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

Cases2 cases

1 to 2 of 2

  1. 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.

  2. Symptoms

    After a Spring-based JVM microservice was deployed to Kubernetes and part of production traffic was routed to it, request latency there was up to 10 times higher than on EC2. Behind the NGINX ingress controller the backend took 100 to 200 ms to answer, where the EC2 instances took about 20 ms.

    Trigger

    Moving the service onto the Kubernetes platform, where KIAM served IAM credentials to pods with its default 15-minute lifetime.

    Root cause
    Component
    Contributing factor
    Detection

    After part of production traffic was routed to the Kubernetes deployment, its request latency was seen to be up to 10 times higher than on EC2.

    Remediation
    • reconfigured KIAM to request IAM credentials with a longer expiration period
    Lessons

    KIAM's short credential lifetime for pods and the AWS Java SDK's eager refresh of any credential within 15 minutes of expiry are each reasonable, but together they force a metadata round trip on every request. When latency rises after a move to Kubernetes, the cause is often the interaction of components that never ran together before rather than Kubernetes itself. Here a packet capture from inside the container found what latency metrics and DNS tests had not.

Check your cluster for this

These 2 cases involve CoreDNS and Credential broker for pods. 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 cause2