¶ Jupyterhub deploy old
위 버전과 저장소는 오래된 것이라 저장소가 존재하지 않을 수 있다.
Helm chart 를 이용한다.
Jupyter 홈페이지 에서 정보를 확인할 수 있다.
Helm chart 1.2.0
¶ Helm repo 등록
helm repo add jupyterhub https://jupyterhub.github.io/helm-chart/
¶ Notebook image build (All-spark-notebook)
¶ all-spark-notebook dockerfile
# Copyright (c) Jupyter Development Team.
# Distributed under the terms of the Modified BSD License.
ARG OWNER=jupyter
ARG BASE_CONTAINER=$OWNER/pyspark-notebook
FROM $BASE_CONTAINER
LABEL maintainer="Jupyter Project "
USER root
COPY ./kubectl /bin/
# RSpark config
ENV R_LIBS_USER "${SPARK_HOME}/R/lib"
RUN fix-permissions "${R_LIBS_USER}"
RUN echo "${NB_USER} ALL=(ALL) NOPASSWD: ALL" >> /etc/sudoers
# R pre-requisites
RUN apt-get update --yes && \
apt-get install --yes --no-install-recommends \
fonts-dejavu \
gfortran \
gcc \
telnet tcpdump lynx build-essential libjpeg-dev curl && \
apt-get clean && rm -rf /var/lib/apt/lists/*
USER ${NB_UID}
RUN echo "alias ll='ls -lha --color=auto'">>/home/jovyan/.bash_profile
RUN mkdir /home/jovyan/.kube
COPY .kube/config /home/jovyan/.kube/
RUN sudo chown $(id -u):$(id -g) /home/jovyan/.kube/config
# R packages including IRKernel which gets installed globally.
RUN mamba install --quiet --yes \
'r-base' \
'r-ggplot2' \
'r-irkernel' \
'r-rcurl' \
'r-sparklyr' && \
mamba clean --all -f -y && \
fix-permissions "${CONDA_DIR}" && \
fix-permissions "/home/${NB_USER}"
# Spylon-kernel
RUN mamba install --quiet --yes 'spylon-kernel' && \
mamba clean --all -f -y && \
python -m spylon_kernel install --sys-prefix && \
rm -rf "/home/${NB_USER}/.local" && \
fix-permissions "${CONDA_DIR}" && \
fix-permissions "/home/${NB_USER}"
RUN pip install --no-cache-dir s3fs py4j toml xgboost==1.5.1 lightgbm==3.3.1 scikit-learn==1.0.1 mlflow mlflow-skinny sqlalchemy alembic sqlparse tqdm boto3 jupyter-server-proxy petastorm &&\
fix-permissions "${CONDA_DIR}" && \
fix-permissions "/home/${NB_USER}"
RUN jupyter serverextension enable --sys-prefix jupyter_server_proxy
¶ chart download
[haedong@haedongg.net:~:]$ wget https://jupyterhub.github.io/helm-chart/jupyterhub-1.2.0.tgz
--2021-11-24 09:36:51-- https://jupyterhub.github.io/helm-chart/jupyterhub-1.2.0.tgz
Length: 43734 (43K) [application/octet-stream]
Saving to: ‘jupyterhub-1.2.0.tgz’
100%[======================================================] 43,734 --.-K/s in 0.01s
2021-11-24 09:36:53 (3.45 MB/s) - ‘jupyterhub-1.2.0.tgz’ saved [43734/43734]
[haedong@haedongg.net:~:]$ tar -cvzf jupyterhub-1.2.0.tgz
jupyterhub/Chart.yaml
jupyterhub/values.yaml
...중략...
jupyterhub/templates/scheduling/user-scheduler/rbac.yaml
jupyterhub/templates/singleuser/netpol.yaml
jupyterhub/templates/singleuser/secret.yaml
jupyterhub/.helmignore
jupyterhub/README.md
jupyterhub/files/hub/jupyterhub_config.py
jupyterhub/files/hub/z2jh.py
¶ 수정
일반적인 환경에서는 특별히 수정할 것이 없다.
