Cases14 cases

7 to 11 of 14

1. IL-0198 An automatic Ubuntu security update restarted systemd-networkd, which flushed the IP rules Cilium relied on and cut more than 60 percent of Datadog's Kubernetes nodes off the network across regions and cloud providers

   Datadog2023

   Symptoms

   Between 06:00 and 07:00 UTC on 8 March 2023, Kubernetes nodes in several Datadog regions lost network connectivity at the same time, on AWS, Google Cloud and Azure. All services across multiple regions were affected, including the regions that host Datadog's CI/CD and automation tools. Datadog's regions are not connected to each other and changes are rolled out one region at a time, so a simultaneous failure on several cloud providers looked implausible at first.

   Node NotReadyService outageThroughput degradation

   Trigger

   On 7 March 2023 Ubuntu published a systemd patch for a CVE (249.11-0ubuntu3.7). Ubuntu's default unattended upgrades installed it on the nodes between 06:00 and 07:00 UTC on 8 March, and installing it restarted systemd-networkd.

   Root cause

   Breaking change in an upgrade

   Component

   systemd-networkdCiliumNode operating system image

   Contributing factor

   Unreviewed defaultsChange with a delayed effectNo staged rolloutAutomation amplification

   Remediation

   • restarted thousands of disconnected instances on Google Cloud and Azure through the cloud APIs, keeping their local disks
   • rebuilt the data lost with terminated AWS instances' local disks through replication, reprocessing and restores from backup

   Lessons

   A change in a base operating system component can stay dormant for months until something restarts that component. Here the trigger was a security patch, and the change reached every region at once because automatic OS updates ran outside the progressive, region-by-region process used for every other change. Cloud providers react differently to an instance that loses its network. Google Cloud and Azure left the instances running, so a restart recovered them with their disks; AWS replaced them quickly, which brought stateless services back fast but destroyed the local-disk data the stateful services needed.

   View case
2. 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
3. IL-0191 A label selector accidentally added to the Loki distributor Service matched only the new pods of a rollout, which took all write traffic, were OOM-killed and stalled the rollout

   Grafana Labs2022

   Symptoms

   During a rollout of the Grafana Loki distributor Deployment in one Grafana Cloud Logs environment, the write path went down for about 25 minutes. The newly started distributor pods were OOM-killed over and over, never passed their health and readiness checks, and the rollout stopped making progress.

   Service outageOOMKilledLoad imbalanceProbe failures

   Trigger

   Step 1 of moving the Loki ring off a separately deployed key-value store onto embedded memberlist added a new label, gossip_ring_member: 'true', to the distributor pods and Service, together with a small config change, and the change required a rollout of the distributors.

   Root cause

   Configuration change

   Component

   Configuration templatingService discoveryContainer memory limit

   Contributing factor

   Unreviewed defaultsIgnored early signalUnrepresentative staging

   Detection

   The first clue was kubectl get pods and the kube_deployment_status_replicas_updated metric showing that only 16 of 140 distributor pods had been updated.

   Remediation

   • scaled the distributor Deployment out horizontally so the load spread over more pods with the new label and the rollout could continue
   • reverted the migration step to end the outage
   • set service_ignored_labels:: [$._config.gossip_member_label] and passed it to k.util.serviceFor so the label is no longer copied into the Service selector

   Action items

   • Update the function that generates a Service from a Deployment or StatefulSet to handle edge cases, including this one

   Lessons

   A Service whose selector is built by copying every label of a workload changes which pods it matches as soon as a new label is added. During a rollout it then matches only the new pods, which receive all the traffic before there are enough of them. A few errors during a rollout in other environments hid the problem, because those environments gave distributors more memory and could absorb the shift. Manifest diffs kept for every pull request made it possible to see that the Service selector had changed.

   View case
4. IL-0054 All ingress traffic lost while draining a GKE node pool because the load balancer only targeted new nodes without ingress-nginx pods

   DevOps Hof2019

   Symptoms

   While the old nodes of a GKE cluster were being drained to move workloads to a newly created node pool, none of the services in the cluster could be reached through ingress-nginx any more.

   Service outageProbe failures

   Trigger

   Cordoning and draining the old node pool removed those nodes from the GCP load balancer backend while the ingress-nginx pods were still running on them.

   Root cause

   Operator error

   Component

   Ingress controllerkube-proxyNode pool

   Contributing factor

   Unreviewed defaultsUnverified assumption

   Detection

   The team noticed during the drain that no service in the cluster was reachable through ingress-nginx.

   Remediation

   • deleted the nginx-ingress-controller pods still running on the old nodes so they were rescheduled on the new, ready nodes

   Lessons

   With externalTrafficPolicy: Local, the load balancer can only reach nodes that run an ingress pod, and cordoned nodes leave the load balancer backend immediately; if the ingress pods stay behind on cordoned nodes, all ingress traffic stops. Before any change that might touch traffic, look twice into the documentation.

   View case
5. IL-0059 Single-master Kubernetes control plane kept dying because the kubelet restarted a healthy etcd on a failing kubeadm liveness probe

   NRE Labs2018

   Symptoms

   The daily NRE Labs statistics showed lesson activity collapsing, and kubectl could not reach the cluster: `The connection to the server 1.2.3.4:6443 was refused - did you specify the right host or port?`

   Control plane unresponsiveProbe failuresService outage

   Trigger

   Unknown. The liveness probe that kubeadm writes into the etcd static pod manifest (an `etcdctl get foo` against 127.0.0.1:2379, failureThreshold 8, timeoutSeconds 15) started failing. The author first suspected GCP maintenance the night before, but could not reproduce the probe failure by hand and does not know why it began.

   Root cause

   unknown

   Component

   etcdkubeletKubernetes API server

   Contributing factor

   Single point of failureUnreviewed defaultsHarmful manual actionIgnored early signalMonitoring blind spot

   Detection

   The author saw lesson activity drop in the daily NRE Labs statistics during his morning routine.

   Remediation

   • removed the liveness probe section from the kubeadm-generated etcd static pod manifest and applied it between etcd restarts

   Action items

   • Add monitoring, especially for the single-node master
   • Run a basic "down for maintenance" page in Google Cloud Functions that points to Twitter for updates, to redirect to during outages

   Lessons

   Because all of the infrastructure is managed as code, the cluster could be rebuilt quickly, but destroying it before finding the cause also destroyed the evidence. Monitoring matters, especially with a single-node master. Read the restart counts in kubectl output, not just the Running status. Remember the fundamentals instead of expecting the issue to be more complicated than it is, and do not let the urgency of an outage push you into hasty decisions. Put up a maintenance page instead of leaving the site failing halfway.

   View case

By root cause8