Cases71 cases

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1. 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.

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2. IL-0051 A third-party log shipping client leaked file descriptors with every new container until nodes failed with too many open files

   thredUP2018

   Symptoms

   While thredUP's move to Kubernetes seemed to be going well, Datadog showed the number of open files on the nodes climbing steadily, with no obvious reason.

   Service outageFile descriptor exhaustion

   Trigger

   Containers starting on a node, which in Kubernetes happens constantly with every deploy and every pod that moves between nodes.

   Root cause

   Software defect

   Component

   Telemetry agent

   Contributing factor

   Unverified assumption

   Detection

   Datadog showed the number of open files on the nodes rising.

   Remediation

   • killed the affected node, brought up a new one and redeployed

   Action items

   • Move away from the log aggregation vendor

   Lessons

   Libraries and agents that worked with the EC2 deployment lifecycle may not cope with Kubernetes, where containers start, stop and move between nodes constantly. Each one needs to be checked against the new lifecycle instead of being trusted because it worked before.

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3. IL-0055 A failing CronJob with the default concurrency policy piled up thousands of restarting pods and took down a cluster

   Target2018

   Symptoms

   A Kubernetes cluster went down after one CronJob kept failing and its pods piled up. Because each failed run kept restarting instead of being replaced by the next one, the pods accumulated into the thousands. The speaker's arithmetic for a job scheduled every minute that fails for three days is 4,320 restarting pods.

   Service outage

   Trigger

   A CronJob kept failing.

   Root cause

   Configuration change

   Component

   Jobs and CronJobsNode pool

   Contributing factor

   Unreviewed defaultsAutomation amplification

   Lessons

   When deploying a CronJob, set its concurrency policy to Replace or Forbid; with the default, failing runs accumulate and restart together. An application should handle a missing dependency with probes and bounded back-off rather than crash in a loop, which also keeps it from hammering a dependency that is already struggling.

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4. IL-0074 All AirMap platform services down as worker nodes went NotReady and pods crash-looped on network and DNS failures

   AirMap2018

   Symptoms

   At about 15:00 UTC on 19 July 2018, monitoring alerted on rising 5xx responses from several APIs, most notably pilot and tiles. Logins failed first, because the pilot service fetches the user's profile, and from there all services became unresponsive. Every affected API ran on the production Kubernetes cluster.

   High error rateNode NotReadyDNS resolution failuresContainer crash loopService outage

   Root cause

   Software defect

   Component

   kubelet

   Contributing factor

   Unpatched known bug

   Detection

   Monitoring alerted on an increase in 5xx responses from several APIs, most notably pilot and tiles.

   Remediation

   • restarted the kubelets on the stuck worker nodes, which did not last
   • restarted all worker nodes in a staggered order starting at about 18:00 UTC, which took about 1.5 hours

   Action items

   • Restart nodes on a rolling schedule to keep nodes and kubelets healthy until the fixes land upstream and reach the cloud provider, Microsoft Azure

   Lessons

   When nodes keep falling back to NotReady after kubelet restarts and pods fail on network and DNS errors, a known upstream bug may be the cause; matching the symptoms to the upstream issue tracker, with help from the community, found the cause and the fix candidates.

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5. IL-0072 High etcd write latency made the API servers return stale data, and the production cluster flipped between two views of its state

   Nordstrom2017

   Symptoms

   A user reported that pods were starting up and then vanishing. When the cluster operators looked, kubectl get pods and kubectl get nodes returned two different sets of data that alternated back and forth, as if there were two opinions of the cluster's state.

   Stale or inconsistent API readsStale endpoint routingService outage

   Trigger

   etcd write latency rose far above the healthy single-digit milliseconds; the speakers say trouble starts once the database sync time crosses double digits or several hundred milliseconds.

   Root cause

   Software defect

   Component

   etcdKubernetes API serverIngress controllerPersistent volumes and stateful sets

   Contributing factor

   Unreviewed defaults

   Detection

   A user reported pods starting up and vanishing.

   Remediation

   • restored service on a replacement cluster
   • freed persistent volumes from the old cluster one by one so they could bind in the new cluster
   • updated DNS records that pointed at the old cluster's load balancer names

   Action items

   • Make the Kubernetes API server request quorum reads from etcd

   Lessons

   etcd is extremely sensitive to write latency; once the database sync time crosses double digits of milliseconds, stale reads or badly degraded performance follow. Without quorum reads, a consistent store can still hand out stale data. Documentation for a fast-moving system changes, so read it again regularly. Moving workloads to a new cluster is hard when they hold persistent volumes or when DNS records point at generated load balancer names.

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