Incident Library
  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases3 cases

1 to 3 of 3

  1. Symptoms

    At 12:00 EST the health check system reported that the backend APIs, the frontend and the tunnels in the EU region were down. The team first took it for a transient error, such as an interrupted client request or a server evicted for memory or CPU pressure, but the main dashboard was offline as well.

    Root cause
    Component
    Contributing factor
    Detection

    The health check system sent a notification that the service was down; the team then found the main dashboard offline.

    Remediation
    • recreated the node pools by hand after the credential rotation failed to recreate them
    • duplicated the main cluster's services into a newly created GKE cluster
    • deleted the Kubernetes Service records in the old cluster so its load balancers could be attached to the new cluster
    • detached the StatefulSet from the old cluster and switched all writes to the main disk
    • exported the data from the temporary ClickHouse instance and inserted it into the main instance
    Action items
    • Change the deployment manifests so services can be switched between clusters quickly without a complicated persistent disk migration
    Lessons

    Recovery of existing infrastructure needs a time limit. Throughout the outage the old cluster looked about to recover, and the reluctance to give up on the salvage effort kept the team from starting over with a new cluster much sooner, which would have been the right call. On older GKE clusters, check the validity of the cluster CA certificate, for example by decoding masterAuth.clusterCaCertificate from gcloud container clusters describe and reading it with openssl x509. GKE's multiple availability zones made no difference in this failure.

  2. Symptoms

    On Saturday 8 July 2018 at about 18:30 CEST, the launch success rate of mybinder.org dropped to zero and stayed there. Suspicious behaviour was first reported on Gitter at 22:48, more than four hours later.

    Root cause
    Component
    Contributing factor
    Detection

    Suspicious behaviour was reported on Gitter at 22:48 CEST, more than four hours after launch success dropped to zero; no downtime notifications were set up.

    Remediation
    • Deleted user pods older than four hours with the delete-pods.py script
    • Culled pods of the most-used images, such as ipython-in-depth, more aggressively
    • Restarted the Hub pod after about 600 pods were culled, which brought launches back to normal
    • Cordoned some of the extra nodes so the autoscaler could reclaim them
    • Ran manual max-age culling the next morning, letting the cluster scale back to 3 nodes
    Action items
    • Set up notifications of downtime
    • Automate cluster scale-down
    • Document the downtime recovery steps so every team member knows them
    • Fix KubeSpawner's failure to delete pods when the pod reflector fails
    • Make KubeSpawner more robust to pod reflector failure
    • Refactor the event reflector into a single reflector instead of one per pod
    • Detect a likely unhealthy Hub state and restart the Hub without manual intervention
    Lessons

    The delete-pods.py script was useful for bulk-deleting old pods, and once the problem was noticed the cluster was healthy within a few minutes. The outage lasted five hours before anyone noticed because no downtime notifications existed, and scaling the cluster back down still took several manual steps of cordoning and draining nodes.

  3. Symptoms

    A user reported that pods were starting up and then vanishing. When the cluster operators looked, kubectl get pods and kubectl get nodes returned two different sets of data that alternated back and forth, as if there were two opinions of the cluster's state.

    Trigger

    etcd write latency rose far above the healthy single-digit milliseconds; the speakers say trouble starts once the database sync time crosses double digits or several hundred milliseconds.

    Root cause
    Component
    Contributing factor
    Detection

    A user reported pods starting up and vanishing.

    Remediation
    • restored service on a replacement cluster
    • freed persistent volumes from the old cluster one by one so they could bind in the new cluster
    • updated DNS records that pointed at the old cluster's load balancer names
    Action items
    • Make the Kubernetes API server request quorum reads from etcd
    Lessons

    etcd is extremely sensitive to write latency; once the database sync time crosses double digits of milliseconds, stale reads or badly degraded performance follow. Without quorum reads, a consistent store can still hand out stale data. Documentation for a fast-moving system changes, so read it again regularly. Moving workloads to a new cluster is hard when they hold persistent volumes or when DNS records point at generated load balancer names.

Check your cluster for this

These 3 cases involve Kubernetes API server and etcd. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause2