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Deploying Nutanix Enterprise AI (NAI) NVD Reference Application

Version 2.6.0

This version of the NAI deployment is based on the Nutanix Enterprise AI (NAI) v2.6.0 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

Early Access(EA)/Technical Preview(TP) Software with NAI v2.6.0

In this lab, we will deploy EA and TP version of the following software to test the following:

  • Nutanix Enterprise AI

    • Unified Endpoints - multiple endpoints for HA and token-based rate limiting
    • Providers - Add remote endpoints from providers to utilize their models in Nutanix Enterprise AI workloads.

Info

Changes in NAI v2.6.0

  • Kserve is of at least of v0.15.0
  • Cert-manager is at least of v1.17.2
  • OpenTelemetry operator is at least of v0.102.0
  • Envoy Gateway is at least of v1.6.3

Enable Pre-requisite Applications

Prometheus and Cert Manager

The following pre-requisite applications will be enabled on NKP GUI:

Note

In this lab, we will be using the Management Cluster Workspace to deploy our Nutanix Enterprise AI (NAI)

However, in a customer environment, it is recommended to use a separate workload NKP cluster.

Info

The helm charts and the container images for these applications are stored in internal Harbor registry. These images got uploaded to Harbor at the time of install NKE in this section.

  1. In the NKP GUI, Go to Clusters
  2. Click on Management Cluster Workspace
  3. Go to Applications

  4. Search and enable the following applications: follow this order to install dependencies for NAI application

    • Kube-prometheus-stack: version 71.0.0 or later (pre-installed on NKP cluster)
    • Cert-manager - v1.17.2

    Cert-manager - v1.17.2

    The following application are pre-installed on NKP cluster with Pro license

    • Cert Manager v1.17.2 or higher

    Check if Cert Manager is installed (pre-installed on NKP cluster if license is installed)

    kubectl get deploy -n cert-manager

    $ kubectl get deploy -n cert-manager

NAME                      READY   UP-TO-DATE   AVAILABLE   AGE
cert-manager              1/1     1            1           145m
cert-manager-cainjector   1/1     1            1           145m
cert-manager-webhook      1/1     1            1           145m

    If not installed, use the following command or NKP Applications GUI to install it

    kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.17.2/cert-manager.yaml

The following pre-requisite applications will be enabled from the command line on the jumphost VM.

Envoy Gateway

  1. Login to VSC on the jumphost VM, append the following environment variables to the $HOME\airgap-nai\.env file and save it

    export NAI_USER=_your_desired_nai_ui_username
export NAI_TEMP_PASS=_your_desired_nai_ui_password # At least 8 characters
export REGISTRY=_your_private_registry
export REGISTRY_USERNAME=admin
export REGISTRY_PASSWORD=_your_private_registry_password
export REGISTRY_EMAIL=admin
export IMAGE_PULL_SECRET=_your_desired_pull_secret_name

    export NAI_USER=admin
export NAI_TEMP_PASS=_XXXXXXXXX # At least 8 characters
export REGISTRY=harbor.10.x.x.x.nip.io
export REGISTRY_USERNAME=admin
export REGISTRY_PASSWORD=XXXXXXXXXXX
export REGISTRY_EMAIL=admin
export IMAGE_PULL_SECRET=private-regcred

  2. IN VSC,go to Terminal and run the following commands to source the environment variables

    source $HOME/airgap-nai/.env

  3. Create Kubernetes namespaces and docker-registry secrets for Envoy Gateway System

    kubectl create namespace envoy-gateway-system --dry-run=client -o yaml | kubectl apply -f -

    kubectl create secret docker-registry ${IMAGE_PULL_SECRET} \
  --docker-server=${REGISTRY} \
  --docker-username=${REGISTRY_USERNAME} \
  --docker-password=${REGISTRY_PASSWORD} \
  --docker-email=${REGISTRY_EMAIL} \
  -n envoy-gateway-system \
  --dry-run=client -o yaml | kubectl apply -f -


    namespace/envoy-gateway-system created

    secret/private-regcred created

  4. Enable Envoy Gateway CRDs v1.6.3 in AI gateway mode

    helm template eg oci://${REGISTRY}/nutanix/gateway-crds-helm \
  --version v1.6.3 \
  --set crds.gatewayAPI.enabled=true \
  --set crds.envoyGateway.enabled=true \
  | kubectl apply --server-side --force-conflicts -f -

    helm template eg oci://harbor.10.x.x.x.nip.io/nutanix/gateway-crds-helm \
  --version v1.6.3 \
  --set crds.gatewayAPI.enabled=true \
  --set crds.envoyGateway.enabled=true \
  | kubectl apply --server-side --force-conflicts -f -

    Pulled: harbor.10.x.x.x.nip.io/nutanix/gateway-crds-helm:v1.6.3
Digest: sha256:55a2c0a4974cc2a83b9e144ec5b9ac687f0ae1b9d26ec178762184d0185db096
customresourcedefinition.apiextensions.k8s.io/backendtlspolicies.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/gatewayclasses.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/gateways.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/grpcroutes.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/httproutes.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/referencegrants.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/tcproutes.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/tlsroutes.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/udproutes.gateway.networking.k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/xbackendtrafficpolicies.gateway.networking.x-k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/xlistenersets.gateway.networking.x-k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/xmeshes.gateway.networking.x-k8s.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/backends.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/backendtrafficpolicies.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/clienttrafficpolicies.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/envoyextensionpolicies.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/envoypatchpolicies.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/envoyproxies.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/httproutefilters.gateway.envoyproxy.io serverside-applied
customresourcedefinition.apiextensions.k8s.io/securitypolicies.gateway.envoyproxy.io serverside-applied

  5. Prepare values file for configuring advanced features for envoy gateway in AI gateway mode.

    cat << EOF > eg-config-for-gateway-mode.yaml
# This file configures Envoy Gateway for AI Gateway mode with rate limiting

config:
  envoyGateway:
    gateway:
      controllerName: "gateway.envoyproxy.io/gatewayclass-controller"
    logging:
      level:
        default: "info"
    provider:
      kubernetes:
        rateLimitDeployment:
          container:
            image: "${REGISTRY}/nutanix/nai-ratelimit:99d85510"
          patch:
            type: "StrategicMerge"
            value:
              spec:
                template:
                  spec:
                    containers:
                      - imagePullPolicy: "IfNotPresent"
                        name: "envoy-ratelimit"
                        image: "${REGISTRY}/nutanix/nai-ratelimit:99d85510"
      type: "Kubernetes"
    extensionApis:
      enableEnvoyPatchPolicy: true
      enableBackend: true
    extensionManager:
      maxMessageSize: 11Mi
      backendResources:
        - group: inference.networking.k8s.io
          kind: InferencePool
          version: v1
      hooks:
        xdsTranslator:
          translation:
            listener:
              includeAll: true
            route:
              includeAll: true
            cluster:
              includeAll: true
            secret:
              includeAll: true
          post:
            - "Translation"
            - "Cluster"
            - "Route"
      service:
        fqdn:
          hostname: "ai-gateway-controller.nai-system.svc.cluster.local"
          port: 1063
    rateLimit:
      backend:
        type: "Redis"
        redis:
          url: "redis-sentinel.nai-system.svc.cluster.local:6379"
EOF

    cat << EOF > eg-config-for-gateway-mode.yaml
# This file configures Envoy Gateway for AI Gateway mode with rate limiting

config:
  envoyGateway:
    gateway:
      controllerName: "gateway.envoyproxy.io/gatewayclass-controller"
    logging:
      level:
        default: "info"
    provider:
      kubernetes:
        rateLimitDeployment:
          container:
            image: "harbor.10.x.x.x.nip.io/nutanix/nai-ratelimit:99d85510"
          patch:
            type: "StrategicMerge"
            value:
              spec:
                template:
                  spec:
                    containers:
                      - imagePullPolicy: "IfNotPresent"
                        name: "envoy-ratelimit"
                        image: "harbor.10.x.x.x.nip.io/nutanix/nai-ratelimit:99d85510"
      type: "Kubernetes"
    extensionApis:
      enableEnvoyPatchPolicy: true
      enableBackend: true
    extensionManager:
      maxMessageSize: 11Mi
      backendResources:
        - group: inference.networking.k8s.io
          kind: InferencePool
          version: v1
      hooks:
        xdsTranslator:
          translation:
            listener:
              includeAll: true
            route:
              includeAll: true
            cluster:
              includeAll: true
            secret:
              includeAll: true
          post:
            - "Translation"
            - "Cluster"
            - "Route"
      service:
        fqdn:
          hostname: "ai-gateway-controller.nai-system.svc.cluster.local"
          port: 1063
    rateLimit:
      backend:
        type: "Redis"
        redis:
          url: "redis-sentinel.nai-system.svc.cluster.local:6379"
EOF

  6. Enable Envoy Gateway v1.6.3 in AI gateway mode

    helm upgrade --install eg oci://${REGISTRY}/nutanix/gateway-helm \
  --version v1.6.3 \
  -n envoy-gateway-system \
  --create-namespace --wait \
  --set global.images.envoyGateway.image=${REGISTRY}/nutanix/nai-gateway:v1.6.3 \
  --set global.images.ratelimit.image=${REGISTRY}/nutanix/nai-ratelimit:99d85510 \
  --set global.imagePullSecrets[0].name=${IMAGE_PULL_SECRET} \
  -f ./eg-config-for-gateway-mode.yaml

    helm upgrade --install eg oci://harbor.10.x.x.x.nip.io/nutanix/gateway-helm \
  --version v1.6.3 \
  -n envoy-gateway-system \
  --create-namespace --wait \
  --set global.images.envoyGateway.image=harbor.10.x.x.x.nip.io/nutanix/nai-gateway:v1.6.3 \
  --set global.images.ratelimit.image=harbor.10.x.x.x.nip.io/nutanix/nai-ratelimit:99d85510 \
  --set global.imagePullSecrets[0].name=private-regcred \
  -f ./eg-config-for-gateway-mode.yaml

    Release "eg" does not exist. Installing it now.
Pulled: harbor.10.x.x.x.nip.io/nutanix/gateway-helm:v1.6.3
Digest: sha256:924799edea136fe405ea37480f5d5e65a81c6b01e3cbe53bf2ab5cde935ef0d6
NAME: eg
LAST DEPLOYED: Tue Apr  7 07:04:05 2026
NAMESPACE: envoy-gateway-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

