Incident Library
  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases9 cases

1 to 5 of 9

  1. Symptoms

    Services on the production Amazon EKS cluster behind the idus marketplace threw intermittent errors whose cause was hard to pin down. Calls to external services such as RDS and Redis failed now and then, and whenever DNS traffic spiked, domain lookups answered slowly or failed outright.

    Trigger

    All CoreDNS pods were scheduled onto the same node, and that node's memory usage spiked until it ran out of memory.

    Root cause
    Component
    Contributing factor
    Detection

    The write-up does not say how the full outage was noticed. The earlier DNS trouble showed up as intermittent service errors, and investigating failed calls to RDS and Redis led to DNS resolution failures.

    Remediation
    • deployed NodeLocal DNSCache as a DaemonSet in front of CoreDNS
    • added a PodDisruptionBudget (maxUnavailable 1) and topologySpreadConstraints across zones for CoreDNS
    • lowered ndots from 5 to 2 with dnsConfig in the Deployments
    Lessons

    The CoreDNS setup that EKS creates by default (two pods) can be enough for a small or development cluster but becomes a bottleneck in a large production cluster, and DNS is a single point of failure that needs high availability and room to scale. Tuning the CoreDNS cache and buffer size only relieved the symptoms; the real load came from the extra queries that ndots:5 generates for external names. A CoreDNS pod without a memory limit can share a node's fate with everything else on it.

  2. Symptoms

    Request latency from the Temporal Server History service, the service that starts workflow executions and records their progress, was higher and less steady than it should be on a self-hosted Kubernetes deployment. The CPU dashboard showed the history pods using less than 60 percent of their CPU, yet the same pods were being throttled.

    Trigger

    Normal load on History pods that had a CPU limit of 2 cores on 8-core nodes, with the Go runtime's GOMAXPROCS left at its default of one per node core.

    Root cause
    Component
    Contributing factor
    Detection

    A Prometheus query for CPU throttling showed the history pods throttled although their CPU usage read under 60 percent.

    Remediation
    • set the GOMAXPROCS environment variable to 2 to match the 2-core CPU limit
    Action items
    • Set GOMAXPROCS automatically from the Kubernetes CPU limit, from Temporal release 1.21.0
    Lessons

    A CPU usage graph averaged over 15 seconds or more can sit far below 100 percent while a container is being throttled, so throttling needs its own metric. A Go program in a container should have GOMAXPROCS matched to its CPU limit, or to its CPU request when it has no limit. The author recommends not using CPU limits at all.

  3. Symptoms

    On a Friday afternoon a tenant of SCHIP, Adevinta's multi-tenant Kubernetes runtime, reported a spike of HTTP 5xx errors in some of its services. The drops in quality of service came back periodically through the following days, each one short, and were reported mostly around midnight.

    Root cause
    Component
    Contributing factor
    Detection

    A tenant reported a spike of HTTP 5xx errors in some of its services; the DNS Latency SLI had already been degraded for some time without being acted on.

    Remediation
    • raised the dnsmasq concurrent query limit from 150 to 1500
    • added a CoreDNS header block that sets the ra and aa flags and clears rd, so dnsmasq caches cluster.local answers
    • configured dnsmasq on each node to answer NXDOMAIN for unresolvable search-domain names instead of forwarding them to CoreDNS
    • changed the fluent-bit log router hostname to a fully qualified name
    • asked the affected tenants to use fully qualified names for internal calls
    Lessons

    The DNS Latency SLI had shown the problem long before anyone looked at it. An SLO only protects you when its SLIs are trusted and a drop is investigated. The investigation took a month partly because several on-call groups worked on it separately, without one place for observations and hypotheses, and sometimes chased hypotheses already discarded. Disprove one hypothesis before starting the next, and collect data the metrics system lacks: DNStop showed the garbage lookups that no dashboard did. With ndots:5, short service names multiply DNS traffic; a node-local cache only helps if it can cache the cluster DNS answers at all.

  4. Symptoms

    On the Saturday the production cluster was moved from kops to EKS, the platform became very slow and too unstable to keep running, and the team reverted.

    Trigger

    Production was moved from a kops cluster using Weave networking to a new EKS cluster using the AWS VPC CNI, without external SNAT enabled.

    Root cause
    Component
    Contributing factor
    Detection

    The team lead saw the platform behaving very slowly after the switch to EKS and phoned the author.

    Remediation
    • reverted production to the kops cluster
    • set AWS_VPC_K8S_CNI_EXTERNALSNAT=true in the AWS VPC CNI
    Action items
    • Monitor and alert on the AWS VPC CNI
    Lessons

    In a networking problem every component in the stack is a suspect; ruling out EKS early cost a lot of time. A DaemonSet that pinged every component from every other one exposed the anomaly that led to the fix. The team had only skimmed the AWS CNI documentation before the migration; knowing how the plugin works internally would have led to better judgements and hypotheses while debugging.

  5. 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.

    Trigger

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

    Root cause
    Component
    Contributing factor
    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.

Check your cluster for this

These 9 cases involve Client-side DNS resolver and cache and conntrack table. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause3

Capacity exhaustion3 cases

  1. IL-0027 All CoreDNS pods landed on one node, the node ran out of memory, and DNS for the whole service went down
  2. IL-0028 Temporal History service latency rose because its pods were CPU-throttled while CPU usage read below 60 percent
  3. IL-0033 Uneven load across kube-dns pods and a DNS packets-per-second limit pushed service latency to 20 seconds
    Airbnb2019

DNS or network fault4 cases

  1. IL-0083 Intermittent 5xx errors in a multi-tenant Kubernetes cluster came from internal DNS: the node-local dnsmasq hit its 150 concurrent query limit, did not cache cluster.local answers, and ndots search lookups flooded CoreDNS
  2. IL-0056 Calls from EKS pods to services behind an NLB in another VPC failed intermittently because the AWS VPC CNI did source NAT on the node
  3. IL-0057 Higher p99 latency after moving a reverse proxy to EKS, from outgoing connections delayed by a SNAT conntrack race
    Prezi2019
  4. IL-0047 Pod-to-pod requests delayed by 5, 10 or 15 seconds because of DNS lookups lost to a conntrack race

Configuration change2 cases

Organisation
  1. 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
  2. IL-0035 Worker nodes went NotReady after a new ElastAlert rule without memory limits used up node memory
    NU.nl2019