Cases2 cases

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1. IL-0230 kube-proxy sync failures during a Kubernetes upgrade corrupted node iptables, and CircleCI jobs stopped starting

   CircleCI2023

   Symptoms

   On 14 March 2023 at about 18:00 UTC, communication errors rose on one CircleCI service, and pipelines for all customers began to start late until jobs did not run at all. Within an hour the errors had spread to many services and to every function of the application, including the CircleCI UI and API.

   Service outageIntermittent connection failuresDNS resolution failures

   Trigger

   At about 17:40 UTC on 14 March the infrastructure team resumed the upgrade of the main production Kubernetes cluster with a changed approach for some components, after a first attempt on 13 March had been rolled back. The ongoing upgrade left kubelet and kube-proxy at mismatched versions.

   Root cause

   Breaking change in an upgrade

   Component

   kube-proxykubeletCoreDNSClient-side DNS resolver and cache

   Contributing factor

   Partial rolloutIneffective rollbackMonitoring blind spotHarmful manual action

   Detection

   At 18:00 UTC engineers saw communication errors rise on one service, then job processing delays climbing and job queues backing up across several services. The kube-proxy "Sync failed" errors were found only in the analysis after the incident.

   Remediation

   • Restarted every node in the cluster so each node built a fresh iptables ruleset
   • Restarted a separate pool of dependencies so jobs using contexts or the machine executor ran again
   • Added capacity to work through the backlog of jobs
   • Restarted the RabbitMQ nodes to fix a few corrupted queues

   Action items

   • Improve the Kubernetes upgrade process to limit the risk of future upgrades
   • Add metrics and alerts for kube-proxy sync errors
   • Evaluate ways to make the RabbitMQ infrastructure more resilient

   Lessons

   No single trigger caused the incident. Because networking underlies everything in the cluster, Kubernetes upgrades carry inherent risk, and CircleCI's risk mitigation did not hold up when several events interacted.

   View case
2. IL-0294 CircleCI Docker and machine jobs stalled for nearly 12 hours after a VM cleanup queue lost all its RabbitMQ consumers

   CircleCI2021

   Symptoms

   From 13:30 UTC on 21 May 2021, CircleCI jobs on Docker, the Machine executor (including Windows, Mac, Arm and GPU) and remote Docker were delayed or blocked. Engineers had been paged at 13:00 for excessive delays in starting jobs, and the alerts showed CircleCI could not provision some types and classes of VM because it was hitting its CPU quotas in GCP.

   Throughput degradationCloud API rate limit exhaustedDatabase overload

   Trigger

   The upgrade of the RabbitMQ cluster from 3.8.9 to 3.8.16 on 20 May 2021, which brought in a 15 minute consumer acknowledgement timeout for all queue types.

   Root cause

   Breaking change in an upgrade

   Component

   Message brokerDatabase

   Contributing factor

   Change with a delayed effectIgnored early signalRetry stormExcessive blast radiusOverlapping failures

   Detection

   Engineers were paged at 13:00 UTC on 21 May for excessive delays in starting jobs. Earlier, a 02:31 notification that a VM destroyer queue had no consumers was handled by restarting pods, and a 10:11 alert that a VM destroy queue was backing up notified once at its threshold and did not page.

   Remediation

   • Blocked Linux machine jobs from entering the work queue
   • Had GCP raise the CPU quotas
   • Deleted old VMs by hand
   • Cancelled some workflows to free resources
   • Reset the VM services deployment so the VM destroy queues had consumers again
   • Scaled up the RDS database instance, at 18:20 and again at 19:15
   • Turned down VM provisioning and blocked remote-docker jobs to shed load
   • Scaled down all pods that created and destroyed VMs
   • Deployed a revised distribution backend that kept remote-docker jobs out of the provisioning queues
   • Brought provisioning and distribution back one component at a time and reversed the mitigation code changes

   Action items

   • Make VM provisioning more robust to changes in load so it can recover from thundering herds
   • Make VM provisioning independent so its failure does not affect Docker jobs
   • Review and improve observability of RabbitMQ and the production queues
   • Batch requests to avoid hitting GCP API rate limits
   • Improve incident response for long-running incidents

   View case

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