Cases7 cases

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1. IL-0153 DOKS worker nodes went NotReady at 06:00 UTC on three days because a systemd timer in the Debian image ran apt upgrade and killed it mid kernel upgrade, breaking node networking

   DigitalOcean2023

   Symptoms

   Customers of DigitalOcean Managed Kubernetes (DOKS) saw worker nodes go NotReady between 06:00 and 07:00 UTC and stay unavailable, taking down the services on them, until the nodes were replaced or rebooted; some nodes needed several replacements or reboots. The first sporadic reports on October 8 said replacing the node fixed it. The same thing happened again around 06:00 UTC on October 9, more widely and across many regions, and again on October 10. Only clusters on versions 1.27.6-do.0 and 1.28.2-do.0 were affected.

   Node NotReadyService outage

   Trigger

   A systemd timer in the DigitalOcean Debian image started apt upgrade daily at 06:00 UTC, with a random delay of up to 60 minutes.

   Root cause

   Configuration change

   Component

   Node operating system imageLinux kernelkubelet

   Contributing factor

   Unreviewed defaultsLimited debug accessChange with a delayed effect

   Detection

   Sporadic customer reports of failed worker nodes arrived at 07:43 UTC on October 8; internal incident response started at 07:10 UTC on October 9 after broader impact across regions.

   Remediation

   • Advised customers to replace or reboot affected worker nodes
   • Arranged SSH and console access to worker nodes while they were healthy, and live-debugged an affected node on October 10
   • Released a DaemonSet to all affected clusters that disables the apt upgrade systemd timer on every worker node
   • Released new node images without the auto-update process

   Action items

   • Disable the timer during node provisioning, then remove the DaemonSet from all clusters
   • Add a check to the internal conformance test suite for new cluster versions that the auto-upgrade process and other unwanted timers stay disabled
   • Support logging into worker nodes even when normal access paths are broken

   Lessons

   An operating system auto-update timer left enabled in a node image can change the kernel and systemd underneath Kubernetes, and a timeout that kills the upgrade half-way can leave a node without networking. Failures that start at the same time every day point to a scheduled job on the nodes, and systemd timers belong on that list next to cron jobs. When the failure takes out a node's network, an investigation that depends on logging into the node stalls; access paths that work while the node is broken shorten diagnosis.

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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.

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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.

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4. IL-0189 A JVM service moved from EC2 to Kubernetes answered up to ten times slower because KIAM's 15-minute credentials made the AWS Java SDK fetch new credentials on every request

   Adevinta2019

   Symptoms

   After a Spring-based JVM microservice was deployed to Kubernetes and part of production traffic was routed to it, request latency there was up to 10 times higher than on EC2. Behind the NGINX ingress controller the backend took 100 to 200 ms to answer, where the EC2 instances took about 20 ms.

   High latency

   Trigger

   Moving the service onto the Kubernetes platform, where KIAM served IAM credentials to pods with its default 15-minute lifetime.

   Root cause

   Configuration change

   Component

   Credential broker for pods

   Contributing factor

   Unreviewed defaults

   Detection

   After part of production traffic was routed to the Kubernetes deployment, its request latency was seen to be up to 10 times higher than on EC2.

   Remediation

   • reconfigured KIAM to request IAM credentials with a longer expiration period

   Lessons

   KIAM's short credential lifetime for pods and the AWS Java SDK's eager refresh of any credential within 15 minutes of expiry are each reasonable, but together they force a metadata round trip on every request. When latency rises after a move to Kubernetes, the cause is often the interaction of components that never ran together before rather than Kubernetes itself. Here a packet capture from inside the container found what latency metrics and DNS tests had not.

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5. IL-0052 A cryptocurrency miner ran on every node of the development and staging clusters through a public, unauthenticated Weave Scope dashboard

   JW Player2019

   Symptoms

   Datadog alerted the DevOps team to a high normalised load average, first on the staging cluster (Day 0, 21:06 EST) and the next day on the development cluster (Day 1, 16:53 EST). The load was first put down to a legitimate service that kept scaling up and down in both environments, and because of the volume of identical alerts they were muted until things settled.

   Sustained high node CPUUnauthorised access or a foreign workload

   Trigger

   An automated crawler found the Weave Scope dashboard on a public load balancer that required no authentication. Weave Scope can open a shell in running containers, and its scope-agent containers ran privileged, as root and with the host's root filesystem mounted, so a command started there could run on the host.

   Root cause

   Configuration change

   Component

   Cluster dashboardCloud load balancer

   Contributing factor

   Ignored early signalUnreviewed defaultsExcessive blast radiusMonitoring blind spot

   Detection

   Datadog alerts on high normalised load average, muted at first as noise from a legitimate service; on Day 3 an engineer ran top on a node and found the gcc process at 100% CPU.

   Remediation

   • stopped Weave Scope and removed its deployment from all Kubernetes clusters
   • checked access logs for unauthorised access to the instances
   • confirmed the miner's outbound connections went only to a mining pool
   • isolated one affected node for later investigation
   • rotated out every node in each cluster so all affected hosts were destroyed and rebuilt

   Action items

   • Audit all Kubernetes and deployment YAML files and security groups for services that are unintentionally public or misconfigured
   • Replace load-average alerts with more meaningful monitors and tune them to signal a real anomaly
   • Research tools such as falcon or sysdig for behavioural monitoring and anomaly and intrusion detection
   • Evaluate Istio and Linkerd for observing and controlling end-to-end network traffic
   • Analyse the cost of scanning Docker images and containers for known vulnerabilities
   • Set aside time in architecture discussions to revisit older choices such as running containers as root
   • Share knowledge of large projects, such as Kubernetes version migrations, across the whole team

   Lessons

   Load average was not a useful signal for spotting a problem in the clusters, and muted noisy alerts nearly hid the miner. A load balancer that Kubernetes creates belongs to Kubernetes: a manual security group edit in the AWS console is reverted, so internal exposure must be declared in the Kubernetes YAML. A dashboard that can open shells, in front of privileged agents that mount the host's root filesystem, gives whoever reaches it root on every node.

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