project_name: do-pytest
provider: do
domain: do.nebari.dev
certificate:
  type: self-signed
security:
  authentication:
    type: custom
    authentication_class: 'firstuseauthenticator.FirstUseAuthenticator'
    config:
       min_password_length: 5
  users:
    example-user:
      uid: 1000
      primary_group: admin
      secondary_groups:
      - users
      password: $2b$12$YrEkTAEFfo4fKO7lYPpReegKagd1irrW5YmRugJcaPCjkVaPzrVLq
  groups:
    users:
      gid: 100
    admin:
      gid: 101
default_images:
  jupyterhub: quansight/nebari-jupyterhub:v0.3.10
  jupyterlab: quansight/nebari-jupyterlab:v0.3.10
  dask_worker: quansight/nebari-dask-worker:v0.3.10
  dask_gateway: quansight/nebari-dask-gateway:v0.3.10
storage:
  conda_store: 60Gi
  shared_filesystem: 100Gi
theme:
  jupyterhub:
    hub_title: Nebari - do-pytest
    hub_subtitle: Autoscaling Compute Environment on Digital Ocean
    welcome: Welcome to do.nebari.dev. It is maintained by <a href="http://quansight.com">Quansight
      staff</a>. The hub's configuration is stored in a github repository based on
      <a href="https://github.com/Quansight/nebari/">https://github.com/Quansight/nebari/</a>.
      To provide feedback and report any technical problems, please use the <a href="https://github.com/Quansight/nebari/issues">github
      issue tracker</a>.
    logo: /hub/custom/images/jupyter_nebari_logo.svg
    primary_color: '#4f4173'
    secondary_color: '#957da6'
    accent_color: '#32C574'
    text_color: '#111111'
    h1_color: '#652e8e'
    h2_color: '#652e8e'
terraform_state:
  type: remote
namespace: dev
digital_ocean:
  region: nyc3
  kubernetes_version: 1.21.5-do.0
  node_groups:
    general:
      instance: s-2vcpu-4gb
      min_nodes: 1
      max_nodes: 1
    user:
      instance: g-2vcpu-8gb
      min_nodes: 1
      max_nodes: 5
    worker:
      instance: g-2vcpu-8gb
      min_nodes: 1
      max_nodes: 5
profiles:
  jupyterlab:
  - display_name: Small Instance
    description: Stable environment with 1 cpu / 4 GB ram
    default: true
    kubespawner_override:
      cpu_limit: 1
      cpu_guarantee: 0.75
      mem_limit: 4G
      mem_guarantee: 2.5G
      image: quansight/nebari-jupyterlab:v0.3.10
  - display_name: Medium Instance
    description: Stable environment with 2 cpu / 8 GB ram
    kubespawner_override:
      cpu_limit: 2
      cpu_guarantee: 1.5
      mem_limit: 8G
      mem_guarantee: 5G
      image: quansight/nebari-jupyterlab:v0.3.10
  dask_worker:
    Small Worker:
      worker_cores_limit: 1
      worker_cores: 0.75
      worker_memory_limit: 4G
      worker_memory: 2.5G
      worker_threads: 1
      image: quansight/nebari-dask-worker:v0.3.10
    Medium Worker:
      worker_cores_limit: 2
      worker_cores: 1.5
      worker_memory_limit: 8G
      worker_memory: 5G
      worker_threads: 2
      image: quansight/nebari-dask-worker:v0.3.10
environments:
  environment-dask.yaml:
    name: dask
    channels:
    - conda-forge
    dependencies:
    - python
    - ipykernel
    - ipywidgets
    - python-graphviz
    - dask ==2.30.0
    - distributed ==2.30.1
    - dask-gateway ==0.9.0
    - numpy
    - numba
    - pandas
  environment-dashboard.yaml:
    name: dashboard
    channels:
    - conda-forge
    dependencies:
    - python
    - ipykernel
    - ipywidgets >=7.6
    - param
    - python-graphviz
    - matplotlib >=3.3.4
    - panel >=0.10.3
    - voila >=0.2.7
    - streamlit >=0.76
    - dash >=1.19