[haedong@haedongg.net:~/jupyterhub:]$ vi values.yaml
...중략...
hub:
config:
Authenticator:
admin_users:
- admin # 관리자 계정
# - administrator 이렇게 추가
DummyAuthenticator:
password: ${REDACTED}
JupyterHub:
admin_access: true
authenticator_class: dummy
...중략...
defaultUrl: "/lab" #Jupyter notebook을 사용하는 경우 비운다.
extraPodConfig: {}
# 여러개의 notebook image를 선택적으로 제공하는 경우
profileList:
- display_name: "ALL spark notebook"
description: "All spark notebook from jupyter hub stack"
default: true
- display_name: "MINIMAL spark notebook"
description: "Minimal spark notebook from jupyter hub stack"
kubespawner_override:
image: redmine:8443/encore/jupyter/minimal-spark-notebook:latest
...중략...
# 아래 포트를 지정하지 않으면 임의의 포트가 지정된다.
nodePorts:
http: 30011
https:
...후략
¶ values.yaml 예시
# fullnameOverride and nameOverride distinguishes blank strings, null values,
# and non-blank strings. For more details, see the configuration reference.
fullnameOverride: ""
nameOverride:
# custom can contain anything you want to pass to the hub pod, as all passed
# Helm template values will be made available there.
custom: {}
# imagePullSecret is configuration to create a k8s Secret that Helm chart's pods
# can get credentials from to pull their images.
imagePullSecret:
${REDACTED} false
automaticReferenceInjection: true
registry:
username:
password:
${REDACTED}
# imagePullSecrets is configuration to reference the k8s Secret resources the
# Helm chart's pods can get credentials from to pull their images.
imagePullSecrets: []
# hub relates to the hub pod, responsible for running JupyterHub, its configured
# Authenticator class KubeSpawner, and its configured Proxy class
# ConfigurableHTTPProxy. KubeSpawner creates the user pods, and
# ConfigurableHTTPProxy speaks with the actual ConfigurableHTTPProxy server in
# the proxy pod.
hub:
config:
Authenticator:
admin_users:
- admin # 관리자 계정
# - administrator 이렇게 추가
DummyAuthenticator:
password: ${REDACTED}
JupyterHub:
admin_access: true
authenticator_class: dummy
service:
type: ClusterIP # jupyterhub를 통해 연결하므로 Nodeport 등으로 변경하면 안된다.
annotations: {}
ports:
nodePort:
extraPorts: []
loadBalancerIP:
baseUrl: /
cookieSecret:
${REDACTED} []
fsGid: 1000
nodeSelector: {}
tolerations: []
concurrentSpawnLimit: 64
consecutiveFailureLimit: 5
activeServerLimit:
deploymentStrategy:
## type: Recreate
## - sqlite-pvc backed hubs require the Recreate deployment strategy as a
## typical PVC storage can only be bound to one pod at the time.
## - JupyterHub isn't designed to support being run in parallell. More work
## needs to be done in JupyterHub itself for a fully highly available (HA)
## deployment of JupyterHub on k8s is to be possible.
type: Recreate
db:
type: sqlite-pvc
upgrade:
pvc:
annotations: {}
selector: {}
accessModes:
- ReadWriteOnce
storage: 1Gi
subPath:
storageClassName: # 별도의 SC를 지정하지 않으면 default SC
url:
password:
${REDACTED} {}
annotations: {}
command: []
args: []
extraConfig: {}
extraFiles: {}
extraEnv: {}
extraContainers: []
extraVolumes: []
extraVolumeMounts: []
image:
name: jupyterhub/k8s-hub
tag: "1.2.0"
pullPolicy:
pullSecrets: []
resources: {}
containerSecurityContext:
runAsUser: 1000
runAsGroup: 1000
allowPrivilegeEscalation: false
lifecycle: {}
services: {}
pdb:
enabled: false
maxUnavailable:
minAvailable: 1
networkPolicy:
enabled: true
ingress: []
