# fullnameOverride and nameOverride distinguishes blank strings, null values, # and non-blank strings. For more details, see the configuration reference. fullnameOverride: "" nameOverride: # enabled is ignored by the jupyterhub chart itself, but a chart depending on # the jupyterhub chart conditionally can make use this config option as the # condition. enabled: # 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: create: false automaticReferenceInjection: true registry: username: password: email: # 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: revisionHistoryLimit: config: JupyterHub: admin_access: true authenticator_class: dummy service: type: ClusterIP annotations: {} ports: nodePort: extraPorts: [] loadBalancerIP: baseUrl: / cookieSecret: initContainers: [] 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: url: password: labels: {} annotations: {} command: [] args: [] extraConfig: {} extraFiles: {} extraEnv: {} extraContainers: [] extraVolumes: [] extraVolumeMounts: [] image: name: jupyterhub/k8s-hub tag: "3.0.3" pullPolicy: pullSecrets: [] resources: {} podSecurityContext: fsGroup: 1000 containerSecurityContext: runAsUser: 1000 runAsGroup: 1000 allowPrivilegeEscalation: false lifecycle: {} loadRoles: {} services: {} pdb: enabled: false maxUnavailable: minAvailable: 1 networkPolicy: enabled: true ingress: [] egress: [] egressAllowRules: cloudMetadataServer: true dnsPortsCloudMetadataServer: true dnsPortsKubeSystemNamespace: true dnsPortsPrivateIPs: true nonPrivateIPs: true privateIPs: true 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: serviceAccount: create: true name: annotations: {} extraPodSpec: {} rbac: create: 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: {} nodePorts: http: 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: revisionHistoryLimit: containerSecurityContext: runAsUser: 65534 # nobody user runAsGroup: 65534 # nobody group allowPrivilegeEscalation: false image: name: jupyterhub/configurable-http-proxy # tag is automatically bumped to new patch versions by the # watch-dependencies.yaml workflow. # tag: "4.5.6" # https://github.com/jupyterhub/configurable-http-proxy/tags pullPolicy: pullSecrets: [] extraCommandLineFlags: [] livenessProbe: enabled: true initialDelaySeconds: 60 periodSeconds: 10 failureThreshold: 30 timeoutSeconds: 3 readinessProbe: enabled: true initialDelaySeconds: 0 periodSeconds: 2 failureThreshold: 1000 timeoutSeconds: 1 resources: {} defaultTarget: errorTarget: extraEnv: {} nodeSelector: {} tolerations: [] networkPolicy: enabled: true ingress: [] egress: [] egressAllowRules: cloudMetadataServer: true dnsPortsCloudMetadataServer: true dnsPortsKubeSystemNamespace: true dnsPortsPrivateIPs: true nonPrivateIPs: true privateIPs: true 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: revisionHistoryLimit: containerSecurityContext: runAsUser: 65534 # nobody user runAsGroup: 65534 # nobody group allowPrivilegeEscalation: false image: name: traefik # tag is automatically bumped to new patch versions by the # watch-dependencies.yaml workflow. # tag: "v2.10.4" # ref: https://hub.docker.com/_/traefik?tab=tags pullPolicy: pullSecrets: [] hsts: includeSubdomains: false preload: false maxAge: 15724800 # About 6 months resources: {} labels: {} extraInitContainers: [] extraEnv: {} extraVolumes: [] extraVolumeMounts: [] extraStaticConfig: {} extraDynamicConfig: {} nodeSelector: {} tolerations: [] extraPorts: [] networkPolicy: enabled: true ingress: [] egress: [] egressAllowRules: cloudMetadataServer: true dnsPortsCloudMetadataServer: true dnsPortsKubeSystemNamespace: true dnsPortsPrivateIPs: true nonPrivateIPs: true privateIPs: true interNamespaceAccessLabels: ignore allowedIngressPorts: [http, https] pdb: enabled: false maxUnavailable: minAvailable: 1 serviceAccount: create: true name: annotations: {} extraPodSpec: {} secretSync: containerSecurityContext: runAsUser: 65534 # nobody user runAsGroup: 65534 # nobody group allowPrivilegeEscalation: false image: name: jupyterhub/k8s-secret-sync tag: "3.0.3" 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: name: 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: "3.0.3" pullPolicy: pullSecrets: [] resources: {} 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: [] egressAllowRules: cloudMetadataServer: false dnsPortsCloudMetadataServer: true dnsPortsKubeSystemNamespace: true dnsPortsPrivateIPs: true nonPrivateIPs: true privateIPs: false interNamespaceAccessLabels: ignore allowedIngressPorts: [] events: true extraAnnotations: {} extraLabels: hub.jupyter.org/network-access-hub: "true" extraFiles: {} extraEnv: {} lifecycleHooks: {} initContainers: [] extraContainers: [] allowPrivilegeEscalation: false uid: 1000 fsGid: 100 serviceAccountName: 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: jupyterhub/k8s-singleuser-sample tag: "3.0.3" pullPolicy: pullSecrets: [] startTimeout: 300 cpu: limit: guarantee: memory: limit: guarantee: 1G extraResource: limits: {} guarantees: {} cmd: jupyterhub-singleuser defaultUrl: extraPodConfig: {} profileList: [] # scheduling relates to the user-scheduler pods and user-placeholder pods. scheduling: userScheduler: enabled: true revisionHistoryLimit: replicas: 2 logLevel: 4 # plugins are configured on the user-scheduler to make us score how we # schedule user pods in a way to help us schedule on the most busy node. By # doing this, we help scale down more effectively. It isn't obvious how to # enable/disable scoring plugins, and configure them, to accomplish this. # # plugins ref: https://kubernetes.io/docs/reference/scheduling/config/#scheduling-plugins-1 # migration ref: https://kubernetes.io/docs/reference/scheduling/config/#scheduler-configuration-migrations # plugins: score: # These scoring plugins are enabled by default according to # https://kubernetes.io/docs/reference/scheduling/config/#scheduling-plugins # 2022-02-22. # # Enabled with high priority: # - NodeAffinity # - InterPodAffinity # - NodeResourcesFit # - ImageLocality # Remains enabled with low default priority: # - TaintToleration # - PodTopologySpread # - VolumeBinding # Disabled for scoring: # - NodeResourcesBalancedAllocation # disabled: # We disable these plugins (with regards to scoring) to not interfere # or complicate our use of NodeResourcesFit. - name: NodeResourcesBalancedAllocation # Disable plugins to be allowed to enable them again with a different # weight and avoid an error. - name: NodeAffinity - name: InterPodAffinity - name: NodeResourcesFit - name: ImageLocality enabled: - name: NodeAffinity weight: 14631 - name: InterPodAffinity weight: 1331 - name: NodeResourcesFit weight: 121 - name: ImageLocality weight: 11 pluginConfig: # Here we declare that we should optimize pods to fit based on a # MostAllocated strategy instead of the default LeastAllocated. - name: NodeResourcesFit args: scoringStrategy: resources: - name: cpu weight: 1 - name: memory weight: 1 type: MostAllocated 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 in # templates/scheduling/user-scheduler/rbac.yaml. # # Debugging advice: # # - Is configuration of kube-scheduler broken in # templates/scheduling/user-scheduler/configmap.yaml? # # - Is the kube-scheduler binary's compatibility to work # against a k8s api-server that is too new or too old? # # - You can update the GitHub workflow that runs tests to # include "deploy/user-scheduler" in the k8s namespace report # and reduce the user-scheduler deployments replicas to 1 in # dev-config.yaml to get relevant logs from the user-scheduler # pods. Inspect the "Kubernetes namespace report" action! # # - Typical failures are that kube-scheduler fails to search for # resources via its "informers", and won't start trying to # schedule pods before they succeed which may require # additional RBAC permissions or that the k8s api-server is # aware of the resources. # # - If "successfully acquired lease" can be seen in the logs, it # is a good sign kube-scheduler is ready to schedule pods. # name: registry.k8s.io/kube-scheduler # tag is automatically bumped to new patch versions by the # watch-dependencies.yaml workflow. The minor version is pinned in the # workflow, and should be updated there if a minor version bump is done # here. We aim to stay around 1 minor version behind the latest k8s # version. # tag: "v1.26.8" # ref: https://github.com/kubernetes/kubernetes/tree/master/CHANGELOG pullPolicy: pullSecrets: [] nodeSelector: {} tolerations: [] labels: {} annotations: {} pdb: enabled: true maxUnavailable: 1 minAvailable: resources: {} serviceAccount: create: true name: annotations: {} extraPodSpec: {} podPriority: enabled: false globalDefault: false defaultPriority: 0 imagePullerPriority: -5 userPlaceholderPriority: -10 userPlaceholder: enabled: true image: name: registry.k8s.io/pause # tag is automatically bumped to new patch versions by the # watch-dependencies.yaml workflow. # # If you update this, also update prePuller.pause.image.tag # tag: "3.9" pullPolicy: pullSecrets: [] revisionHistoryLimit: replicas: 0 labels: {} annotations: {} 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: revisionHistoryLimit: labels: {} 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: "3.0.3" pullPolicy: pullSecrets: [] containerSecurityContext: runAsUser: 65534 # nobody user runAsGroup: 65534 # nobody group allowPrivilegeEscalation: false podSchedulingWaitDuration: 10 nodeSelector: {} tolerations: [] resources: {} serviceAccount: create: true name: annotations: {} continuous: enabled: true pullProfileListImages: true extraImages: {} pause: containerSecurityContext: runAsUser: 65534 # nobody user runAsGroup: 65534 # nobody group allowPrivilegeEscalation: false image: name: registry.k8s.io/pause # tag is automatically bumped to new patch versions by the # watch-dependencies.yaml workflow. # # If you update this, also update scheduling.userPlaceholder.image.tag # tag: "3.9" pullPolicy: pullSecrets: [] ingress: enabled: false annotations: {} ingressClassName: 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 adminUsers: true # --cull-admin-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