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

Cases2 cases

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  1. Symptoms

    A tech support engineer called Palark to say that a customer's cluster, production environment included, had practically stopped working. On the control plane nodes the kube-apiserver processes had used up all the memory and were crashing and restarting over and over, so the Kubernetes API was unreachable and completely non-functional.

    Trigger

    Cilium agent pods on more than 200 nodes sent LIST requests to the Kubernetes API en masse at the same time.

    Root cause
    Component
    Contributing factor
    Detection

    A tech support engineer phoned the team to report that the customer's cluster was practically non-operational.

    Remediation
    • added CPU and memory to the control plane nodes in two steps, from 8 CPUs and 16 GB of RAM to 16 CPUs and 64 GB, until the API stabilised
    • restarted the Cilium agents in a test window agreed with the customer to reproduce the memory growth
    • deployed a FlowSchema and a PriorityLevelConfiguration named cilium-pods that limit and queue LIST requests from the Cilium service accounts to cilium.io resources
    • reduced the control plane nodes back to their original resources
    Action items
    • Make an API Priority and Fairness configuration a standard part of Palark's Kubernetes platform
    Lessons

    In a large cluster, many agents sending LIST requests at once can exhaust kube-apiserver memory, and with several API servers the crash moves from one to the next. APF can hold back such a client: a FlowSchema matches its requests and a PriorityLevelConfiguration gives them a small concurrency share and a queue, so the requests run more slowly instead of all at once. With APF enabled, the total concurrency it divides is the sum of --max-requests-inflight (default 400) and --max-mutating-requests-inflight (default 200), shared among priority levels in proportion to their assured concurrency shares, so raising one level's share lowers every other level's limit. Long-running requests such as logs and exec, and WATCH requests, are not subject to APF. The response headers X-Kubernetes-PF-FlowSchema-UID and X-Kubernetes-PF-PriorityLevel-UID show where a request landed, and the metrics Apiserver_flowcontrol_rejected_requests_total, Apiserver_current_inqueue_requests and Apiserver_flowcontrol_request_execution_seconds, with the debug endpoints /debug/api_priority_and_fairness/dump_priority_levels and /debug/api_priority_and_fairness/dump_queues, show how the queues behave.

  2. 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.

Check your cluster for this

These 2 cases involve Kubernetes API server and Cilium. 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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