diff --git a/charts/values-overrides/examples/gke/README.md b/charts/values-overrides/examples/gke/README.md
new file mode 100644
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+# Deploy a Graphistry k8s cluster using GKE
+This guide provides step-by-step instructions for deploying Graphistry on Google Kubernetes Engine (GKE).  The steps are based on the official documentation of [Graphistry Helm Charts](https://github.com/graphistry/graphistry-helm) and the [NVIDIA GPU Operator with Google GKE](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/google-gke.html).
+
+## Prerequisites
+
+### gcloud
+Install the `gcloud` CLI: donwload the Linux binaries from (e.g. `google-cloud-cli-477.0.0-linux-x86_64.tar.gz`):
+https://cloud.google.com/sdk/docs/install
+
+Verify the installation using:
+```bash
+cloud --version
+# Google Cloud SDK 477.0.0
+# beta 2024.05.17
+# bq 2.1.4
+# bundled-python3-unix 3.11.8
+# core 2024.05.17
+# gcloud-crc32c 1.0.0
+# gke-gcloud-auth-plugin 0.5.8
+# gsutil 5.29
+# kubectl 1.27.14
+```
+
+### kubectl
+Install `kubectl` compatible with `gcloud`:
+```bash
+gcloud components install kubectl
+```
+
+More details here:
+https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl
+
+Verify the installation using:
+```bash
+kubectl version
+# WARNING: This version information is deprecated and will be replaced with the output from kubectl version --short.  Use --output=yaml|json to get the full version.
+# Client Version: version.Info{Major:"1", Minor:"27+", GitVersion:"v1.27.14-dispatcher", GitCommit:"643004a51a14c7a149377e6651fb926f17c06c5a", GitTreeState:"clean", BuildDate:"2024-05-15T21:18:29Z", GoVersion:"go1.21.9", Compiler:"gc", Platform:"linux/amd64"}
+# Kustomize Version: v5.0.1
+```
+
+### heml
+Install Helm from:
+https://github.com/helm/helm/releases
+
+Download the `linux-amd64` version and add the binaries to the prefix path:
+```bash
+wget https://get.helm.sh/helm-v3.15.1-linux-amd64.tar.gz
+tar xvf helm-v3.15.1-linux-amd64.tar.gz
+export PATH=$PATH:$PWD/linux-amd64/
+```
+
+Verify the installation using:
+```bash
+helm version
+# version.BuildInfo{Version:"v3.15.1", GitCommit:"e211f2aa62992bd72586b395de50979e31231829", GitTreeState:"clean", GoVersion:"go1.22.3"}
+```
+
+## Create a K8S cluster
+In this example the cluster will have a single node with only 1 GPU (`nvidia-tesla-t4`):
+```bash
+gcloud beta container clusters create demo-cluster \
+      --zone us-central1-a \
+      --release-channel "regular" \
+      --machine-type "n1-highmem-4" \
+      --accelerator "type=nvidia-tesla-t4,count=1" \
+      --image-type "UBUNTU_CONTAINERD" \
+      --disk-type "pd-standard" \
+      --disk-size "1000" \
+      --no-enable-intra-node-visibility \
+      --metadata disable-legacy-endpoints=true \
+      --max-pods-per-node "110" \
+      --num-nodes "1" \
+      --logging=SYSTEM,WORKLOAD \
+      --monitoring=SYSTEM \
+      --enable-ip-alias \
+      --no-enable-intra-node-visibility \
+      --default-max-pods-per-node "110" \
+      --no-enable-master-authorized-networks \
+      --tags=nvidia-ingress-all
+```
+
+## Get cluster credentials
+The next command should fill the credentials in `~/.kube/config`:
+```bash
+USE_GKE_GCLOUD_AUTH_PLUGIN=True \
+    gcloud container clusters get-credentials demo-cluster --zone us-central1-a
+```
+
+Verify the credentials and the cluster labels:
+```bash
+kubectl get nodes --show-labels
+cat ~/.kube/config
+```
+
+## Test the K8S cluster
+```bash
+kubectl get nodes -o wide
+kubectl get all
+```
+
+## Setup the NVIDIA GPU Operator
+```bash
+kubectl create ns gpu-operator
+kubectl apply -n gpu-operator -f - <<EOF
+apiVersion: v1
+kind: ResourceQuota
+metadata:
+  name: gpu-operator-quota
+spec:
+  hard:
+    pods: 100
+  scopeSelector:
+    matchExpressions:
+    - operator: In
+      scopeName: PriorityClass
+      values:
+        - system-node-critical
+        - system-cluster-critical
+EOF
+kubectl get -n gpu-operator resourcequota
+```
+
+## Install the NVIDIA GPU Operator
+```bash
+helm repo remove nvidia
+helm repo add nvidia https://helm.ngc.nvidia.com/nvidia \
+    && helm repo update
+```
+
+Test if `nfd.enabled` is `false`, if is true then add `--set nfd.enabled=false` to the `helm install` command:
+```bash
+kubectl get nodes -o json | jq '.items[].metadata.labels | keys | any(startswith("feature.node.kubernetes.io"))'
+helm install --wait --generate-name \
+    -n gpu-operator --create-namespace nvidia/gpu-operator \
+    --timeout 60m \
+    --set driver.version="550.90.07"
+```
+Note: The recomended driver version can be found in the official [NVIDIA GPU Operator Matrix](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/platform-support.html#gpu-operator-component-matrix).
+
+Check the cluster labels again, it should have GPU accelerator support for the K8s node selector:
+```bash
+kubectl get nodes --show-labels | grep "nvidia.com/gpu.present"
+# should contain something like: ...,nvidia.com/gpu.present=true,...
+```
+
+Wait until all pods are running or completed:
+```bash
+kubectl get pods -n gpu-operator --watch
+```
+
+Test we have applied corrrectly the operator using:
+```bash
+kubectl get nodes -ojson | jq .items[].status.capacity | grep nvidia.com/gpu
+# output example: "nvidia.com/gpu": "1",
+```
+
+**Note**: We don't need to install the NVIDIA Device Plugin given that we are using the NVIDIA GPU Operator.
+
+## Inspect the NVIDIA GPU Operator (optional)
+```bash
+kubectl get all -n gpu-operator
+kubectl get po -n gpu-operator -A | grep nvidia
+kubectl describe deployment gpu-operator -n gpu-operator
+kubectl describe rs gpu-operator -n gpu-operator
+```
+
+## Create the graphistry namespace and set it as default
+```bash
+kubectl create namespace graphistry
+kubectl get ns
+kubectl config set-context --current --namespace=graphistry
+kubectl get all
+```
+
+## Create the Docker Hub secret
+Here you can use your Docker Hub user and password, your account must have access to the official Graphistry docker images.
+```bash
+kubectl create secret docker-registry dockerhub-secret \
+    --namespace graphistry \
+    --docker-server=docker.io \
+    --docker-username=user123 \
+    --docker-password=thepassword
+kubectl get secret
+```
+
+## Create a Secret for Graph App Kit (OPTIONAL)
+For for information visit [graph-app-kit](https://github.com/graphistry/graph-app-kit).
+```bash
+kubectl apply -f - <<EOF
+apiVersion: v1
+kind: Secret
+metadata:
+  name: gak-secret
+  namespace: graphistry
+type: Opaque
+stringData:
+  username: gke_graphistry_user1
+  password: gke_graphistry_password1
+EOF
+```
+
+## Get Graphistry Helm charts
+```bash
+git clone https://github.com/graphistry/graphistry-helm
+cd graphistry-helm
+bash chart-bundler/bundler.sh
+```
+
+## Install NGINX Ingress Controller
+```bash
+helm upgrade --install ingress-nginx ingress-nginx \
+    --repo https://kubernetes.github.io/ingress-nginx \
+    --namespace ingress-nginx --create-namespace \
+    --set controller.service.type=LoadBalancer
+```
+
+Verify the `EXTERNAL-IP` (this will be used to access to the cluster from the browser):
+```bash
+kubectl get service --namespace ingress-nginx ingress-nginx-controller --output wide --watch
+```
+
+## Create the storage class
+```bash
+kubectl apply -f - <<EOF
+apiVersion: storage.k8s.io/v1
+kind: StorageClass
+metadata:
+  name: retain-sc-graphistry
+provisioner: pd.csi.storage.gke.io
+volumeBindingMode: WaitForFirstConsumer
+EOF
+```
+
+## Install Postgres Operator
+```bash
+helm upgrade -i postgres-operator ./charts-aux-bundled/postgres-operator --namespace postgres-operator --create-namespace
+```
+
+## Install Postgres Cluster
+```bash
+helm show values ./charts/postgres-cluster
+helm upgrade -i postgres-cluster ./charts/postgres-cluster --set global.provisioner="pd.csi.storage.gke.io" --namespace graphistry --create-namespace
+kubectl get pods --watch
+```
+
+## Install Dask Operator and CRDs
+```bash
+cd charts-aux-bundled/dask-kubernetes-operator/ && helm dep build && cd ../..