  7. Create an EnvoyProxy custom resource to configure the Envoy data plane with private registry access:

    cat <<EOF | kubectl apply -f -
apiVersion: gateway.envoyproxy.io/v1alpha1
kind: EnvoyProxy
metadata:
  name: nai-envoyproxy
  namespace: envoy-gateway-system
spec:
  provider:
    type: Kubernetes
    kubernetes:
      envoyDeployment:
        pod:
          imagePullSecrets:
            - name: ${IMAGE_PULL_SECRET}
        container:
          image: "${REGISTRY}/nutanix/nai-envoy:distroless-v1.36.4"
EOF

    cat <<EOF | kubectl apply -f -
apiVersion: gateway.envoyproxy.io/v1alpha1
kind: EnvoyProxy
metadata:
  name: nai-envoyproxy
  namespace: envoy-gateway-system
provider:
kubernetes:
  envoyDeployment:
    pod:
      imagePullSecrets:
      - name: private-regcred
    container:
      image: harbor.10.x.x.x/nip.io/nutanix/nai-envoy:distroless-v1.36.4
EOF

    envoyproxy.gateway.envoyproxy.io/nai-envoyproxy created

  8. Check if Envoy Gateway resources are ready

    kubectl wait --timeout=5m -n envoy-gateway-system deployment/envoy-gateway --for=condition=Available

    deployment.apps/envoy-gateway condition met

Kserve

  1. Create kubernetes namespaces and docker-registry secrets for KServe

    kubectl create namespace kserve --dry-run=client -o yaml | kubectl apply -f -

    kubectl create secret docker-registry ${IMAGE_PULL_SECRET} \
  --docker-server=${REGISTRY} \
  --docker-username=${REGISTRY_USERNAME} \
  --docker-password=${REGISTRY_PASSWORD} \
  --docker-email=${REGISTRY_EMAIL} \
  -n kserve \
  --dry-run=client -o yaml | kubectl apply -f -


    namespace/kserve created

    secret/private-regcred created

  2. Run the Kserve CRD installation

    helm upgrade --install kserve-crd \
  oci://${REGISTRY}/kserve-crd \
  --version v0.15.0 \
  -n kserve \
  --create-namespace 

    helm upgrade --install kserve-crd \
  oci://harbor.10.x.x.x.nip.io/nutanix/kserve-crd \
  --version v0.15.0 \
  -n kserve \
  --create-namespace

    Release "kserve-crd" does not exist. Installing it now.
Pulled: harbor.10.x.x.x.nip.io/nutanix/kserve-crd:v0.15.0
Digest: sha256:01533cdda82c767fdd39172846f04c5185011eab2769b2c3d727bdd0f244a8f5
NAME: kserve-crd
LAST DEPLOYED: Tue Apr  7 07:10:02 2026
NAMESPACE: kserve
STATUS: deployed
REVISION: 1
TEST SUITE: None

  3. Run the Kserve installation

    helm upgrade --install kserve \
  oci://${REGISTRY}/kserve \
  --version v0.15.0 \
  -n kserve \
  --set controller.image.repository=${REGISTRY}/kserve-controller \
  --set controller.image.tag=v0.15.0 \
  --set kserve.controller.deploymentMode=RawDeployment \
  --set kserve.controller.gateway.disableIngressCreation=true

    helm upgrade --install kserve \
  oci://harbor.10.x.x.x.nip.io/kserve \
  --version v0.15.0 \
  -n kserve \
  --set controller.image.repository=harbor.10.x.x.x.nip.io/kserve-controller \
  --set controller.image.tag=v0.15.0 \
  --set kserve.controller.deploymentMode=RawDeployment \
  --set kserve.controller.gateway.disableIngressCreation=true

    Pulled: harbor.10.x.x.134.nip.io/nkp/kserve:v0.15.0
Digest: sha256:cafd90ab1d91a54a28c1ff2761d976bdda0bb173675ef392a16ac250b044d15f
I0226 01:59:34.229355  555781 warnings.go:110] "Warning: spec.privateKey.rotationPolicy: In cert-manager >= v1.18.0, the default value changed from `Never` to `Always`."
NAME: kserve
LAST DEPLOYED: Tue Apr  7 07:10:05 2026
NAMESPACE: kserve
STATUS: deployed
REVISION: 1
TEST SUITE: None

OpenTelemetry

  1. Create kubernetes namespaces and docker-registry secrets for OpenTelemetry

    kubectl create namespace opentelemetry --dry-run=client -o yaml | kubectl apply -f -

    kubectl create secret docker-registry ${IMAGE_PULL_SECRET} \
  --docker-server=${REGISTRY} \
  --docker-username=${REGISTRY_USERNAME} \
  --docker-password=${REGISTRY_PASSWORD} \
  --docker-email=${REGISTRY_EMAIL} \
  -n opentelemetry \
  --dry-run=client -o yaml | kubectl apply -f -


    namespace/opentelemetry created

    secret/private-regcred created

  2. Run the OpenTelemetry operator installation

    helm upgrade --install opentelemetry-operator oci://${REGISTRY}/nutanix/opentelemetry-operator \
  --version 0.102.0 \
  -n opentelemetry --create-namespace --wait \
  --set manager.image.repository=${REGISTRY}/nutanix/nai-opentelemetry-operator \
  --set manager.collectorImage.repository=${REGISTRY}/nutanix/nai-opentelemetry-collector-k8s \
  --set kubeRBACProxy.image.repository=${REGISTRY}/nutanix/nai-kube-rbac-proxy

    helm upgrade --install opentelemetry-operator oci://harbor.10.x.x.134.nip.io/opentelemetry-operator \
  --version 0.102.0 \
  -n opentelemetry --create-namespace --wait \
  --set manager.image.repository=harbor.10.x.x.134.nip.io/nutanix/nai-opentelemetry-operator \
  --set manager.collectorImage.repository=harbor.10.x.x.134.nip.io/nutanix/nai-opentelemetry-collector-k8s \
  --set kubeRBACProxy.image.repository=harbor.10.x.x.134.nip.io/nutanix/nai-kube-rbac-proxy 

