Cases17 cases

12 to 16 of 17

1. IL-0015 A GKE cluster's /16 pod address range ran out at 256 nodes, leaving new pods Pending and node scale-ups failing

   loveholidays2020

   Symptoms

   A colleague wrote in Slack that his application was taking a long time to deploy. A deployment that normally finishes in minutes had been running for about an hour: about half of the new pods were running and serving traffic, and the other half were Pending.

   Pods PendingIP address exhaustionScale-up failure

   Trigger

   The cluster reaching 256 nodes, the most its /16 pod secondary range could hold at 256 addresses per node; every further node creation failed.

   Root cause

   Capacity exhaustion

   Component

   VPC subnet or pod address rangeCluster autoscalerNode pool

   Contributing factor

   Unreviewed defaultsUnknown limit

   Detection

   A colleague reported in Slack that a deployment was slow; the pending pods' events and the cluster autoscaler status ConfigMap showed the exhausted IP space.

   Remediation

   • lowered the maximum pods per node on selected node pools, cutting IP consumption by about 30%
   • moved some node pools to larger instance types

   Action items

   • Lower the maximum pods per node on node pools that do not run many pods
   • Use larger instance types in some node pools

   Lessons

   In a VPC-native GKE cluster the number of nodes, not the number of pods, uses up the pod range: by default each node reserves 256 addresses, so even a /16 is full at 256 nodes. Maximum pods per node and node size are the practical levers; larger nodes pack better but take more pods down when they fail.

   View case
2. IL-0033 Uneven load across kube-dns pods and a DNS packets-per-second limit pushed service latency to 20 seconds

   Airbnb2019

   Symptoms

   On May 10 the latency graphs of several services showed a few spikes of up to about one second, then latency climbed to five seconds and then to 20 seconds, and it stayed there for a long time. The same pattern appeared on many services, not just one.

   High latencyIntermittent timeoutsLoad imbalanceDNS resolution failures

   Trigger

   Several services sent a high volume of external DNS queries, all of which went through kube-dns.

   Root cause

   Capacity exhaustion

   Component

   kube-dnskube-proxyClient-side DNS resolver and cache

   Contributing factor

   Unreviewed defaults

   Detection

   Latency graphs of several services showed the rise; engineers then looked at load per kube-dns pod.

   Lessons

   By default a pod discovers DNS through the kube-dns cluster IP and uses the ClusterFirst policy, so even external lookups go through kube-dns. If a pod does not need cluster DNS, set its dnsPolicy to Default or None. Check the DNS policy early and often. iptables picks backends at random and is not a load balancer, so pods behind a cluster IP, kube-dns included, can carry very different loads.

   View case
3. IL-0002 CI builder pods could not get AWS IAM credentials because kubelet fell minutes behind its API rate limit

   Zalando2019

   Symptoms

   Builds on Zalando's in-house Continuous Delivery Platform (CDP), which runs CI/CD on Kubernetes, timed out and failed for almost an hour on 11 June 2019. The Kubernetes builder pods could not get AWS IAM credentials.

   High error rateCredentials unavailableControl plane lag

   Trigger

   An unlucky rescaling of the CDP Kubernetes cluster left only one node available for builder pods. Builder pods were created and deleted on that node so quickly that kubelet fell behind.

   Root cause

   Capacity exhaustion

   Component

   kubeletCredential broker for podsKubernetes API serverCI system

   Contributing factor

   Unreviewed defaultsSingle point of failure

   Remediation

   • Scaled the CDP cluster up by hand so builder pods spread over more than one node

   Action items

   • Raise the kubelet QPS limit from the default 5 to 50 in the global cluster configuration

   View case
4. IL-0076 Kubernetes masters went down after Dex filled etcd with AuthRequest objects and deleting its namespace started an endless list-and-timeout loop

   Fullstaq2019

   Symptoms

   Dex, the OIDC proxy that handled Kubernetes authentication, stored its data in the Kubernetes API (storage type kubernetes, inCluster: true) and had built up a huge number of AuthRequest objects. Listing all AuthRequests timed out, and without the list they could not be deleted.

   Control plane unresponsiveMonitoring outage

   Trigger

   The dex namespace was deleted so that Kubernetes would clean up the accumulated AuthRequest objects itself.

   Root cause

   Capacity exhaustion

   Component

   Kubernetes API serveretcdCluster authentication provider

   Contributing factor

   Unreviewed defaultsHarmful manual actionRetry stormLimited debug accessIgnored early signal

   Detection

   The speaker says he had got hints of the problem earlier. While the masters were down, plenty of alerts arrived in Slack, but monitoring could not be reached because authentication and port-forwarding no longer worked.

   Remediation

   • removed the kubernetes finalizer from the dex namespace by calling the API directly (kill-kube-ns)
   • deployed Dex to a new namespace with sane defaults

   Lessons

   Dex with Kubernetes as its storage keeps every AuthRequest as an API object, and with a long TTL they pile up until the API cannot list them. Deleting a namespace that holds that many objects makes Kubernetes list them in a loop and can overload the masters. Monitoring that is reached through cluster authentication is lost when authentication is what broke.

   View case
5. 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.

   View case

By root cause1