Incident Library
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Cases3 cases

1 to 3 of 3

  1. Symptoms

    At 23:48 CET on 24 January 2024 the Scaleway Kubernetes API for the FR-PAR region ran out of memory. At the same minute Scaleway saw requests to its API Gateway spike.

    Trigger

    Simultaneous deployments in the FR-PAR region pushed the Scaleway Kubernetes API out of memory.

    Root cause
    Component
    Contributing factor
    Detection

    Increased load on the API Gateway was detected at 23:48, the minute the incident began, and the incident was escalated to on-call engineers at 00:00:10.

    Remediation
    • raised the memory limit and garbage collection thresholds of the Kubernetes managed services
    • deployed additional replicas of key services
    • purged the registry cache and monitored the clusters as they stabilised
    • adjusted service configurations after the incident to keep the platform stable
    Action items
    • Implement a local authentication cache
    • Further develop node authentication
    • Enhance monitoring, adjust rate limiting strategies and improve incident response protocols
    Lessons

    Because the Kubernetes API also handled node authentication, its memory exhaustion made some nodes NotReady, and the endless retries of those nodes added load on the API Gateway. Scaleway plans a local authentication cache and further work on node authentication.

  2. 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.

    Trigger

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

    Root cause
    Component
    Contributing factor
    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.

  3. 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.

    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
    Component
    Contributing factor
    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.

Check your cluster for this

These 3 cases involve Container memory limit 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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