+helm upgrade -i dask-operator ./charts-aux-bundled/dask-kubernetes-operator --namespace dask-operator --create-namespace
+```
+
+Wait until the operator is ready and running:
+```bash
+kubectl get pods --watch --namespace dask-operator
+```
+
+## Install Graphistry Resources
+```bash
+helm show values ./charts/graphistry-helm-resources
+helm upgrade -i graphistry-resources ./charts/graphistry-helm-resources --set global.provisioner="pd.csi.storage.gke.io" --namespace graphistry --create-namespace
+kubectl get pods --watch
+```
+
+## Install Graphistry
+You can set the CUDA and Graphistry versions by editing `./charts/values-overrides/examples/gke/gke_values.yaml`:
+```yaml
+cuda:
+  version: "11.8" #cuda version
+
+global:  ## global settings for all charts
+  tag: v2.41.0
+```
+
+Install Graphistry using the next commands:
+```bash
+helm show values ./charts/graphistry-helm
+kubectl get secret | grep dockerhub-secret
+helm upgrade -i g-chart ./charts/graphistry-helm \
+    --values ./charts/values-overrides/examples/gke/default_gke_values.yaml \
+    -f ./charts/values-overrides/examples/gke/gke_values.yaml \
+    --namespace graphistry --create-namespace
+```
+
+Wait unilt all the pods are running and completed:
+```bash
+kubectl get pods --watch
+```
+
+It's possible to get the public cluster address using this command (this IP is the `EXTERNAL-IP` of the `ingress-controller`):
+```bash
+kubectl get ingress -n graphistry
+```
+
+Once you open Graphistry in the browser, create an account for the admin user with the email and password.
+
+## Update Graphistry deployment
+In case we want to change some values in `../gke_values.yaml` we need to reuse the volume names:
+```bash
+helm upgrade -i g-chart ./charts/graphistry-helm \
+    --values ./charts/values-overrides/examples/gke/default_gke_values.yaml \
+    --set volumeName.dataMount=$(kubectl get pv | grep "data-mount" | tail -n 1 | awk '{print $1;}') \
+    --set volumeName.localMediaMount=$(kubectl get pv | grep "local-media-mount" | tail -n 1 | awk '{print $1;}') \
+    --set volumeName.gakPublic=$(kubectl get pv | grep "gak-public" | tail -n 1 | awk '{print $1;}') \
+    --set volumeName.gakPrivate=$(kubectl get pv | grep "gak-private" | tail -n 1 | awk '{print $1;}') \
+    -f ./charts/values-overrides/examples/gke/gke_values.yaml \
+    --namespace graphistry --create-namespace
+kubectl get pods --watch
+```
+
+## Delete k8s cluster
+```bash
+helm uninstall g-chart
+helm uninstall graphistry-resources
+
+helm uninstall postgres-cluster
+helm uninstall postgres-operator --namespace postgres-operator
+helm uninstall dask-operator --namespace dask-operator
+
+kubectl get ns
+kubectl config set-context --current --namespace=default
+kubectl delete namespace graphistry
+gcloud container clusters delete demo-cluster --zone us-central1-a
+```
+
+## Utils
+
+### caddy-ingress
+```bash
+kubectl describe ingress caddy-ingress-graphistry -n graphistry
+kubectl describe $(kubectl get pods -o name | grep caddy)
+
+# print the logs
+kubectl logs $(kubectl get pods -o name | grep caddy) -f
+```
+
+### nexus
+```bash
+# print the logs
+kubectl logs $(kubectl get pods -o name | grep nexus) -f
+
+# get into the container
+kubectl exec -i -t $(kubectl get pods -o name | grep nexus) --container nexus -- /bin/bash
+```
+
+### streamgl-gpu
+```bash
+kubectl describe $(kubectl get pods -o name | grep streamgl-gpu)
+
+# print the logs
+kubectl logs $(kubectl get pods -o name | grep streamgl-gpu) -f
+```
+
+### forge-etl-python
+```bash
+kubectl describe $(kubectl get pods -o name | grep forge-etl-python)
+
+# print the logs
+kubectl logs $(kubectl get pods -o name | grep forge-etl-python) -f
+
+# get into the container
+kubectl exec -i -t $(kubectl get pods -o name | grep forge-etl-python) --container forge-etl-python -- /bin/bash
+```
+
+### dask-cuda
+```bash
+kubectl describe $(kubectl get pods -o name | grep dask-cuda)
+
+# print the logs
+kubectl logs $(kubectl get pods -o name | grep dask-cuda) -f
+```
diff --git a/charts/values-overrides/examples/gke/default_gke_values.yaml b/charts/values-overrides/examples/gke/default_gke_values.yaml
new file mode 100644
index 00000000..fbca3fbb
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+++ b/charts/values-overrides/examples/gke/default_gke_values.yaml
@@ -0,0 +1,68 @@
+global:
+  imagePullPolicy: Always
+  imagePullSecrets: 
+    - name: dockerhub-secret
+  provisioner: pd.csi.storage.gke.io #storage class provisioner.