## egress for JupyterHub already includes Kubernetes internal DNS and
## access to the proxy, but can be restricted further, but ensure to allow
## access to the Kubernetes API server that couldn't be pinned ahead of
## time.
##
## ref: https://stackoverflow.com/a/59016417/2220152
egress:
- to:
- ipBlock:
cidr: 0.0.0.0/0
interNamespaceAccessLabels: ignore
allowedIngressPorts: []
allowNamedServers: false
namedServerLimitPerUser:
authenticatePrometheus:
redirectToServer:
shutdownOnLogout:
templatePaths: []
templateVars: {}
livenessProbe:
# The livenessProbe's aim to give JupyterHub sufficient time to startup but
# be able to restart if it becomes unresponsive for ~5 min.
enabled: true
initialDelaySeconds: 300
periodSeconds: 10
failureThreshold: 30
timeoutSeconds: 3
readinessProbe:
# The readinessProbe's aim is to provide a successful startup indication,
# but following that never become unready before its livenessProbe fail and
# restarts it if needed. To become unready following startup serves no
# purpose as there are no other pod to fallback to in our non-HA deployment.
enabled: true
initialDelaySeconds: 0
periodSeconds: 2
failureThreshold: 1000
timeoutSeconds: 1
existingSecret:
${REDACTED}
annotations: {}
extraPodSpec: {}
rbac:
enabled: true
# proxy relates to the proxy pod, the proxy-public service, and the autohttps
# pod and proxy-http service.
proxy:
secretToken:
annotations: {}
deploymentStrategy:
## type: Recreate
## - JupyterHub's interaction with the CHP proxy becomes a lot more robust
## with this configuration. To understand this, consider that JupyterHub
## during startup will interact a lot with the k8s service to reach a
## ready proxy pod. If the hub pod during a helm upgrade is restarting
## directly while the proxy pod is making a rolling upgrade, the hub pod
## could end up running a sequence of interactions with the old proxy pod
## and finishing up the sequence of interactions with the new proxy pod.
## As CHP proxy pods carry individual state this is very error prone. One
## outcome when not using Recreate as a strategy has been that user pods
## have been deleted by the hub pod because it considered them unreachable
## as it only configured the old proxy pod but not the new before trying
## to reach them.
type: Recreate
## rollingUpdate:
## - WARNING:
## This is required to be set explicitly blank! Without it being
## explicitly blank, k8s will let eventual old values under rollingUpdate
## remain and then the Deployment becomes invalid and a helm upgrade would
## fail with an error like this:
##
## UPGRADE FAILED
## Error: Deployment.apps "proxy" is invalid: spec.strategy.rollingUpdate: Forbidden: may not be specified when strategy `type` is 'Recreate'
## Error: UPGRADE FAILED: Deployment.apps "proxy" is invalid: spec.strategy.rollingUpdate: Forbidden: may not be specified when strategy `type` is 'Recreate'
rollingUpdate:
# service relates to the proxy-public service
service:
type: LoadBalancer
labels: {}
annotations: {}
# 아래 포트를 지정하지 않으면 임의의 포트가 지정된다.
nodePorts:
http: 30011
https:
disableHttpPort: false
extraPorts: []
loadBalancerIP:
loadBalancerSourceRanges: []
# chp relates to the proxy pod, which is responsible for routing traffic based
# on dynamic configuration sent from JupyterHub to CHP's REST API.
chp:
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
image:
name: jupyterhub/configurable-http-proxy
tag: 4.5.0 # https://github.com/jupyterhub/configurable-http-proxy/releases
pullPolicy:
pullSecrets: []
extraCommandLineFlags: []
livenessProbe:
enabled: true
initialDelaySeconds: 60
periodSeconds: 10
readinessProbe:
enabled: true
initialDelaySeconds: 0
periodSeconds: 2
failureThreshold: 1000
resources: {}
defaultTarget:
errorTarget:
extraEnv: {}
nodeSelector: {}
tolerations: []
networkPolicy:
enabled: true
ingress: []
egress:
- to:
- ipBlock:
cidr: 0.0.0.0/0
interNamespaceAccessLabels: ignore
allowedIngressPorts: [http, https]
pdb:
enabled: false
maxUnavailable:
minAvailable: 1
extraPodSpec: {}
# traefik relates to the autohttps pod, which is responsible for TLS
# termination when proxy.https.type=letsencrypt.
traefik:
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
image:
name: traefik
tag: v2.4.11 # ref: https://hub.docker.com/_/traefik?tab=tags
pullPolicy:
pullSecrets: []
hsts:
includeSubdomains: false
preload: false
maxAge: 15724800 # About 6 months
resources: {}
labels: {}
extraEnv: {}
extraVolumes: []
extraVolumeMounts: []
extraStaticConfig: {}
extraDynamicConfig: {}
nodeSelector: {}
tolerations: []
extraPorts: []
networkPolicy:
enabled: true
ingress: []
egress:
- to:
- ipBlock:
cidr: 0.0.0.0/0
interNamespaceAccessLabels: ignore
allowedIngressPorts: [http, https]
pdb:
enabled: false
maxUnavailable:
minAvailable: 1
serviceAccount:
annotations: {}
extraPodSpec: {}
secretSync:
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
image:
name: jupyterhub/k8s-secret-sync
tag: "1.2.0"
pullPolicy:
pullSecrets: []
resources: {}
labels: {}
https:
enabled: false
type: letsencrypt
#type: letsencrypt, manual, offload, secret
letsencrypt:
contactEmail:
# Specify custom server here (https://acme-staging-v02.api.letsencrypt.org/directory) to hit staging LE
acmeServer: https://acme-v02.api.letsencrypt.org/directory
manual:
key:
cert:
secret:
${REDACTED}
key: tls.key
crt: tls.crt
hosts: []
# singleuser relates to the configuration of KubeSpawner which runs in the hub
# pod, and its spawning of user pods such as jupyter-myusername.
singleuser:
podNameTemplate:
extraTolerations: []
nodeSelector: {}
extraNodeAffinity:
required: []
preferred: []
extraPodAffinity:
required: []
preferred: []
extraPodAntiAffinity:
required: []
preferred: []
networkTools:
image:
name: jupyterhub/k8s-network-tools
tag: "1.2.0"
pullPolicy:
pullSecrets: []
cloudMetadata:
# block set to true will append a privileged initContainer using the
# iptables to block the sensitive metadata server at the provided ip.
blockWithIptables: true
ip: 169.254.169.254
networkPolicy:
enabled: true
ingress: []
egress:
# Required egress to communicate with the hub and DNS servers will be
# augmented to these egress rules.
#
# This default rule explicitly allows all outbound traffic from singleuser
# pods, except to a typical IP used to return metadata that can be used by
# someone with malicious intent.
- to:
- ipBlock:
cidr: 0.0.0.0/0
except:
- 169.254.169.254/32
interNamespaceAccessLabels: ignore
allowedIngressPorts: []
events: true
extraAnnotations: {}
extraLabels:
hub.jupyter.org/network-access-hub: "true"
extraFiles: {}
extraEnv: {}
lifecycleHooks: {}
initContainers: []
extraContainers: []
uid: 1000
fsGid: 100
serviceAccountName:
# Jupyter notebook 이 구동되는 팟의 home 디렉토리
storage:
type: dynamic
extraLabels: {}
extraVolumes: []
extraVolumeMounts: []
static:
pvcName:
subPath: "{username}"
capacity: 10Gi
homeMountPath: /home/jovyan
dynamic:
storageClass:
pvcNameTemplate: claim-{username}{servername}
volumeNameTemplate: volume-{username}{servername}
storageAccessModes: [ReadWriteOnce]
image:
name: redmine:8443/encore/jupyter/all-spark-notebook
tag: "latest" # 팟의 이미를 수정했을 때 빠른 반영을 위해 latest 선택
# notebook server를 시작(또는 재시작) 할 때 팟 이미지를 새로 가져온다.
pullPolicy:
pullSecrets: []
startTimeout: 300
cpu:
limit:
guarantee:
memory:
limit:
guarantee: 1G
extraResource:
limits: {}
guarantees: {}
cmd: jupyterhub-singleuser
defaultUrl: "/lab" #Jupyter notebook을 사용하는 경우 비운다.
extraPodConfig: {}
# 여러개의 notebook image를 선택적으로 제공하는 경우
profileList:
- display_name: "ALL spark notebook"
description: "All spark notebook from jupyter hub stack"
default: true
- display_name: "MINIMAL spark notebook"
description: "Minimal spark notebook from jupyter hub stack"
kubespawner_override:
image: redmine:8443/encore/jupyter/minimal-spark-notebook:latest
# scheduling relates to the user-scheduler pods and user-placeholder pods.
scheduling:
userScheduler:
enabled: true
replicas: 2
logLevel: 4
# plugins ref: https://kubernetes.io/docs/reference/scheduling/config/#scheduling-plugins-1
plugins:
score:
disabled:
- name: SelectorSpread
- name: TaintToleration
- name: PodTopologySpread
- name: NodeResourcesBalancedAllocation
- name: NodeResourcesLeastAllocated
# Disable plugins to be allowed to enable them again with a different
# weight and avoid an error.
- name: NodePreferAvoidPods
- name: NodeAffinity
- name: InterPodAffinity
- name: ImageLocality
enabled:
- name: NodePreferAvoidPods
weight: 161051
- name: NodeAffinity
weight: 14631
- name: InterPodAffinity
weight: 1331
- name: NodeResourcesMostAllocated
weight: 121
- name: ImageLocality
weight: 11
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
image:
# IMPORTANT: Bumping the minor version of this binary should go hand in
# hand with an inspection of the user-scheduelrs RBAC resources
# that we have forked.
name: k8s.gcr.io/kube-scheduler
tag: v1.19.13 # ref: https://github.com/kubernetes/website/blob/main/content/en/releases/patch-releases.md
pullPolicy:
pullSecrets: []
nodeSelector: {}
tolerations: []
pdb:
enabled: true
maxUnavailable: 1
minAvailable:
resources: {}
serviceAccount:
annotations: {}
extraPodSpec: {}
podPriority:
enabled: false
globalDefault: false
defaultPriority: 0
userPlaceholderPriority: -10
userPlaceholder:
enabled: true
image:
name: k8s.gcr.io/pause
# tag's can be updated by inspecting the output of the command:
# gcloud container images list-tags k8s.gcr.io/pause --sort-by=~tags
#
# If you update this, also update prePuller.pause.image.tag
tag: "3.5"
pullPolicy:
pullSecrets: []
replicas: 0
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
resources: {}
corePods:
tolerations:
- key: hub.jupyter.org/dedicated
operator: Equal
value: core
effect: NoSchedule
- key: hub.jupyter.org_dedicated
operator: Equal
value: core
effect: NoSchedule
nodeAffinity:
matchNodePurpose: prefer
userPods:
tolerations:
- key: hub.jupyter.org/dedicated
operator: Equal
value: user
effect: NoSchedule
- key: hub.jupyter.org_dedicated
operator: Equal
value: user
effect: NoSchedule
nodeAffinity:
matchNodePurpose: prefer
# prePuller relates to the hook|continuous-image-puller DaemonsSets
prePuller:
annotations: {}
resources: {}
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
extraTolerations: []
# hook relates to the hook-image-awaiter Job and hook-image-puller DaemonSet
hook:
enabled: true
pullOnlyOnChanges: true
# image and the configuration below relates to the hook-image-awaiter Job
image:
name: jupyterhub/k8s-image-awaiter
tag: "1.2.0"
pullPolicy:
pullSecrets: []
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
podSchedulingWaitDuration: 10
nodeSelector: {}
tolerations: []
resources: {}
serviceAccount:
annotations: {}
continuous:
enabled: true
pullProfileListImages: true
extraImages: {}
pause:
containerSecurityContext:
runAsUser: 65534 # nobody user
runAsGroup: 65534 # nobody group
allowPrivilegeEscalation: false
image:
name: k8s.gcr.io/pause
# tag's can be updated by inspecting the output of the command:
# gcloud container images list-tags k8s.gcr.io/pause --sort-by=~tags
#
# If you update this, also update scheduling.userPlaceholder.image.tag
tag: "3.5"
pullPolicy:
pullSecrets: []
ingress:
enabled: false
annotations: {}
hosts: []
pathSuffix:
pathType: Prefix
tls: []
