Cases2 cases

1 to 2 of 2

1. IL-0109 A retried node rollover on a DFDS EKS cluster set the Auto Scaling group back to 15 instances, and the default termination policy removed every healthy worker node, leaving the cluster with no nodes

   DFDS2023sev1

   Symptoms

   At 09:33 UTC on 14 February 2023 end users told the platform team that Kubernetes logs were not arriving in CloudWatch as expected. The investigation went through fluentd and found that the nodes were running containerd as their container runtime instead of docker-shim. A scheduled node rollover the day before, at 07:30 UTC on 13 February, had set containerd as the default runtime by accident.

   Service outageResources deletedMonitoring outage

   Trigger

   A scheduled node rollover had accidentally made containerd the default container runtime, which stopped log shipping to CloudWatch; the unscheduled rollover to revert it timed out, and the pipeline run that followed reduced the Auto Scaling group from 30 to 15 instances.

   Root cause

   Configuration change

   Component

   Container runtimeNode launch templateNode poolTerraformTelemetry agent

   Contributing factor

   Automation amplificationUnreviewed defaultsUnrepresentative stagingNo configuration testsNo runbookHarmful manual action

   Detection

   End users reported the missing CloudWatch logs that started the work. The postmortem lists 2 minutes as the time to detection of the node failure.

   Remediation

   • ran the node rollover script to add new nodes, which failed on a timeout from Docker Hub
   • ran the node rollover script a second time, which added new nodes that the load balancer marked healthy at 11:01 UTC

   Action items

   • Document the rollover process, especially what can be done when it goes wrong
   • Investigate options for improving the rollover process
   • Add fluentd log collection to the QA test suite so logs are covered end to end
   • Add alarms for fluentd when too little or no log data is sent
   • Implement a staging environment
   • Implement guards against selecting an invalid container runtime

   Lessons

   When a change goes wrong, rolling back to a known working configuration is safer than rushing a fix, which can make the damage worse. Launching new worker nodes depends on the cloud-init script not failing in any way. The QA configuration differed from production, there was no staging environment, the QA tests did not cover fluentd log collection, and the rollover process had no documentation for when it fails.

   View case
2. IL-0061 A Terraform pull request merged out of order deleted a production GKE cluster, and recreating it deleted a second one

   Spotify2019

   Symptoms

   Terraform, applied from the shared cluster configuration repository after a merge, deleted Spotify's production GKE cluster in Asia. While the team tried to recreate it, Terraform deleted a second production cluster, so two of the three production clusters were gone.

   Resources deleted

   Trigger

   A feature team's pull request that added three users to an existing RBAC role binding file was merged before the cluster operators' pull request that imported the Asia cluster into Terraform state. The review build of the import pull request had already written the cluster into the shared state file, and the merged configuration had no definition of the Asia cluster, so Terraform removed it.

   Root cause

   Configuration change

   Component

   TerraformCI systemGKE control plane

   Contributing factor

   No safeguard on destructive changeMissed in reviewUnverified assumption

   Detection

   Internal service discovery could not reach the deleted cluster and the cluster operator team was paged.

   Remediation

   • removed the deleted clusters from the service discovery configuration and restarted service discovery so clients fell back to the instances outside Kubernetes
   • one team that ran half on Kubernetes and half on VMs created more VMs outside Kubernetes to handle the load
   • recreated the clusters, using the hourly backups
   • updated the places where the old clusters' master IPs were hardcoded

   Action items

   • Post the Terraform dry-run output as a comment on each pull request
   • Require a status check that the branch is up to date with master, so the dry run reflects what will actually happen
   • Require an approving review on pull requests
   • Fail reviews automatically when certain keywords such as destroy appear; cluster deletions are done manually outside this repository
   • Add linters and validators for the cluster configuration
   • Schedule and announce disaster recovery tests that cover a cluster going away and smaller failures

   Lessons

   Plan for failure from the start and migrate large infrastructure gradually, so there is redundancy and a way back. A backup whose restore has never been tested is not a backup. Practising disaster recovery paid off: restoring the first deleted cluster took three and a quarter hours, and the team can now restore a larger cluster in one hour. What matters is not who made the mistake but what was learned from it.

   View case

By root cause1