    Release "opentelemetry-operator" does not exist. Installing it now.
Pulled: harbor.10.x.x.134/nutanix/opentelemetry-operator:0.102.0
Digest: sha256:1616912e98fbce5236707de9f7c8b91a98c9ecef6c207f625d9d5fa7683a31c8
I0407 08:26:51.082158 1388823 warnings.go:107] "Warning: spec.privateKey.rotationPolicy: In cert-manager >= v1.18.0, the default value changed from `Never` to `Always`."
NAME: opentelemetry-operator
LAST DEPLOYED: Tue Apr  7 08:26:49 2026
NAMESPACE: opentelemetry
STATUS: deployed
REVISION: 1
NOTES:
[WARNING] No resource limits or requests were set. Consider setter resource requests and limits via the `resources` field.
    Check helm deployment status

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

    helm list -n envoy-gateway-system
helm list -n kserve
helm list -n opentelemetry

Deploy NAI

  1. Append the following environment variables to the $HOME\airgap-nai\.env file and save it

    export NAI_API_RWX_STORAGECLASS=_desired_rwx_files_storageclass_created_in_previous_section
export NAI_DEFAULT_RWO_STORAGECLASS=_desired_rwo_volume_storageclass
export NKP_WORKSPACE_NAMESPACE=_desired_nkp_workspace # (1)!

    1. Get the values for the NKP workspace using the following commands:

      nkp get workspaces
# Get the names of workspaces
# NAME                    NAMESPACE                   
# default-workspace       kommander-default-workspace
# kommander-workspace     kommander 

nkp get clusters -w kommander-workspace
# Ensure the target cluster is in the correct workspace
# WORKSPACE               NAME            KUBECONFIG                              STATUS 
# kommander-workspace     host-cluster    kommander-self-attach-kubeconfig        Joined

    export NAI_API_RWX_STORAGECLASS=nai-nfs-storage
export NAI_DEFAULT_RWO_STORAGECLASS=nutanix-volume
export NKP_WORKSPACE_NAMESPACE=kommander-workspace #(1)!
    1. Use kommander-workspace if this is where your cluster is deployed

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

    source $HOME/airgap-nai/.env

  3. In VSCode Explorer pane, browse to $HOME/airgap-nai folder

  4. Run the following command to create a helm values file:

    cat <<EOF > darksite-nai-operators.yaml
global:
  imagePullSecrets:
    - name: ${IMAGE_PULL_SECRET}

naiRedis:
  naiRedisImage:
    name: ${REGISTRY}/nutanix/nai-redis

naiJobs:
  naiJobsImage:
    image: ${REGISTRY}/nutanix/nai-jobs

nai-clickhouse-operator:
  operator:
    image:
      registry: ${REGISTRY}
      repository: nutanix/nai-clickhouse-operator
  metrics:
    image:
      registry: ${REGISTRY}
      repository: nutanix/nai-clickhouse-metrics-exporter

ai-gateway-helm:
  extProc:
    image: 
      repository: ${REGISTRY}/nutanix/nai-ai-gateway-extproc
  controller:
    image:
      repository: ${REGISTRY}/nutanix/nai-ai-gateway-controller
EOF

    global:
  imagePullSecrets:
    - name: private-regcred

naiRedis:
  naiRedisImage:
    name: harbor.10.x.x.134.nip.io/nutanix/nai-redis

naiJobs:
  naiJobsImage:
    image: harbor.10.x.x.134.nip.io/nutanix/nai-jobs

nai-clickhouse-operator:
  operator:
    image:
      registry: harbor.10.x.x.134.nip.io
      repository: nutanix/nai-clickhouse-operator
  metrics:
    image:
      registry: harbor.10.x.x.134.nip.io
      repository: nutanix/nai-clickhouse-metrics-exporter

ai-gateway-helm:
  extProc:
    image: 
      repository: harbor.10.x.x.134.nip.io/nutanix/nai-ai-gateway-extproc
  controller:
    image:
      repository: harbor.10.x.x.134.nip.io/nutanix/nai-ai-gateway-controller

  5. Install nai-operators helm chart in the nai-system namespace 

    helm upgrade --install nai-operators oci://${REGISTRY}/nutanix/nai-operators \
  --version=2.6.0 \
  -n nai-system --create-namespace --wait \
  --set "naiAIGateway.enabled=true" \
  --insecure-skip-tls-verify \
  -f ./darksite-nai-operators.yaml

    helm upgrade --install nai-operators oci://harbor.10.x.x.134.nip.io/nkp/nai-operators \
  --version=2.6.0 \
  -n nai-system --create-namespace --wait \
  --set "naiAIGateway.enabled=true" \
  --insecure-skip-tls-verify \
  -f ./darksite-nai-operators.yaml