# cull relates to the jupyterhub-idle-culler service, responsible for evicting
# inactive singleuser pods.
#
# The configuration below, except for enabled, corresponds to command-line flags
# for jupyterhub-idle-culler as documented here:
# https://github.com/jupyterhub/jupyterhub-idle-culler#as-a-standalone-script
#
cull:
enabled: true
users: false # --cull-users
removeNamedServers: false # --remove-named-servers
timeout: 3600 # --timeout
every: 600 # --cull-every
concurrency: 10 # --concurrency
maxAge: 0 # --max-age
debug:
enabled: false
global:
safeToShowValues: false
¶ 설치
압축을 해제한 디렉토리에서 수행한다
helm upgrade --cleanup-on-fail --install jupyterhub jupyterhub/jupyterhub --namespace jupyterhub --create-namespace --values values.yaml
$ helm upgrade --cleanup-on-fail \
--install jupyter haedong/jupyterhub \
# jupyter:사용하고자 하는 이름 haedong/jupyterhub:리포지터리의 이름
--namespace jupyter \
--create-namespace
Release "jupyter" does not exist. Installing it now.
NAME: jupyter
LAST DEPLOYED: Wed Nov 24 08:38:02 2021
NAMESPACE: jupyter
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
Thank you for installing JupyterHub!
Your release is named "jupyter" and installed into the namespace "jupyter".
You can check whether the hub and proxy are ready by running:
kubectl --namespace=jupyter get pod
and watching for both those pods to be in status 'Running'.
You can find the public (load-balancer) IP of JupyterHub by running:
kubectl -n jupyter get svc proxy-public -o jsonpath='{.status.loadBalancer.ingress[].ip}'
It might take a few minutes for it to appear!
To get full information about the JupyterHub proxy service run:
kubectl --namespace=jupyter get svc proxy-public
If you have questions, please:
1. Read the guide at https://z2jh.jupyter.org
2. Ask for help or chat to us on https://discourse.jupyter.org/
3. If you find a bug please report it at https://github.com/jupyterhub/zero-to-jupyterhub-k8s/issues
¶ 확인
[haedong@haedongg.net:~/jupyterhub:]$ kubectl get all -n jupyter
NAME READY STATUS RESTARTS AGE
pod/continuous-image-puller-d8prj 1/1 Running 0 53m
pod/continuous-image-puller-m72nr 1/1 Running 0 53m
pod/continuous-image-puller-mncvb 1/1 Running 0 53m
pod/hub-76b767dd57-lhsrg 1/1 Running 0 53m
pod/jupyter-admin 1/1 Running 0 33m
pod/jupyter-encore 1/1 Running 0 42m
pod/proxy-7d8c4d84f9-rjs79 1/1 Running 0 53m
pod/user-scheduler-7ff857c86b-gx2t5 1/1 Running 0 53m
pod/user-scheduler-7ff857c86b-xb7z7 1/1 Running 0 53m
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/hub ClusterIP 10.105.55.90 <none> 8081/TCP 53m
service/proxy-api ClusterIP 10.98.68.237 <none> 8001/TCP 53m
service/proxy-public LoadBalancer 10.111.11.67 <pending> 80:32608/TCP 53m
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE
daemonset.apps/continuous-image-puller 3 3 3 3 3 <none> 53m
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/hub 1/1 1 1 53m
deployment.apps/proxy 1/1 1 1 53m
deployment.apps/user-scheduler 2/2 2 2 53m
NAME DESIRED CURRENT READY AGE
replicaset.apps/hub-76b767dd57 1 1 1 53m
replicaset.apps/proxy-7d8c4d84f9 1 1 1 53m
replicaset.apps/user-scheduler-7ff857c86b 2 2 2 53m
NAME READY AGE
statefulset.apps/user-placeholder 0/0 53m
마스터 노드의 32608 port로 접속할 수 있다.
¶ 예시
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¶ 노드 선택
다음을 추가한다.
cmd: jupyterhub-singleuser
defaultUrl:
extraPodConfig: {}
profileList:
- display_name: "Minimal notebook"
description: "Minimal spark notebook from jupyter hub stack"
default: true
kubespawner_override:
node_affinity_preferred:
- weight: 1
preference:
matchExpressions:
- key: nvidia.com/gpu.deploy.operands
operator: In
values:
- "false"
extra_resource_limits:
nvidia.com/gpu: "0"
- display_name: "All spark notebook"
description: "All spark notebook from jupyter hub stack"
kubespawner_override:
image: repository:8443/library/jupyter/all-pyspark-notebook:latest
extra_resource_limits:
nvidia.com/gpu: "1"