This is a code test !
---
# nameOverride: dask
# fullnameOverride: dask
scheduler:
name: scheduler # Dask scheduler name.
enabled: true # Enable/disable scheduler.
image:
repository: "harbor-repo.vmware.com/dockerhub-proxy-cache/daskdev/dask" # Container image repository.
tag: 2021.4.1 # Container image tag.
pullPolicy: IfNotPresent # Container image pull policy.
pullSecrets: # Container image [pull secrets](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
# - name: regcred
replicas: 1 # Number of schedulers (should always be 1).
serviceType: "LoadBalancer" # Scheduler service type. Set to `LoadBalancer` to expose outside of your cluster.
# serviceType: "NodePort"
# serviceType: "LoadBalancer"
loadBalancerIP: null # Some cloud providers allow you to specify the loadBalancerIP when using the `LoadBalancer` service type. If your cloud does not support it this option will be ignored.
servicePort: 8786 # Scheduler service internal port.
serviceAnnotations: {} # Scheduler service annotations.
extraArgs: [] # Extra CLI arguments to be passed to the scheduler
# - --preload
# - scheduler-setup.py
resources: {} # Scheduler pod resources. See `values.yaml` for example values.
# limits:
# cpu: 1.8
# memory: 6G
# requests:
# cpu: 1.8
# memory: 6G
tolerations: [] # Tolerations.
affinity: {} # Container affinity.
nodeSelector: {} # Node Selector.
securityContext: {} # Security Context.
# serviceAccountName: ""
metrics:
enabled: false # Enable scheduler metrics. Pip package [prometheus-client](https://pypi.org/project/prometheus-client/) should be present on scheduler.
serviceMonitor:
enabled: false # Enable scheduler servicemonitor.
namespace: "" # Deploy servicemonitor in different namespace, e.g. monitoring.
namespaceSelector: {} # Selector to select which namespaces the Endpoints objects are discovered from.
# Default: scrape .Release.Namespace only
# To scrape all, use the following:
# namespaceSelector:
# any: true
interval: 30s # Interval at which metrics should be scraped.
jobLabel: "" # The label to use to retrieve the job name from.
targetLabels: [] # TargetLabels transfers labels on the Kubernetes Service onto the target.
metricRelabelings: [] # MetricRelabelConfigs to apply to samples before ingestion.
webUI:
name: webui # Dask webui name.
servicePort: 80 # webui service internal port.
ingress:
enabled: false # Enable ingress.
tls: false # Ingress should use TLS.
# secretName: dask-scheduler-tls
hostname: dask-ui.example.com # Ingress hostname.
annotations: # Ingress annotations. See `values.yaml` for example values.
# kubernetes.io/ingress.class: "nginx"
# secretName: my-tls-cert
# kubernetes.io/tls-acme: "true"
worker:
name: worker # Dask worker name.
image:
repository: "harbor-repo.vmware.com/dockerhub-proxy-cache/daskdev/dask" # Container image repository.
tag: 2021.4.1 # Container image tag.
pullPolicy: IfNotPresent # Container image pull policy.
dask_worker: "dask-worker" # Dask worker command. E.g `dask-cuda-worker` for GPU worker.
pullSecrets: # Container image [pull secrets](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
# - name: regcred
replicas: 3 # Number of workers.
strategy:
type: RollingUpdate # Strategy used to replace old Pods with new ones.
custom_scheduler_url: null # connect to already existing scheduler, deployed not by this chart.
default_resources: # overwritten by resource limits if they exist
cpu: 1 # Default CPU (DEPRECATED use `resources`).
memory: "4GiB" # Default memory (DEPRECATED use `resources`).
env: # Environment variables. See `values.yaml` for example values.
# - name: EXTRA_APT_PACKAGES
# value: build-essential openssl
# - name: EXTRA_CONDA_PACKAGES
# value: numba xarray -c conda-forge
- name: EXTRA_PIP_PACKAGES
# value: s3fs dask-ml prometheus-client --upgrade
value: s3fs dask-ml mimesis xgboost --upgrade
extraArgs: [] # Extra CLI arguments to be passed to the worker
# - --preload
# - worker-setup.py
resources: {} # Worker pod resources. See `values.yaml` for example values.
