Cases2 cases

1 to 2 of 2

1. IL-0469 The managed Azure Kubernetes API server for the data100 hub stopped answering, so the stopped hub pod was not recreated

   UC Berkeley2019

   Symptoms

   On 25 February 2019 the Kubernetes API server of the managed Azure cluster running the data100 hub became unreachable. kubectl failed for every operation and requests to create new resources failed, so when the hub pod stopped, no new one was created and users saw a proxy error message.

   Control plane unresponsiveService outage

   Root cause

   Cloud provider outage

   Component

   AKS control planeKubernetes API serverkubelet

   Contributing factor

   Limited debug access

   Detection

   Infrastructure staff were notified in Slack at 11:34 and found that kubectl failed for all operations while the hub proxy was up.

   Remediation

   • Created a new cluster and requested a new NFS server in its resource group
   • Detached the data volumes from the old NFS server and moved them to the new cluster's resource group
   • Imported the ZFS pool into the new NFS server
   • Created the staging hub with helm and updated DNS
   • Created the prod hub with helm and updated DNS

   Action items

   • Monitor the API server endpoint remotely and alert when it is down

   View case
2. IL-0506 UC Berkeley DataHub logins failed and students got empty home directories after the JupyterHub database was overwritten

   UC Berkeley2017

   Symptoms

   At about 1 AM on 9 February 2017, UC Berkeley's DataHub was reported down: users trying to log in got a proxy error. The hub pod was running, but its log was full of sqlite errors.

   Service outageData lossMisrouted requests

   Trigger

   While debugging, an operator ran `.save jupyterhub.sqlite` in sqlite3 inside the hub pod without having attached the database, which replaced the JupyterHub database file with an empty one.

   Root cause

   Operator error

   Component

   DatabasePersistent volumes and stateful setsJupyterHub

   Contributing factor

   No safeguard on destructive changeUnsafe failure behaviourHarmful manual action

   Detection

   DataHub was reported down at about 1 AM, when users got a proxy error at login. At 1:12 AM a user reported that he could log in but all his notebooks were gone.

   Remediation

   • Scaled the hub to 0 replicas
   • Rebuilt the JupyterHub sqlite database by matching Kubernetes PVC names back to user ids
   • Set cookie_id to null instead of a dummy value and attached the rebuilt database to the hub
   • Changed the cookie secret in the hub pod and restarted it to log all users out
   • Deleted all user pods to log everyone out
   • Ran a script that filled in cookie_id for all users, restarted the hub and deleted all user pods again
   • Dropped the new users with a '.' in their name and renamed the older users from '-' to '.'

   Action items

   • Report upstream that JupyterHub uses only part of the cookie secret and discards the rest
   • Report upstream that the cookie_id column of the users table should have UNIQUE and NOT NULL constraints
   • Ask KubeSpawner to support username hashes in PVC and pod names so the names stay the same when the database is deleted
   • Ask OAuthenticator to support using the id from the Google authenticator as the user id, giving stable user ids
   • Switch to Google Cloud SQL, a hosted and managed MySQL database
   • Take regular and tested backups of the database
   • Start an operational FAQ of things to do and not to do
   • Set up better monitoring and paging
   • Document escalation procedures explicitly

   View case

By root cause2