    Release "nai-operators" does not exist. Installing it now.
Pulled: harbor.10.x.x.134/nutanix/nai-operators:2.6.0
Digest: sha256:06d4b66a5d64add26bc6cc0f0864482ddabcdf735e05ab2a5ba347fcf4deae9b
I0407 07:33:29.955493 1376860 warnings.go:107] "Warning: spec.template.spec.containers[1].ports[0]: duplicate port name \"metrics\" with spec.template.spec.containers[0].ports[0], services and probes that select ports by name will use spec.template.spec.containers[0].ports[0]"
I0407 07:33:29.976628 1376860 warnings.go:107] "Warning: spec.privateKey.rotationPolicy: In cert-manager >= v1.18.0, the default value changed from `Never` to `Always`."
NAME: nai-operators
LAST DEPLOYED: Tue Apr  7 07:33:28 2026
NAMESPACE: nai-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

  6. Verify all three nai-operator pods are running. Note that ai-gateway-controller- pod is also running as we are installing AI Gateway features

    kubens nai-system
kubectl get pod

    kubectl get po

NAME                                                    READY   STATUS    RESTARTS   AGE
ai-gateway-controller-fc568fdc-hpsfv                    1/1     Running   0          30s
nai-operators-nai-clickhouse-operator-86d684894-b6swh   2/2     Running   0          30s
redis-standalone-6dd5f64ff5-98r5b                       2/2     Running   0          30s

  7. Run the following command to create a helm values file:

    cat <<EOF > darksite-nai-core.yaml
global:
  imagePullSecrets:
    - name: ${IMAGE_PULL_SECRET}

defaultStorageClassName: ${NAI_DEFAULT_RWO_STORAGECLASS}
naiIepOperator:
  iepOperatorImage:
    image: ${REGISTRY}/nutanix/nai-iep-operator

  modelProcessorImage:
    image: ${REGISTRY}/nutanix/nai-python-processor

  dataSourceProcessorImage:
    image: ${REGISTRY}/nutanix/nai-python-processor

  finetuneProcessorImage:
    image: ${REGISTRY}/nutanix/nai-finetuning

naiInferenceUi:
  naiUiImage:
    image: ${REGISTRY}/nutanix/nai-inference-ui

naiJobs:
  naiJobsImage:
    image: ${REGISTRY}/nutanix/nai-jobs

naiApi:
  storageClassName: ${NAI_API_RWX_STORAGECLASS}
  naiApiImage:
    image: ${REGISTRY}/nutanix/nai-api
  supportedTGIImage: ${REGISTRY}/nutanix/nai-tgi
  supportedKserveRuntimeImage: ${REGISTRY}/nutanix/nai-kserve-huggingfaceserver
  eppImage: ${REGISTRY}/nutanix/nai-epp-inference-scheduler
  supportedVLLMImage: ${REGISTRY}/nutanix/nai-vllm
  supportedKserveCustomModelServerRuntimeImage: ${REGISTRY}/nutanix/nai-kserve-custom-model-server
  superAdmin:
    username: admin
    password: ${NAI_TEMP_PASS} # At least 8 characters
    # email: admin@nutanix.com
    # firstName: admin

naiDatabase:
  naiDbImage:
    image: ${REGISTRY}/nutanix/nai-postgres:16.1-alpine

naiIam:
  iamProxy:
    image: ${REGISTRY}/nutanix/nai-iam-proxy

  iamProxyControlPlane:
    image: ${REGISTRY}/nutanix/nai-iam-proxy-control-plane

  iamUi:
    image: ${REGISTRY}/nutanix/nai-iam-ui

  iamUserAuthn:
    image: ${REGISTRY}/nutanix/nai-iam-user-authn

  iamThemis:
    image: ${REGISTRY}/nutanix/nai-iam-themis

  iamThemisBootstrap:
    image: ${REGISTRY}/nutanix/nai-iam-bootstrap

naiLabs:
  labsImage:
    image: ${REGISTRY}/nutanix/nai-rag-app

nai-clickhouse-keeper:
  clickhouseKeeper:
    storage:
      storageClass: ${NAI_DEFAULT_RWO_STORAGECLASS}
    image:
      registry: ${REGISTRY}
      repository: nutanix/nai-clickhouse-keeper

oauth2-proxy:
  image:
    repository: ${REGISTRY}/nutanix/nai-oauth2-proxy

nai-clickhouse-server:
  clickhouse:
    storage:
      storageClass: ${NAI_DEFAULT_RWO_STORAGECLASS}
    image:
      registry: ${REGISTRY}
      repository: nutanix/nai-clickhouse-server
    initContainers:
      addUdf:
        image:
          registry: ${REGISTRY}
          repository: nutanix/nai-clickhouse-udf
      waitForKeeper:
        image:
          registry: ${REGISTRY}
          repository: nutanix/nai-jobs

nai-clickhouse-schemas:
  image:
    registry: ${REGISTRY}
    repository: nutanix/nai-clickhouse-schemas

naiMonitoring:
  opentelemetry:
    storageClassName: ${NAI_API_RWX_STORAGECLASS}
    collectorImage: ${REGISTRY}/nutanix/nai-opentelemetry-collector-contrib:0.141.0
    targetAllocator:
      image:
        repository: ${REGISTRY}/nutanix/nai-target-allocator
  nodeExporter:
    serviceMonitor:
      namespaceSelector:
        matchNames:
          - ${NKP_WORKSPACE_NAMESPACE}
  dcgmExporter:
    serviceMonitor:
      namespaceSelector:
        matchNames:
          - ${NKP_WORKSPACE_NAMESPACE}
EOF

