk '{print $1, $3}'

3m43s Scheduled
3m43s SuccessfulAttachVolume
3m36s Pulling
3m29s Pulled
3m29s Created
3m29s Started
3m43s SuccessfulCreate
90s   Completed
3m53s Provisioning
3m53s ExternalProvisioning
3m45s ProvisioningSucceeded
3m53s PvcCreateSuccessful
3m48s PvcNotBound
3m43s ModelProcessorJobActive
90s   ModelProcessorJobComplete

The model is downloaded to the Nutanix Files pvc volume.

After a successful model import, you will see it in Active status in the NAI UI under Models menu

Create and Test Inference Endpoint

In this section we will create an inference endpoint using the downloaded model.

  1. Navigate to Inference Endpoints menu and click on Create Endpoint button

  2. Fill the following details:

    • Endpoint Name: llama-8b
    • Model Instance Name: Meta-LLaMA-8B-Instruct
    • Use GPUs for running the models : Checked
    • No of GPUs (per instance):
    • GPU Card: NVIDIA-L40S (or other available GPU)
    • No of Instances: 1
    • API Keys: Create a new API key or use an existing one

  3. Click on Create

  4. Monitor the nai-admin namespace to check if the services are coming up

    kubens nai-admin
kubectl get po,deploy

    kubens nai-admin
get po,deploy
NAME                                                     READY   STATUS        RESTARTS   AGE
pod/llama8b-predictor-00001-deployment-9ffd786db-6wkzt   2/2     Running       0          71m

NAME                                                 READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/llama8b-predictor-00001-deployment   1/1     1            0           3d17h

  5. Check the events in the nai-admin namespace for resource usage to make sure all 

    kubectl get events -n nai-admin --sort-by='.lastTimestamp' | awk '{print $1, $3, $5}'

    $ kubectl get events -n nai-admin --sort-by='.lastTimestamp' | awk '{print $1, $3, $5}'

110s FinalizerUpdate Updated
110s FinalizerUpdate Updated
110s RevisionReady Revision
110s ConfigurationReady Configuration
110s LatestReadyUpdate LatestReadyRevisionName
110s Created Created
110s Created Created
110s Created Created
110s InferenceServiceReady InferenceService
110s Created Created

  6. Once the services are running, check the status of the inference service

    kubectl get isvc

    kubectl get isvc

NAME      URL                                          READY   PREV   LATEST   PREVROLLEDOUTREVISION   LATESTREADYREVISION       AGE
llama8b   http://llama8b.nai-admin.svc.cluster.local   True           100                              llama8b-predictor-00001   3d17h