Cases6 cases

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1. IL-0112 The daily node rollover put DFDS's EKS nodes on an AMI later recalled for a kernel issue, causing "PLEG is not healthy" NodeNotReady flaps and pod network timeouts

   DFDS2022

   Symptoms

   On 2022-10-31 a planned upgrade of the vpc-cni EKS add-on, started from the deployment pipeline at 13:45 UTC, timed out at 14:10. Only about 10 of the 45 aws-node pods had upgraded, 5 were stuck in Terminating and the other 30 had not been attempted.

   Node NotReadyUpgrade stallIntermittent timeoutsIntermittent connection failures

   Trigger

   At 07:30 UTC on 2022-10-31 the daily node rollover replaced the existing nodes with nodes built from AMI v20221027, the latest AWS EKS node AMI, released on 2022-10-29 and later recalled because of a kernel issue.

   Root cause

   Software defect

   Component

   Node operating system imageLinux kernelkubeletAWS VPC CNINode launch templateTerraform

   Contributing factor

   No staged rolloutAutomation amplificationOverlapping failuresMonitoring blind spotNo health probes

   Detection

   The team noticed nodes flapping between NodeNotReady and NodeReady ("KubeletNotReady PLEG is not healthy") at 14:30 UTC while watching the stalled vpc-cni upgrade, about seven hours after the rollover. Time to detection was 7 hours. Alerting did not catch the NodeNotReady events or the socket growth.

   Remediation

   • cordoned, drained and deleted 15 stuck nodes one at a time to complete the vpc-cni upgrade
   • changed the Terraform infrastructure-modules so a specific AMI could be set
   • rolled the EC2 Auto Scaling group launch configuration back to the previous known good AMI through the pipeline

   Action items

   • Reach out to teams with suggestions about readiness and liveness probes
   • Create a dashboard for readiness and liveness probe coverage
   • Write a wiki article on readiness and liveness probes and their usefulness
   • Modify infrastructure-modules to allow specifying a particular AMI
   • Schedule a discussion on whether to take the latest AMI immediately and how to test new AMIs before they are deployed
   • Implement alerting on abnormal NodeNotReady events and on increased socket use
   • Create a learning path for Kubernetes within the team
   • Collect logs from nodes centrally
   • Create a Prometheus exporter that retrieves the latest available AMI, with a dashboard and alerts

   Lessons

   When a new node AMI has just been rolled out, upgrading other cluster components on the same day makes it hard to tell which change is causing trouble; here the vpc-cni upgrade on the same day confused matters. Taking the latest AMI automatically with no way to pin one meant a rollback first needed a Terraform change. The team also concluded that it needs better communication paths with application teams during incidents.

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2. IL-0146 New AKS clusters with Azure CNI in Central India lost tunnel connectivity because VMs began getting MAC addresses with a 06 prefix, which exposed a dormant bug in bridge-mode Azure CNI

   Microsoft Azure2020

   Symptoms

   In newly created AKS clusters using Azure CNI in Central India, kubectl exec and kubectl logs could time out, and pod-to-pod or pod-to-node traffic could time out. The cluster diagnostics page showed tunnel exec issues. Clusters using kubenet were not affected.

   Intermittent timeouts

   Trigger

   VMs in Central India started being assigned MAC addresses in a much higher range than before (06 prefix rather than the usual 00).

   Root cause

   Software defect

   Component

   Azure CNINode operating system image

   Contributing factor

   –

   Remediation

   • told owners of affected scale-set clusters to run a node image upgrade, or any Kubernetes upgrade such as a patch version, to get the Azure CNI that does not use a bridge
   • told owners of availability-set clusters to scale out and delete the VMs with a high-range MAC address in bridge mode
   • advised recreating affected clusters that were brand new

   Action items

   • Roll out a hotfix that makes transparent mode the default in all regions

   Lessons

   A change in how the platform assigns MAC addresses can wake a long-dormant bug in the network plugin. Knowing which CNI mode the nodes run (bridge or transparent) and keeping node images current decides whether such a bug reaches you.

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3. IL-0029 Slow user-facing services from CPU throttling on containers that used far less CPU than their limit

   Buffer2020

   Symptoms

   Services on Buffer's kops-managed cluster on AWS (about 60 nodes and 1500 containers) answered more slowly than they should have. The container throttling metric showed that many containers were being throttled whatever their CPU usage was, including containers that never came close to their CPU limit.

   CPU throttlingHigh latencyNode NotReady

   Trigger

   CPU limits on user-facing services, enforced through CFS quota by a Linux kernel with a bug that throttled containers even when they were well under their limit.

   Root cause

   Software defect

   Component

   Container CPU limitLinux kernelNode operating system image

   Contributing factor

   Unpatched known bugUnverified assumption

   Detection

   While reviewing the container throttling metric, the team noticed many containers being throttled even though their CPU usage stayed far below their limits.

   Remediation

   • removed CPU limits from all services directly or indirectly on the users' critical path
   • moved those services to dedicated tainted nodes and gave them matching tolerations
   • set each service's CPU request to its peak usage over a few months plus a margin of more than 20%, and set memory requests the same way

   Action items

   • Move nodes to a kernel that contains the CFS throttling fix (4.19 or later), which for Buffer means a kops version whose host image is Ubuntu 20.04
   • After the kernel upgrade, check whether throttling is fully gone and update the post

   Lessons

   A CPU limit can slow a service down even when the service uses a small part of it, because of how the kernel enforces CFS quota on older kernels; the throttling metric shows it, the CPU usage graph does not. Upgrading the kernel is the safer fix. Removing limits works for latency, but only together with honest CPU and memory requests, isolation of the unbounded services, and monitoring of node usage, since unbounded containers can starve the kubelet.

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4. IL-0143 GKE nodes upgraded to certain 1.13 and 1.14 versions had an elevated number of kernel panics, fixed by releases that downgraded the Container-Optimized OS image

   Google Cloud2019

   Symptoms

   Some nodes in Google Kubernetes Engine clusters that had recently been upgraded showed an elevated number of kernel panics. The status page described it as kernel panics following an upgrade in GKE version.

   Node kernel panic

   Trigger

   Upgrading GKE node pools to one of the affected 1.13 or 1.14 versions.

   Root cause

   Software defect

   Component

   Node operating system imageLinux kernel

   Contributing factor

   –

   Remediation

   • advised affected users to downgrade to a patch release not on the affected list, with support helping Release Channel users
   • released GKE 1.13.11-gke.14, 1.13.12-gke.8, 1.14.7-gke.23 and 1.14.8-gke.12, which downgraded Container-Optimized OS to cos-73-11647-293-0
   • rolled the fixed versions out to node pools with auto-upgrade enabled; clusters on manual upgrades had to upgrade their nodes themselves

   Action items

   • Ship a GKE release with an upgraded kernel that fixes the panics

   Lessons

   Downgrading the node operating system image was used as a temporary mitigation until a kernel fix was available.

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