Cases52 cases

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1. IL-0001 Cluster-wide DNS outage after CoreDNS pods were OOM-killed again and again under a burst of DNS queries

   Zalando2019

   Symptoms

   Customers of the Zalando Fashion Store got a high rate of errors on all web product pages and outfit pages for more than an hour. The errors came from the main data aggregation layer service, which runs in one of Zalando's Kubernetes clusters.

   High error rateDNS resolution failuresOOMKilledMonitoring outage

   Trigger

   Calls from the aggregation layer to a single, not very important downstream service started timing out. The aggregation layer returned 404s for them, clients retried, and the resulting spike in requests became a spike in DNS queries to CoreDNS.

   Root cause

   Capacity exhaustion

   Component

   CoreDNSContainer memory limitClient-side DNS resolver and cache

   Contributing factor

   Unknown limitNo cachingRetry stormUnreviewed defaultsExcessive blast radiusMonitoring blind spot

   Detection

   The on-call engineer for the aggregation layer phoned the on-call Kubernetes engineer. Automatic paging did not happen because the cluster's monitoring and alerting ran inside the cluster and failed along with DNS. The Kubernetes engineer then saw that the CoreDNS pods were being OOM-killed.

   Remediation

   • Raised the CoreDNS memory requests and limits by hand from 100Mi to 2000Mi

   Action items

   • Introduce a more resilient DNS setup: CoreDNS fronted by dnsmasq on every node
   • Improve high-level alerting from outside the clusters, so that a cluster problem is known before or at the same time as applications are affected
   • Improve incident response processes and tooling so that any on-call engineer can escalate directly to other teams when automatic paging fails, for example through a chat bot

   Lessons

   The Kubernetes DNS setup was far from resilient enough: a single application could take down DNS for everything in the cluster. The blast radius of one application sending more DNS queries should be limited to one node at most, ideally to single pods. Known Kubernetes DNS problems, such as Linux kernel races in conntrack handling and the ndots 5 problem, were familiar to the team and partly mitigated, but their combined effect on the DNS infrastructure was worse than the team had understood. Monitoring that runs inside the cluster was not robust enough: when the cluster's DNS broke, it could not page anyone, and recovery took longer than it should have.

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2. IL-0031 Kubernetes API server OOM-killed, leaving the Skipper ingress without routes; the talk points to a misconfigured CronJob manifest

   Zalando2018

   Symptoms

   Customers were affected, and Zalando's IAM service answered requests with HTTP 404. The talk shows this on slides titled "Customer impact" and "IAM returning 404", followed by a slide on the number of pods in the cluster.

   High error rateControl plane unresponsiveOOMKilled

   Trigger

   A CronJob (apiVersion batch/v2alpha1, schedule "*/15 9-19 * * Mon-Fri") whose concurrencyPolicy: Forbid and job history limits sat inside the pod template spec instead of the CronJob spec. The talk shows it right after the slides on the number of pods and the API server being OOM-killed, and the lessons add a quota on the number of pods.

   Root cause

   Capacity exhaustion

   Component

   Kubernetes API serverIngress controller

   Contributing factor

   Single point of failureExcessive blast radius

   Remediation

   • fixed the CronJob manifest: moved concurrencyPolicy: Forbid and the job history limits to the CronJob spec, added activeDeadlineSeconds: 120 and changed the schedule to "7 8-18 * * Mon-Fri"

   Action items

   • Make the ingress stay healthy during API server problems
   • Make the ingress keep the last known set of routes
   • Use a ResourceQuota on the number of pods (the example sets pods: "1500")

   Lessons

   An AWS ALB routes traffic to all hosts when all hosts report unhealthy, so the ingress should stay healthy during API server problems. An ingress controller that reads routes from the API server should keep its last known set of routes. Use a quota for the number of pods.

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3. 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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4. 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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