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Cases2 cases

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  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

    On a Saturday at 5:12 pm, Blue Matador's own monitoring raised a SystemOOM event for one node in the production Kubernetes cluster. Four minutes later a second warning reported a low EBS Burst Balance on that node's root volume. CloudWatch data showed the burst balance had actually bottomed out at 5:02 pm, before the memory event; the warning arrived late because EBS metrics lag 10 to 15 minutes.

    Trigger

    Memory use of the fluentd-sumologic log shipper pods grew until the node ran out of memory; log volume in Sumo Logic had been steady, so a burst of logs was not the cause.

    Root cause
    Component
    Contributing factor
    Detection

    Blue Matador's own monitoring product alerted on the SystemOOM event, followed minutes later by a low EBS Burst Balance warning for the same node.

    Remediation
    • restarted all fluentd-sumologic pods so they started with low memory
    • set RUBY_GC_HEAP_OLDOBJECT_LIMIT_FACTOR to 0.9 on the fluentd-sumologic pods
    • added memory requests of 128Mi and limits of 1024Mi, and CPU requests of 100m and limits of 250m, to the fluentd-sumologic pods
    Action items
    • Apply default resource limits and resource quotas so that every pod runs with requests and limits
    Lessons

    When checking for restarted pods, look in every namespace, not only the application one. Set resource requests and limits on every pod, third-party ones in particular, so that one workload cannot exhaust a node. Investigate side signals such as the disk I/O spike while the logs still exist.

Check your cluster for this

These 2 cases involve Telemetry agent and CoreDNS. 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.

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