+  nodeSelector:
+    nvidia.com/gpu.present: "true"
+    cloud.google.com/gke-accelerator: nvidia-tesla-t4
+  multiNode: false #multinode selector switch to determine if going multi/single node
+  devMode: false   #dev mode for debugging with nexus, postgres and nginx
+  postgres:
+    repository: graphistry-postgres #postgres repository name   
+    name: graphistry                #db name
+    user: graphistry                #db user
+    port: 5432                      #port for postgres service to listen on
+    host: postgres                  #hostname for postgres
+  postgresVolumeLabel: graphistry-postgres
+
+
+#domain: gke-dev.grph.xyz 
+#tlsEmail: "percy@graphistry.com" 
+tls: false
+fwdHeaders: true
+#volumeName:
+  #dataMount: pvc-c3e768a1-29a8-42ad-95e0-692b608dd19f
+  #localMediaMount: pvc-76551421-a3fb-4a24-9d35-62e7d470627b
+  #gakPublic: pvc-eec4b0d9-b074-4117-9093-276912661f8a
+  #gakPrivate: pvc-75bb5fd0-ab86-49c4-afed-6e261161808c
+networkPolicy:
+  strict: false
+
+#ingress management - determines if ingress is going to be on internal load balancer 
+# NOTICE these annotations make possible ingress can expose the port 80 to the local host
+#  kubernetes.io/ingress.class: public
+#  nginx.ingress.kubernetes.io/rewrite-target: /
+ingress:
+  management:
+    annotations:
+
+
+graphistryResources:
+  storageClassParameters:
+      pd.csi.storage.gke.io/fstype: ext4
+      type: gp2
+
+
+## createServiceAccount: true only true on initial deployment
+k8sDashboard:
+  enabled: true
+  readonly: false
+  createServiceAccount: false
+
+
+nodeEnv: production #sets the Node environment - set to development in dev mode
+appEnvironment: production #sets the appEnvironment for nexus - set to development in dev mode
+
+# djangoSettingsModule: "config.settings.production" #Sets the django settings - set to config.settings.dev in dev mode
+# djangoDebug: "True" #sets django in debug mode set to true in dev mode
+
+graphistryCPUMode: "0" #sets graphistry to cpu mode - to be used in dev mode set to 1
+metrics: false #enables metrics for prometheus - must have kube-prometheus-stack installed
+graphAppKitPublic: true # graph app kit public - determines if public dashboard is going to be deployed
+graphAppKitPrivate: true # graph app kit private - determines if private dashboard is going to be deployed
+forgeWorkers: "1" #sets the number of forge workers recommend 1 per 4 GB GPU memory
+
+
+dask:
+  operator: false
diff --git a/charts/values-overrides/examples/gke/gke_values.yaml b/charts/values-overrides/examples/gke/gke_values.yaml
new file mode 100644
index 00000000..7a5a8009
--- /dev/null
+++ b/charts/values-overrides/examples/gke/gke_values.yaml
@@ -0,0 +1,375 @@
+cuda:
+  version: "11.8" #cuda version
+
+global:  ## global settings for all charts
+  tag: v2.41.0
+  logs: #change log levels
+      LogLevel: DEBUG #log level for the application
+      GraphistryLogLevel: DEBUG #log level for graphistry
+
+
+CaddyResources: {}  # Resources for the Caddy pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 500m
+  #   memory: 500Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+DaskSchedulerResources: {}  # Resources for the Dask Scheduler pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 500m
+  #   memory: 1Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+DaskWorkerResources: # Resources for the Dask worker pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 3000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+  # limits:
