Possible to increase mem allocation in JHub via helm?

JupyterHub
1

Hi,

We deploy JupyterHub to Kubernetes (specifically, AWS managed kubernetes “EKS”)
We deploy it via helm.
We run version 0.8.2 of JupyterHub.

We want to know:
(1) What is the default memory allocation for notebook servers?
(2) Is it possible to increase it? How?

For reference, this is our helm chart:

auth:
  admin:
    access: true
    users:
      - REDACTED
  type: github
  github:
    clientId: "REDACTED"
    clientSecret: "REDACTED"
    callbackUrl: "REDACTED"
    org_whitelist:
      - "REDACTED"
  scopes:
    - read:org

singleuser:
  image:
    # Get the latest image tag at:
    # https://hub.docker.com/r/jupyter/datascience-notebook/tags/
    # Inspect the Dockerfile at:
    # https://github.com/jupyter/docker-stacks/tree/master/datascience-notebook/Dockerfile
    # name: jupyter/datascience-notebook
    # tag: 177037d09156
    name: REDACTED
    tag: REDACTED
    pullPolicy: Always
  storage:
    capacity: 32Gi

  lifecycleHooks:
    postStart:
      exec:
        command: ["/bin/sh", "-c", "touch ~/.env && chmod 777 ~/.env"]

hub:
  # cookie_max_age_days - determines how long we keep the github
  # cookie in the hub server (in days).
  # cull_idle_servers time out - determines how long it takes before
  # we kick out an inactive user and shut down their user server.
  extraConfig: |
    import sys
    c.JupyterHub.cookie_max_age_days = 2
    c.JupyterHub.services = [
        {
            "name": "cull-idle",
            "admin": True,
            "command": [sys.executable, "/usr/local/bin/cull_idle_servers.py", "--timeout=3600"],
        }
    ]
2

The default memory limit will be determined by your K8S cluster (might be unlimited?). The Helm chart has some configuration options to limit CPU and memory (this is for the latest version of the chart, but I don’t think it’s changed):
https://zero-to-jupyterhub.readthedocs.io/en/latest/customizing/user-resources.html