# limits:
# cpu: 1
# memory: 3G
# nvidia.com/gpu: 1
# requests:
# cpu: 1
# memory: 3G
# nvidia.com/gpu: 1
mounts: {} # Worker Pod volumes and volume mounts, mounts.volumes follows kuberentes api v1 Volumes spec. mounts.volumeMounts follows kubernetesapi v1 VolumeMount spec
# volumes:
# - name: data
# emptyDir: {}
# volumeMounts:
# - name: data
# mountPath: /data
annotations: {} # Annotations
tolerations: [] # Tolerations.
affinity: {} # Container affinity.
nodeSelector: {} # Node Selector.
securityContext: {} # Security Context.
# serviceAccountName: ""
# port: ""
portDashboard: 8790 # Worker dashboard and metrics port.
# this option overrides "--nthreads" on workers, which defaults to resources.limits.cpu / default_resources.limits.cpu
# use it if you need to limit the amount of threads used by multicore workers, or to make workers with non-whole-number cpu limits
# threads_per_worker: 1
metrics:
enabled: false # Enable workers metrics. Pip package [prometheus-client](https://pypi.org/project/prometheus-client/) should be present on workers.
podMonitor:
enabled: false # Enable workers podmonitor
namespace: "" # Deploy podmonitor in different namespace, e.g. monitoring.
namespaceSelector: {} # Selector to select which namespaces the Endpoints objects are discovered from.
# Default: scrape .Release.Namespace only
# To scrape all, use the following:
# namespaceSelector:
# any: true
interval: 30s # Interval at which metrics should be scraped.
jobLabel: "" # The label to use to retrieve the job name from.
podTargetLabels: [] # PodTargetLabels transfers labels on the Kubernetes Pod onto the target.
metricRelabelings: [] # MetricRelabelConfigs to apply to samples before ingestion.
jupyter:
name: jupyter # Jupyter name.
enabled: true # Enable/disable the bundled Jupyter notebook.
rbac: true # Create RBAC service account and role to allow Jupyter pod to scale worker pods and access logs.
image:
repository: "harbor-repo.vmware.com/dockerhub-proxy-cache/daskdev/dask-notebook" # Container image repository.
tag: 2021.4.1 # Container image tag.
pullPolicy: IfNotPresent # Container image pull policy.
pullSecrets: # Container image [pull secrets](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/).
# - name: regcred
#
replicas: 1 # Number of notebook servers.
serviceType: "LoadBalancer" # Scheduler service type. Set to `LoadBalancer` to expose outside of your cluster.
# serviceType: "NodePort"
# serviceType: "LoadBalancer"
servicePort: 80 # Jupyter service internal port.
# This hash corresponds to the password 'dask'
password: 'sha1:aae8550c0a44:9507d45e087d5ee481a5ce9f4f16f37a0867318c' # Password hash. Default hash corresponds to the password `dask`.
env: # Environment variables. See `values.yaml` for example values.
# - name: EXTRA_CONDA_PACKAGES
# value: "numba xarray -c conda-forge"
- name: EXTRA_PIP_PACKAGES
# value: "s3fs dask-ml --upgrade"
value: s3fs dask-ml mimesis xgboost --upgrade
command: null # Container command.
args: # Container arguments.
# - "start.sh"
# - "jupyter"
# - "lab"
extraConfig: |-
# Extra Jupyter config goes here
# E.g
# c.NotebookApp.port = 8888
resources: {} # Jupyter pod resources. See `values.yaml` for example values.
# limits:
# cpu: 2
# memory: 6G
# requests:
# cpu: 2
# memory: 6G
mounts: {} # Worker Pod volumes and volume mounts, mounts.volumes follows kuberentes api v1 Volumes spec. mounts.volumeMounts follows kubernetesapi v1 VolumeMount spec
# volumes:
# - name: data
# emptyDir: {}
# volumeMounts:
# - name: data
# mountPath: /data
tolerations: [] # Tolerations.
affinity: {} # Container affinity.
nodeSelector: {} # Node Selector.
securityContext: {} # Security Context.
serviceAccountName: "dask-jupyter" # Service account for use with RBAC
ingress:
enabled: false # Enable ingress.
tls: false # Ingress should use TLS.
# secretName: dask-jupyter-tls
hostname: dask-jupyter.example.com # Ingress hostname.
annotations: # Ingress annotations. See `values.yaml` for example values.
# kubernetes.io/ingress.class: "nginx"
# secretName: my-tls-cert
# kubernetes.io/tls-acme: "true"
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