Cases14 cases

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1. IL-0014 A GKE upgrade to a withdrawn version stalled on slow drains and a stuck node pool, then broke an ingress and confused the HPA

   loveholidays2019

   Symptoms

   On the evening of a long-overdue upgrade of a loveholidays production GKE cluster from 1.10.X to 1.12.5-gke.10, planned to take 2 to 2.5 hours, the master upgrade and the first two 7-node NodePools went smoothly. After that the NodePool upgrades slowed to a crawl. Each node is cordoned, drained and upgraded in turn. Even a 14-node cluster at about 5 minutes per node took over an hour, and with about 100 more nodes to go, some of them taking over 15 minutes to drain, the sequential drains were too slow to finish at a reasonable hour.

   Upgrade stallPods PendingScale-up failureService outageAutoscaler misbehaviour

   Trigger

   A manual upgrade of the GKE masters and NodePools from 1.10.X to 1.12.5-gke.10, two versions at once, on 19 March 2019; GKE's release notes of 14 March had already said that version was no longer available for new clusters or master upgrades because masters showed elevated error rates, but it could still be selected.

   Root cause

   Cloud provider outage

   Component

   GKE control planeNode poolCluster autoscalerIngress controllerHorizontal pod autoscaler

   Contributing factor

   Unrepresentative stagingOverlapping failuresIgnored early signal

   Detection

   The slow drains, zombie nodes and stuck NodePool were seen by the engineer running the upgrade; the broken Ingress was noticed after the upgrade and explained by Google support; the HPA problem was noticed the next day.

   Remediation

   • drained the remaining NodePool nodes ahead of the upgrade with kubectl drain --ignore-daemonsets --delete-local-data
   • deleted the zombie instances from the managed instance group with gcloud compute instance-groups managed delete-instances
   • cancelled the stuck UPGRADE_NODES operation with gcloud beta container operations cancel
   • used kubectl port-forward in place of the broken internal Ingresses
   • scaled down the older of two active ReplicaSets, or triggered a dummy deployment, to bring the HPA back

   Action items

   • Alert when a HorizontalPodAutoscaler is at 70% and at 100% of its capacity
   • Alert when a deployment has had two active ReplicaSets for 30 minutes and for 60 minutes
   • Re-evaluate termination grace periods that were set to arbitrary large values
   • Read the GKE release notes before every cluster upgrade
   • Use auto-upgrade in non-production environments, and manual cluster upgrades with automatic node upgrades in production
   • Keep environments as identical as possible, including resource names

   Lessons

   Read the release notes before upgrading: the target version had been withdrawn five days earlier. Drain time depends on pod configuration, so emptyDir volumes, long grace periods and missing disruption budgets turn a NodePool upgrade into hours. Pre-production only catches problems like the ingress bug if it matches production down to resource names. Auto-upgrades in non-production surface problems early, and a mix of manual cluster upgrades and automatic node upgrades in production keeps clusters current without much effort.

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2. IL-0003 linkerd lost Kubernetes service discovery after an etcd reconfiguration, and restarting every linkerd instance turned failed payments into a full platform outage

   Monzo2017

   Symptoms

   At 14:10 an engineer deployed a change to a service that Monzo's current account needs to process payments, and every request to that service started to fail. Current account customers saw payment failures; the prepaid card was not affected at first because it does not use that service. The change was rolled back at 14:12, but the errors continued.

   High error rateStale endpoint routingService outage

   Trigger

   At 14:10 an engineer deployed a change to a service needed to process current account payments. Two weeks earlier the etcd cluster had been upgraded and grown from three to nine nodes, and one day earlier another team had scaled a new service down to zero replicas while leaving its Kubernetes service in place.

   Root cause

   Software defect

   Component

   etcdKubernetes API serverLinkerdkubelet

   Contributing factor

   Ineffective rollbackHarmful manual actionOverlapping failuresMonitoring blind spotSingle point of failure

   Detection

   Payment failures began right after the 14:10 deploy. The team rolled back at 14:12 and declared an outage internally at 14:16. At 15:13, when no service could serve requests, practically all automated alerts fired.

   Remediation

   • Rolled back the payments service change (the errors continued)
   • Activated internal backup processes so most customers could still use their card
   • Restarted all linkerd instances (this made the outage worse)
   • Restarted the three Kubernetes API server processes so replacement linkerd instances could start
   • Began deploying a newer linkerd version with the fix for empty services
   • Deleted the Kubernetes service that had no endpoints, which let linkerd load service discovery again

   Action items

   • Fix the bug in Kubernetes that can trigger timeouts after a cluster reconfiguration
   • Roll out a new version of linkerd that fixes the parsing error
   • Create better health checks, dashboards and alerts for the affected components so they give clearer signals about what is wrong and prevent human error
   • Improve procedures to communicate outages internally and externally as clearly and quickly as possible

   Lessons

   A large failure in a distributed system can be very hard to understand, and well-meant human action can compound it, as restarting every linkerd instance did here by exposing a second incompatibility. Because Monzo deploys often and its network changes constantly, the deployment and request-routing systems have to be trustworthy. Monzo committed to publishing a similar post-mortem for any incident of this severity.

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