+  #   nvidia.com/gpu: 1
+
+
+ForgeETLResources: {}  # Resources for the Forge Etl pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 1000m
+  #   memory: 1Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+ForgeETLPythonResources:  # Resources for the Forge ETL python pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 3000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+  # limits:
+  #   nvidia.com/gpu: 1
+
+
+GAKResources: {}  # Resources for the graph app kit pods
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 2000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+NexusResources: {}  # Resources for the nexus pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 2000m
+  #   memory: 400Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+NginxResources: {}  # Resources for the nginx pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 500m
+  #   memory: 500Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+InitContainerResources: {}  # Resources for the notebook pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 3000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+NotebookResources: {}  # Resources for the notebook pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 3000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+PivotResources: {}  # Resources for the pivot pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 2000m
+  #   memory: 2Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+RedisResources: {}  # Resources for the redis pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 1000m
+  #   memory: 100Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+StreamglGpuResources: # Resources for the streamgl gpu pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 2000m
+  #   memory: 2Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+  #limits:
+  #  nvidia.com/gpu: 1
+
+
+StreamglSessionsResources: {}  # Resources for the streamgl sessions pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 500m
+  #   memory: 400Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+StreamglVgraphResources: {}  # Resources for the streamgl vgraph etl pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 1000m
+  #   memory: 500Mi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+StreamglVizResources: {}  # Resources for the streamgl viz pod
+  # We usually recommend not to specify default resources and to leave this as a conscious
+  # choice for the user. This also increases chances charts run on environments with little
+  # resources, such as Minikube. If you do want to specify resources, uncomment the following
+  # lines, adjust them as necessary, and remove the curly braces after 'resources:'.
+  # limits:
+  #   cpu: 3000m
+  #   memory: 4Gi
+  # requests:
+  #   cpu: 100m
+  #   memory: 128Mi
+
+
+#environment variables 
+ # can be set like helm install chart_name --name release_name \
+ #--set env.DBUser="FOO" --set env.DBPassword="BAR"
+env: #environment variables
+ - name: HOST
+   value: 0.0.0.0
+ - name: AUTH_LDAP_BIND_PASSWORD
+   value: abc123xyz
+ - name: DJANGO_SECRET_KEY
+   value: abc123xyz
+ - name: LEGACY_API_KEY_CANARY
+   value: abc123xyz
+ - name: LEGACY_API_KEY_SECRET
+   value: abc123xyz
+ - name: DASK_DISTRIBUTED__WORKER__DAEMON
+   value: "False"
+ - name: CHUNK_DASK_CUDF_ROWS
+   value: "500000"
+ - name: DASK_CSV_BLOCKSIZE
+   value: 64 MiB
+ - name: DASK_CUDF_CSV_CHUNKSIZE
+   value: 64 MiB
+ - name: REMOTE_DASK_DIAGNOSTICS
+   value: dask-scheduler:8787
+ - name: AIR_GAPPED
+   value: "0"
+ - name: PIVOT_PORT 
+   value: "8080"
+ - name: PORT
+   value: "8080"
+ - name: NODE_NO_WARNINGS
+   value: "1"
+ - name: USE_LOCAL_USER
+   value: "false"
+ - name: NODE_OPTIONS
+   value: --max-old-space-size=64000 --stack-trace-limit=20
+ - name: NODE_REDIS_URL
+   value: redis://redis:6379
+ - name: NODE_TLS_REJECT_UNAUTHORIZED
+   value: "0"
+ - name: CELERY_FLOWER_PASSWORD
+   value: JPkK3b2ihuwAGLJ8AjE3aNRmEEvYm5jyCTVlqDbRzzOAMrZhyzJ3SfgnQZMrBBCw
+ - name: CELERY_FLOWER_USER
+   value: ATZpVOzzQgESuKVmUYQDoJwNqjvueLoP
+ - name: DJANGO_ADMIN_URL
+   value: admin/
+ - name: DJANGO_ALLOWED_HOSTS
+   value: '*'
+ - name: DJANGO_SECURE_SSL_REDIRECT
+   value: "False"
+ - name: GOOGLE_ANALYTICS_ID
+   value: UA-59712214-2
+ - name: IS_SIGNUPS_OPEN_AFTER_FIRST_DEFAULT
+   value: "false"
+ - name: IS_SOCIAL_AUTH_GITHUB_OPEN_DEFAULT
+   value: "false"
+ - name: IS_SOCIAL_AUTH_GOOGLE_OPEN_DEFAULT
+   value: "false"
+ - name: JWT_AUTH_COOKIE
+   value: graphistry_jwt
+ - name: REDIS_URL
+   value: redis://redis:6379/0
+ - name: USE_DOCKER
+   value: "yes"
+ - name: PIVOT_CONFIG_FILES
+   value: /opt/graphistry/apps/core/pivot/data/config/config.json
+ - name: CLEAR_LOCAL_DATASET_CACHE_ON_STARTUP
+   value: "false"
+ - name: CLEAR_LOCAL_SESSION_CACHE_ON_STARTUP
+   value: "true"
+ - name: FORGE_ETL_HOSTNAME
+   value: nginx
+ - name: FORGE_ETL_PATH
+   value: /api/v1/etl/
+ - name: FORGE_ETL_PORT
+   value: "80"
+ - name: GRAPH_PLAY_TIMEOUTMS
+   value: "60000"
+ - name: LOCAL_DATASET_CACHE
+   value: "true"
+ - name: LOCAL_DATASET_CACHE_DIR
+   value: /opt/graphistry/data
+ - name: LOCAL_SESSIONS_CACHE_DIR
+   value: /opt/graphistry/data
+ - name: LOCAL_WORKBOOK_CACHE
+   value: "true"
+ - name: LOCAL_WORKBOOK_CACHE_DIR
+   value: /opt/graphistry/data
+ - name: NGINX_HOST
+   value: nginx
+ - name: PM2_MAX_WORKERS
+   value: "4"
+ - name: STREAMGL_CPU_NUM_WORKERS
+   value: "4"
+ - name: STREAMGL_INACTIVITY_TIMEOUT_MS
+   value: "30000"
+ - name: STREAMGL_NUM_WORKERS
+   value: "4"
+ - name: UPLOAD_MAX_SIZE
+   value: 1G
+ - name: ZIPKIN_ENABLED
+   value: "false"
+ - name: ACME_AGREE
+   value: "true"
+ - name: OTEL_EXPORTER_OTLP_ENDPOINT
+   value: "http://otel-collector:4317"
+ - name: ENABLE_OPEN_TELEMETRY
+   value: "false"
+
+##streamlit environment variables
+ ## can be set like helm upgrade -i  chart_name --name release_name \
+ ##--set stENVPublic.LOG_LEVEL="FOO" 
+#streamlitEnv: #graph-app-kit (streamlit) environment variables
+ #- name: LOG_LEVEL
+   #value: TRACE
+ #- name: BASE_PATH
+   #value: dashboard/
+ #- name: BASE_URL
+   #value: "http://localhost:8501/dashboard"
+ #- name: FAVICON_URL
+   #value: "https://hub.graphistry.com/pivot/favicon/favicon.ico"
+ #- name: USE_DOCKER
+   #value: "True"
+ #- name: ST_PUBLIC_PORT
+   #value: 8501
+ #- name: GRAPH_VIEWS
+   #value: "/apps/views"
+ #- name: COMPOSE_PROJECT_NAME
+   #value: 
+ #- name: VERSION_BASE
+   #value: "v2.32.4"
+ #- name: NEPTUNE_READER_PROTOCOL
+   #value: 
+ #- name: NEPTUNE_READER_HOST
+   #value: 
+ #- name: NEPTUNE_READER_PORT
+   #value: 
+ #- name: NEPTUNE_KEY_PATH
+   #value: 
+ #- name: NEPTUNE_TUNNEL_HOST
+   #value: 
+ #- name: NEPTUNE_TUNNEL_USER
+   #value:  
+ #- name: TIGERGRAPH_HOST
+   #value: 
+ #- name: TIGERGRAPH_USERNAME
+   #value: 
+ #- name: TIGERGRAPH_PASSWORD
+   #value: 
+ #- name: TIGERGRAPH_GRAPHNAME
+   #value: 
+ #- name: TIGERGRAPH_SECRET
+   #value: