Cases8 cases

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1. IL-0204 An etcd memory spike overloaded the control plane of a Render Frankfurt cluster, and DNS then failed because CoreDNS ran on the rebooted control plane nodes and could not start without the API server

   Render2024

   Symptoms

   In January 2022 an etcd memory spike overloaded the Kubernetes control plane of one of Render's clusters in Frankfurt. At first only operations that need the control plane failed: new deploys and cron job runs.

   Control plane unresponsiveDeploys failingDNS resolution failuresHigh error rate

   Trigger

   A memory spike in etcd overloaded the cluster's control plane.

   Root cause

   Capacity exhaustion

   Component

   etcdCoreDNSKubernetes API server

   Contributing factor

   Unreviewed defaultsHarmful manual action

   Action items

   • Run CoreDNS on data plane nodes instead of control plane nodes
   • Run etcd on dedicated nodes

   Lessons

   CoreDNS can keep answering from its in-memory cache while the API server is down, but it cannot initialise without it. With CoreDNS on the control plane nodes, a reboot or restart during a control plane outage turned a failure of deploys and cron jobs into a failure of requests to services that were already running. The core problem was that the data plane was not isolated enough from the control plane: even without the reboot, the etcd memory spike alone could have forced CoreDNS to restart.

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2. IL-0182 Too few CoreDNS replicas on EKS were overloaded during traffic spikes, raising latency and cutting the network for task pods, and the over-provisioned, tightly spread CoreDNS pods added later blocked Karpenter consolidation

   이언철2024

   Symptoms

   When traffic changed sharply, CoreDNS came under heavy load, and the cluster saw network problems and a sudden rise in latency. The horizontal pod autoscaler then added pods, database connections surged, and the impact spread to the whole service.

   High latencyIntermittent connection failuresAutoscaler misbehaviour

   Trigger

   Sharp changes in traffic loaded the small number of CoreDNS pods beyond what they could handle.

   Root cause

   Capacity exhaustion

   Component

   CoreDNSKarpenterHorizontal pod autoscalerPod scheduling and placement

   Contributing factor

   Automation amplificationHarmful manual action

   Remediation

   • Set up the Cluster Proportional Autoscaler for CoreDNS with nodesPerReplica and coresPerReplica chosen for the instance types in use
   • Spread CoreDNS with soft topologySpreadConstraints (ScheduleAnyway) instead of anti-affinity so Karpenter could consolidate nodes
   • Added alert thresholds on CoreDNS error rate, panics, request duration and request rate
   • Deployed NodeLocal DNSCache so each node answers DNS from a local cache and forwards misses to the main CoreDNS

   Lessons

   A fixed, small number of CoreDNS pods cannot follow a cluster whose nodes and pods change quickly with traffic, and the damage spreads: DNS latency triggers autoscaling, which in turn floods the database with connections. Simply adding many CoreDNS replicas created a different problem, because with tainted nodes and a maxSkew: 1 spread constraint the pods piled onto a few nodes and blocked Karpenter consolidation. Scaling CoreDNS in proportion to the cluster and putting a DNS cache on every node handled both.

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3. 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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