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

Cases5 cases

1 to 5 of 5

  1. Symptoms

    The cluster could not be reached from outside. On the control plane node, sudo systemctl status kubelet showed TLS handshake errors such as "http: TLS handshake error from 101.198.0.183:19517: tls: client requested unsupported application protocols" and "http: TLS handshake error from 101.198.0.172:36328: tls: client offered only unsupported versions: [302 301]".

    Trigger

    The leaf certificates that kubeadm had generated for the cluster, valid for one year by default, expired at 2026-02-20 16:16 UTC.

    Root cause
    Component
    Contributing factor
    Detection

    The author could not connect to the cluster from outside and went to the control plane node to read the kubelet logs.

    Remediation
    • renewed all expired certificates with sudo kubeadm certs renew all
    • restarted containerd and the kubelet so the static control plane pods restarted with the new certificates
    • copied the renewed /etc/kubernetes/admin.conf to $HOME/.kube/config
    Lessons

    A kubeadm cluster stops working one year after its leaf certificates were issued unless they are renewed. The first errors seen may be TLS handshake failures or a flag error that does not mention certificates; the decisive message is the x509 expiry in the kube-apiserver log for its connection to etcd. The author recommends checking expiry with kubeadm certs check-expiration and renewing from 30 days before. kubeadm upgrade apply renews the certificates too, so a cluster upgraded at least once a year avoids the problem; a cluster run for a long time without upgrades can renew from cron, for example with 0 3 1 1 * root kubeadm certs renew all && systemctl restart kubelet in /etc/cron.d/kubeadm-cert-renew.

  2. 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.

    Trigger

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

    Root cause
    Component
    Contributing factor
    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.

  3. Symptoms

    One evening, right after an ordinary restart of kube-apiserver in a customer's production cluster, etcd memory consumption rose almost threefold. The sudden growth led to a cascading restart of all the master nodes.

    Trigger

    An ordinary restart of kube-apiserver, after which every pod of the log collector DaemonSet sent its list requests at the same time.

    Root cause
    Component
    Contributing factor
    Detection

    Memory graphs showed etcd memory on the master nodes almost tripling after a kube-apiserver restart; the audit logs then pointed to one DaemonSet's list requests.

    Remediation
    • created a PriorityLevelConfiguration named limit-list-custom that queues requests (assuredConcurrencyShares 5, 16 queues, handSize 4, queueLengthLimit 50)
    • created a FlowSchema that routes list and get requests on pods from the log collector's service account to that priority level
    Action items
    • Submit a pull request adding resource version support to the Kubernetes Rust library
    • Open a pull request to the Vector log collector to address the startup list requests
    • Apply the same flow-control approach to a similar problem found with the Cilium CNI
    Lessons

    A field selector reduces what kube-apiserver returns, not what it reads from etcd: listing the pods of one node still reads every pod in the cluster. A DaemonSet whose pods all list at startup multiplies that by the node count each time kube-apiserver restarts. Where exact freshness is not needed, resourceVersion=0 lets kube-apiserver answer from its cache; where the client cannot set it, API Priority and Fairness can queue the requests so they reach etcd gradually.

  4. 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.

  5. Symptoms

    The daily NRE Labs statistics showed lesson activity collapsing, and kubectl could not reach the cluster: `The connection to the server 1.2.3.4:6443 was refused - did you specify the right host or port?`

    Trigger

    Unknown. The liveness probe that kubeadm writes into the etcd static pod manifest (an `etcdctl get foo` against 127.0.0.1:2379, failureThreshold 8, timeoutSeconds 15) started failing. The author first suspected GCP maintenance the night before, but could not reproduce the probe failure by hand and does not know why it began.

    Root cause
    Component
    Contributing factor
    Detection

    The author saw lesson activity drop in the daily NRE Labs statistics during his morning routine.

    Remediation
    • removed the liveness probe section from the kubeadm-generated etcd static pod manifest and applied it between etcd restarts
    Action items
    • Add monitoring, especially for the single-node master
    • Run a basic "down for maintenance" page in Google Cloud Functions that points to Twitter for updates, to redirect to during outages
    Lessons

    Because all of the infrastructure is managed as code, the cluster could be rebuilt quickly, but destroying it before finding the cause also destroyed the evidence. Monitoring matters, especially with a single-node master. Read the restart counts in kubectl output, not just the Running status. Remember the fundamentals instead of expecting the issue to be more complicated than it is, and do not let the urgency of an outage push you into hasty decisions. Put up a maintenance page instead of leaving the site failing halfway.

Check your cluster for this

These 5 cases involve etcd and Kubernetes API server. 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