Cases6 cases

3 to 6 of 6

1. IL-0449 Pods on Enigmo's new EKS managed node groups kept restarting or stuck Terminating and the nodes became unusable

   Enigmo2020

   Symptoms

   Two or three days after Enigmo created EKS managed node groups and moved its pods there from the old node groups, the cluster suddenly became unstable: pods restarted again and again or could not stop and stayed around indefinitely, node CPU and memory load rose high, and the nodes became unusable from the cluster.

   Pods stuck in TerminatingSustained high node CPUMemory pressureNode NotReadyUpgrade stall

   Trigger

   Enigmo created EKS managed node groups that used an AMI containing the bug and moved its pods onto them, as preparation for upgrading EKS from 1.15 to 1.16.

   Root cause

   Breaking change in an upgrade

   Component

   Node operating system imageNode pool

   Contributing factor

   Ineffective rollbackChange with a delayed effect

   Remediation

   • Changed the managed node groups' AMI version to the fixed release
   • Ran the managed node group update through CloudFormation
   • Watched the pods across all namespaces during the update
   • Force-deleted every pod that stayed in Terminating with kubectl delete --grace-period=0 --force

   Action items

   • Check the latest releases of the cluster's modules quarterly or monthly and upgrade them regularly

   Lessons

   As long as a team uses Amazon EKS or Kubernetes, it has to keep track of upgrades of the cluster and of modules such as ingress controllers, because a release with breaking changes can be announced without warning after a long stable period. Checking releases and upgrading on a regular schedule keeps the effect of each upgrade on the service small.

   View case
2. IL-0401 Prow jobs on the k8s-prow-build GKE cluster failed and merges stalled as nodes hit IOPS throttling and kernel panics

   Kubernetes project2019

   Symptoms

   On 30 May 2019, in the run-up to the Kubernetes 1.15 code freeze, Prow test jobs in the k8s-prow-build cluster failed in surprising ways or were aborted partway through. Jobs were reported to GitHub as failed while Deck still showed them as running, because pods exited without uploading `finished.json`, the file most Prow tooling uses to tell a job's state.

   Node NotReadyNode kernel panicPods stuck in TerminatingThroughput degradation

   Trigger

   A spike in test load before the Kubernetes 1.15 code freeze pushed disk I/O on the build nodes far beyond the IOPS that GCP allows for 250 GB disks.

   Root cause

   Capacity exhaustion

   Component

   Cloud block storageNode root diskkubeletCI system

   Contributing factor

   Monitoring blind spotIgnored early signal

   Detection

   Several users reported jobs that GitHub showed as failed but Deck showed as still running, and the first report came on Slack at 13:26. Alerting for these failures did not exist or did not work.

   Remediation

   • Requested and received additional disk quota
   • Brought up 55 nodes with 500 GB disks in a new node pool
   • Migrated all nodes from the 250 GB disk pool to the 500 GB disk pool by draining old nodes, finishing at 23:55

   Action items

   • Create or fix monitoring so the oncall is paged when tide stops doing things
   • Set a process and guidelines for adding new members to the oncall rotation, with preparation and extra support

   Lessons

   Prow metrics were not recorded before the incident, which made it hard to understand, and alerting for these failures did not exist or did not work. After the cause was found and a fix devised, nothing happened for another two hours. The team counts it as luck that someone who recognised IOPS as the problem happened to be around to look.

   View case
3. IL-0402 mybinder.org launches dropped to zero for hours because a JupyterHub pod on a lost GKE node kept its hub database PVC

   Binder Project2018

   Symptoms

   On 13 March 2018 at 07:28 CET the mybinder.org team noticed that JupyterHub had not been spawning new users and that the launch success rate on the Grafana dashboard had been at zero for several hours. Many pods were in the states "Unknown" and "NodeLost", on at least the nodes `10.128.0.7` and `10.128.0.5`.

   Service outageNode NotReadyPods stuck in TerminatingPods stuck in ContainerCreating

   Root cause

   unknown

   Component

   Persistent volumes and stateful setsNode pool

   Contributing factor

   Pages not delivered

   Detection

   The team noticed only after several hours, when the launch success rate on the Grafana dashboard had been at zero for a long time. No Stackdriver alert email arrived in time, because those emails were marked as spam and reached the team hours later.

   Remediation

   • Cordoned the bad nodes
   • Deleted the hub pod in Unknown state and the hub pod stuck in ContainerCreating
   • Reset node gke-prod-a-ssd-pool-32-134a959a-n2sk from the GCP web interface to force the PVC to be released
   • Force-deleted every pod in Unknown or NodeLost state with kubectl delete --grace-period=0 --force

   Action items

   • Investigate why the outage started, through Stackdriver logs and Google Cloud incidents
   • Set up an alerting service that does not depend on Stackdriver
   • Document how to check whether a PVC has not been released
   • Document how to restart a node by hand when commands are not working
   • Document how to delete pods that are in Unknown state

   Lessons

   The error went unnoticed for a long time because Stackdriver alert emails were marked as spam and arrived hours late. Once the problem was found, each step was logged and the steps were made more forceful as needed, so the hub was down only briefly after detection.

   View case
4. IL-0507 Student pods on UC Berkeley DataHub got stuck in Terminating or would not start because Docker hung on two Azure nodes

   UC Berkeley2017

   Symptoms

   On 10 October 2017 at 10:45 AM, a post on the course Piazza reported that two students could not start their servers on UC Berkeley's DataHub, and the /hub/admin interface could not start them either. At first it was thought the students might have run out of memory.

   Pods stuck in Terminating

   Root cause

   unknown

   Component

   Container runtime

   Contributing factor

   –

   Detection

   Students reported on the course Piazza at 10:45 AM, and later in the course Slack, that their servers would not start.

   Remediation

   • Force-deleted the stuck user pods with kubectl --namespace=prod delete pod jupyter-<name> --grace-period=0 --force
   • Cordoned node k8s-pool1-19522833-13
   • Force-deleted the stuck pods on k8s-pool2-19522833-9 and cordoned that node
   • Stopped and started k8s-pool1-19522833-13 from the Azure portal, after which Docker responded, and uncordoned it
   • Stopped and started k8s-pool2-19522833-9 from the Azure portal

   Action items

   • When several student servers fail to start or stop, check whether their pods ran on the same nodes
   • Find out how many nodes do not mount /var/lib/docker on sdb1
   • Watch for elevated counts of pods stuck in Terminating

   View case

By root cause5