    global:
imagePullSecrets:
  - name: private-regcred

defaultStorageClassName: nutanix-volume
naiIepOperator:
  iepOperatorImage:
    image: harbor.10.x.x.134/nutanix/nai-iep-operator

  modelProcessorImage:
    image: harbor.10.x.x.134/nutanix/nai-python-processor

  dataSourceProcessorImage:
    image: harbor.10.x.x.134/nutanix/nai-python-processor

  finetuneProcessorImage:
    image: harbor.10.x.x.134/nutanix/nai-finetuning

naiInferenceUi:
  naiUiImage:
    image: harbor.10.x.x.134/nutanix/nai-inference-ui

naiJobs:
  naiJobsImage:
    image: harbor.10.x.x.134/nutanix/nai-jobs

naiApi:
  storageClassName: nai-nfs-storage
  naiApiImage:
    image: harbor.10.x.x.134/nutanix/nai-api
  supportedTGIImage: harbor.10.x.x.134/nutanix/nai-tgi
  supportedKserveRuntimeImage: harbor.10.x.x.134/nutanix/nai-kserve-huggingfaceserver
  eppImage: harbor.10.x.x.134/nutanix/nai-epp-inference-scheduler
  supportedVLLMImage: harbor.10.x.x.134/nutanix/nai-vllm
  supportedKserveCustomModelServerRuntimeImage: harbor.10.x.x.134/nutanix/nai-kserve-custom-model-server
  superAdmin:
    username: admin
    password: XXXXXXXXXX # At least 8 characters
    # email: admin@nutanix.com
    # firstName: admin

naiDatabase:
  naiDbImage:
    image: harbor.10.x.x.134/nutanix/nai-postgres:16.1-alpine

naiIam:
  iamProxy:
    image: harbor.10.x.x.134/nutanix/nai-iam-proxy

  iamProxyControlPlane:
    image: harbor.10.x.x.134/nutanix/nai-iam-proxy-control-plane

  iamUi:
    image: harbor.10.x.x.134/nutanix/nai-iam-ui

  iamUserAuthn:
    image: harbor.10.x.x.134/nutanix/nai-iam-user-authn

  iamThemis:
    image: harbor.10.x.x.134/nutanix/nai-iam-themis

  iamThemisBootstrap:
    image: harbor.10.x.x.134/nutanix/nai-iam-bootstrap

naiLabs:
  labsImage:
    image: harbor.10.x.x.134/nutanix/nai-rag-app

nai-clickhouse-keeper:
  clickhouseKeeper:
    storage:
      storageClass: nutanix-volume
    image:
      registry: harbor.10.x.x.134
      repository: nutanix/nai-clickhouse-keeper

oauth2-proxy:
  image:
    repository: harbor.10.x.x.134/nutanix/nai-oauth2-proxy

nai-clickhouse-server:
  clickhouse:
    storage:
      storageClass: nutanix-volume
    image:
      registry: harbor.10.x.x.134
      repository: nutanix/nai-clickhouse-server
    initContainers:
      addUdf:
        image:
          registry: harbor.10.x.x.134
          repository: nutanix/nai-clickhouse-udf
      waitForKeeper:
        image:
          registry: harbor.10.x.x.134
          repository: nutanix/nai-jobs

nai-clickhouse-schemas:
  image:
    registry: harbor.10.x.x.134
    repository: nutanix/nai-clickhouse-schemas

naiMonitoring:
  opentelemetry:
    storageClassName: nai-nfs-storage
    collectorImage: harbor.10.x.x.134/nutanix/nai-opentelemetry-collector-contrib:0.141.0
    targetAllocator:
      image:
        repository: harbor.10.x.x.134/nutanix/nai-target-allocator
  nodeExporter:
    serviceMonitor:
      namespaceSelector:
        matchNames:
          - kommander-workspace
  dcgmExporter:
    serviceMonitor:
      namespaceSelector:
        matchNames:
          - kommander-workspace

  8. Install NAI Core helm chart in the nai-system namespace 

    helm upgrade --install nai-core oci://${REGISTRY}/nutanix/nai-core \
  --version 2.6.0 \
  -n nai-system --create-namespace --wait \
  --set "naiAIGateway.enabled=true" \
  --insecure-skip-tls-verify \
  -f ./darksite-nai-core.yaml

    helm upgrade --install nai-core oci://harbor.10.x.x.134/nutanix/nai-core \
  --version 2.6.0 \
  -n nai-system --create-namespace --wait \
  --set "naiAIGateway.enabled=true" \
  --insecure-skip-tls-verify \
  -f ./darksite-nai-core.yaml

    Release "nai-core" has been upgraded. Happy Helming!
NAME: nai-core
LAST DEPLOYED: Tue Apr  7 08:31:50 2026
NAMESPACE: nai-system
STATUS: deployed
REVISION: 1
TEST SUITE: None

  9. Check if all NAI core pods are running 

    kubens nai-system
kubectl get pods

    Active namespace is "nai-system".
NAME                                                    READY   STATUS      RESTARTS     AGE
ai-gateway-controller-fc568fdc-vdcln                    1/1     Running     0            9h
chi-nai-clickhouse-server-chcluster1-0-0-0              1/1     Running     0            9h
chk-nai-clickhouse-keeper-chkeeper-0-0-0                1/1     Running     0            9h
iam-database-bootstrap-shkz5-xmwmr                      0/1     Completed   0            9h
iam-proxy-6899b56d94-bnkph                              1/1     Running     0            9h
iam-proxy-control-plane-58c67c59b7-dzq5q                1/1     Running     1            9h
iam-themis-79955f5cb-8tdgw                              1/1     Running     1            9h
iam-themis-bootstrap-b2uzx-vqq24                        0/1     Completed   0            9h
iam-ui-55f7f7bc95-t25d2                                 1/1     Running     0            9h
iam-user-authn-6c59768cb9-x8dbv                         1/1     Running     0            9h
nai-api-5ffcf69697-4k6bw                                1/1     Running     2            9h
nai-api-db-migrate-tm42r-9qkf8                          0/1     Completed   0            9h
nai-clickhouse-schema-job-1775611064-cp5jk              0/1     Completed   0            9h
nai-db-0                                                1/1     Running     0            9h
nai-iep-model-controller-7449cf9fc7-gxq4t               1/1     Running     0            9h
nai-labs-694c7bfc46-t7mw7                               1/1     Running     0            9h
nai-oauth2-proxy-5d4ff7c6d6-ncbtm                       1/1     Running     0            9h
nai-oidc-client-registration-wplkm-xf6b7                0/1     Completed   0            9h
nai-operators-nai-clickhouse-operator-86d684894-r8qh7   2/2     Running     0            9h
nai-otel-collector-collector-7kxzd                      1/1     Running     0            9h
nai-otel-collector-collector-854nl                      1/1     Running     0            9h
nai-otel-collector-collector-lf2kd                      1/1     Running     0            9h
nai-otel-collector-collector-m9w5c                      1/1     Running     0            9h
nai-otel-collector-collector-pk7v9                      1/1     Running     0            9h
nai-otel-collector-collector-qs44c                      1/1     Running     0            9h
nai-otel-collector-collector-rdd8f                      1/1     Running     0            9h
nai-otel-collector-targetallocator-844556594c-mq9jk     1/1     Running     0            9h
nai-ui-8c9fd97b9-fb82k                                  1/1     Running     0            9h
redis-standalone-6dd5f64ff5-qjhdm                       2/2     Running     0            9h

  10. The Prometheus monitoring from the NKP catalog has specific RBAC rules applied. Create the required clusterRole to enable Nutanix Enterprise AI to fetch metrics

    kubectl patch clusterrole nai-otel-role --type='json' -p='[
  {
    "op": "add",
    "path": "/rules/-",
    "value": {
      "apiGroups": [""],
      "resources": ["services/kube-prometheus-stack-prometheus-node-exporter"],
      "verbs": ["get"]
    }
  }
]'

    kubectl patch servicemonitor nai-node-exporter-monitor -n nai-system --type='json' -p='[
  {"op": "add", "path": "/spec/endpoints/0/bearerTokenFile", "value": "/var/run/secrets/kubernetes.io/serviceaccount/token"},
  {"op": "replace", "path": "/spec/endpoints/0/scheme", "value": "https"},
  {"op": "add", "path": "/spec/endpoints/0/tlsConfig", "value": {"insecureSkipVerify": true}}
]'


    clusterrole.rbac.authorization.k8s.io/nai-otel-role patched

    servicemonitor.monitoring.coreos.com/nai-node-exporter-monitor patched

Install SSL Certificate and Gateway Elements

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 Envoy 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.

Manual - 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 nai-system create secret tls nai-cert --cert=path/to/nai.crt --key=path/to/nai.key

Use patch commmand (Step 6) onwards in this section to use this certificate.

Skip the steps in this self-signed certificate section to use the organisation generated certificates.

Automate - using Cert Manager and Public Certificate Authority (CA) for NAI SSL Certificate

Using Cert Manager to manage the Public Certificate Authority (CA) for NAI SSL Certificate is also a possiblity.

At a high level (Cloudflare Example):

  1. Get a API key from DNS provider woth Edit Zone rights
  2. Create a Kubernetes Secret from the API key
  3. Create a ClusterIssuer with Cert Mangager/Let's Encrypt - Configure cert-manager to use DNS-01 challenge with Cloudflare for automatic certificate issuance.
  4. Create the certificate and store it as a Secret
  5. Patch the NAI Envoy Ingress Gateway gateway listener with the secret (SSL certificate)

To create and use a self-signed certificate, follow these steps:

  1. Get the NAI UI ingress gateway host using the following command:

    NAI_UI_ENDPOINT=$(kubectl get svc -n envoy-gateway-system -l "gateway.envoyproxy.io/owning-gateway-name=nai-ingress-gateway,gateway.envoyproxy.io/owning-gateway-namespace=nai-system" -o jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}' | grep -v '^$' || kubectl get svc -n envoy-gateway-system -l "gateway.envoyproxy.io/owning-gateway-name=nai-ingress-gateway,gateway.envoyproxy.io/owning-gateway-namespace=nai-system" -o jsonpath='{.items[0].status.loadBalancer.ingress[0].hostname}')

  2. Get the value of NAI_UI_ENDPOINT environment variable

    echo $NAI_UI_ENDPOINT

    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.${NAI_UI_ENDPOINT}.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: nai-system
spec:
  issuerRef:
    name: selfsigned-issuer
    kind: ClusterIssuer
  secretName: nai-cert
  commonName: nai.${NAI_UI_ENDPOINT}.nip.io
  dnsNames:
  - nai.${NAI_UI_ENDPOINT}.nip.io
  ipAddresses:
  - ${NAI_UI_ENDPOINT}
EOF

  6. Patch the Envoy gateway with the nai-cert certificate details

    kubectl patch gateway nai-ingress-gateway -n nai-system --type='json' -p='[{"op": "replace", "path": "/spec/listeners/1/tls/certificateRefs/0/name", "value": "nai-cert"}]'

  7. Create EnvoyProxy

    k apply -f -<<EOF
apiVersion: gateway.envoyproxy.io/v1alpha1
kind: EnvoyProxy
metadata:
  name: envoy-service-config
  namespace: nai-system
spec:
  provider:
    type: Kubernetes
    kubernetes:
      envoyService:
        type: LoadBalancer
EOF

  8. Patch the nai-ingress-gateway resource with the new EnvoyProxy details

    kubectl patch gateway nai-ingress-gateway -n nai-system --type=merge \
-p '{
    "spec": {
        "infrastructure": {
            "parametersRef": {
                "group": "gateway.envoyproxy.io",
                "kind": "EnvoyProxy",
                "name": "envoy-service-config"
            }
        }
    }
}'

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. Use the ${NAI_USER} and ${NAI_TEMP_PASS} values set in ${ENVIRONMENT}-values.yaml files during helm installation of NAI v.2.4.0

  3. Change the password for the admin user

  4. 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

Troubleshooting Endpoint ISVC

TGI Imange and Self-signed Certificates

Only follow this procedure if this isvc is not starting up.

KNative Serving Image Tag Checking

From testing, we have identified that KServe module is making sure that there are no container image tag discrepencies, by pulling image using SHA digest. This is done to avoid pulling images that are updated without updating the tag.

We have avoided this behavior by patching the config-deployment config map in the knative-serving namespace to skip image tag checking. Check this Prepare for NAI Deployment sectionfor more details.

kubectl patch configmap  config-deployment -n knative-serving --type merge -p '{"data":{"registries-skipping-tag-resolving":"${REGISTRY}"}'

If this procedure was not followed, then the isvc will not start up.

  1. If the isvc is not coming up, then explore the events in nai-admin namespace.

    kubens nai-admin
kubectl get isvc
kubectl get events  --sort-by='.lastTimestamp'

    $ kubectl get isvc

NAME      URL                                          READY   PREV   LATEST   PREVROLLEDOUTREVISION   LATESTREADYREVISION       AGE
llama8b   http://llama8b.nai-admin.svc.cluster.local   False

$ kubectl get events --sort-by='.lastTimestamp'

Warning   InternalError         revision/llama8b-predictor-00001   Unable to fetch image "harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi:2.3.1-825f39d": failed to resolve image to digest: 
Get "https://harbor.10.x.x.134.nip.io/v2/": tls: failed to verify certificate: x509: certificate signed by unknown authority

    The temporary workaround is to use the TGI images SHA signature from the container registry.

    This site will be updated with resolutions for the above issues in the future.

  2. Note the above TGI image SHA digest from the container registry.

    docker pull ${REGISTRY}/nutanix/nai-tgi:${NAI_TGI_RUNTIME_VERSION}

    docker pull harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi:2.3.1-825f39d

2.3.1-825f39d: Pulling from nkp/nutanix/nai-tgi
Digest: sha256:2df9fab2cf86ab54c2e42959f23e6cfc5f2822a014d7105369aa6ddd0de33006
Status: Image is up to date for harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi:2.3.1-825f39d
harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi:2.3.1-825f39d

  3. The SHA digest will look like the following:

    TGI image SHA digest will be different for different environments
    sha256:2df9fab2cf86ab54c2e42959f23e6cfc5f2822a014d7105369aa6ddd0de33006

  4. Create a copy of the isvc manifest

    kubectl get isvc llama8b -n nai-admin -o yaml > llama8b.yaml

  5. Edit the isvc

    kubectl edit isvc llama8b -n nai-admin

  6. Search and replace the image tag with the SHA digest from the TGI image.

    <snip>

env:
- name: STORAGE_URI
  value: pvc://nai-c34d8d58-d6f8-4cb4-94e4-28-pvc-claim/model-files
  image: harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi:2.3.1-825f39d

<snip>
    7. After replacing the image's SHA digest, the image value should look as follows: 

    <snip>

env:
- name: STORAGE_URI
  value: pvc://nai-c34d8d58-d6f8-4cb4-94e4-28-pvc-claim/model-files
  image: harbor.10.x.x.134.nip.io/nkp/nutanix/nai-tgi@sha256:2df9fab2cf86ab54c2e42959f23e6cfc5f2822a014d7105369aa6ddd0de33006

<snip>

  7. Save the isvc configuration by writing the changes to the file and exiting the vi editor using :wq! key combination.

  8. Verify that the isvc is running

    kubens nai-admin
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

This should resolve the issue the issue with the TGI image.

Report Other Issues

If you are facing any other issues, please report them here in the NAI LLM GitHub Repo Issues page.