Cases5 cases

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1. IL-0464 IONOS Managed Kubernetes control planes went unreachable for minutes at a time as their shared etcd grew and fragmented

   IONOS Cloud2026

   Symptoms

   From 14 to 16 March 2026 a subset of customer control planes on IONOS Managed Kubernetes (MK8s) became unavailable again and again, each time for several minutes. While a cluster was unreachable, operations that depend on the Kubernetes API, such as deployments, scaling and health checks, did not work reliably.

   Control plane unresponsiveImage pull failures

   Root cause

   Capacity exhaustion

   Component

   etcdKubernetes API serverManaged Kubernetes control plane and provider API

   Contributing factor

   Excessive blast radius

   Remediation

   • Defragmented the affected database instances, reclaiming about 3–4 GiB per instance
   • Shortened the database compaction intervals on the affected instances
   • Deployed a fix for the affected AI Model Hub database services
   • Applied final changes to all affected clusters

   Action items

   • Expand monitoring dashboards to show control plane health per database instance
   • Move the highest-volume clusters to dedicated database backends
   • Make incidents of this kind trigger immediate paging
   • Roll the updated compaction interval out to all shared control plane database instances
   • Run automated, scheduled defragmentation jobs on all instances
   • Rebalance clusters across database instances to reduce concentration
   • Contact customers whose clusters write disproportionate data, for example to store large security scan reports outside the control plane database
   • Introduce per-tenant resource quotas and key-count limits on the shared control plane database
   • Re-architect the shared control plane for stronger isolation, with dedicated database instances and better vertical scaling
   • Evaluate full database sharding for customers with consistently high data volumes
   • Hold regular drills on database resource exhaustion and recovery

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2. IL-0204 An etcd memory spike overloaded the control plane of a Render Frankfurt cluster, and DNS then failed because CoreDNS ran on the rebooted control plane nodes and could not start without the API server

   Render2024

   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.

   Control plane unresponsiveDeploys failingDNS resolution failuresHigh error rate

   Trigger

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

   Root cause

   Capacity exhaustion

   Component

   etcdCoreDNSKubernetes API server

   Contributing factor

   Unreviewed defaultsHarmful manual action

   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.

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3. IL-0194 After a kube-apiserver restart, pod LIST requests from every pod of a Vector DaemonSet nearly tripled etcd memory and restarted all master nodes

   Palark2023

   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.

   Control plane unresponsiveDatabase overload

   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

   Capacity exhaustion

   Component

   etcdKubernetes API serverTelemetry agent

   Contributing factor

   Unknown limitUnreviewed defaults

   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.

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4. IL-0076 Kubernetes masters went down after Dex filled etcd with AuthRequest objects and deleting its namespace started an endless list-and-timeout loop

   Fullstaq2019

   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.

   Control plane unresponsiveMonitoring outage

   Trigger

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

   Root cause

   Capacity exhaustion

   Component

   Kubernetes API serveretcdCluster authentication provider

   Contributing factor

   Unreviewed defaultsHarmful manual actionRetry stormLimited debug accessIgnored early signal

   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.

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5. IL-0075 Kubernetes API servers pegged on CPU when the cluster grew to about 290 nodes, traced to Datadog agents polling the API

   Civis Analytics2019

   Symptoms

   After Civis released its new script infrastructure on Kubernetes internally in September 2018, developers reported that kubectl commands were slow, and users intermittently could not start notebooks and services.

   Control plane lagControl plane unresponsiveHigh latencyHigh error rateDNS resolution failures

   Trigger

   Migrating clients' Python, R and container scripts from the in-house Bocce system to Kubernetes (the project called Croquet) pushed the cluster to about 290 EC2 instances under a large script load.

   Root cause

   Capacity exhaustion

   Component

   Kubernetes API serverTelemetry agentetcd

   Contributing factor

   Unknown limitUnverified assumptionMonitoring blind spotNo capacity planning

   Detection

   Developer reports of slow kubectl commands and user reports of notebooks and services failing to start, then high CPU on the master nodes.

   Remediation

   • moved internal users back to the old Bocce infrastructure
   • resized the three master nodes from m4.large to m4.4xlarge
   • changed the Datadog setup so per-node agents no longer polled the API server for service metadata
   • raised max-requests-inflight for non-mutating requests from 400 to 1200
   • grew the etcd EBS volumes from 20 to 100 GB (100 to 300 IOPS)
   • switched client scripts from the ClusterFirst DNS policy to Default

   Action items

   • Upgrade etcd from 2.2.1 to 3.x once Kops supports a safe migration
   • Solve the in-cluster DNS timeouts so client scripts can talk to other workloads in the cluster

   Lessons

   Kubernetes can reach thousands of nodes only after tuning, and third-party DaemonSets are a common cause of control plane load: an agent on every node that polls or watches the API server multiplies with the cluster size. Datadog, kube2iam and the fluentd metadata filter all showed this. A small configuration change often fixes it, but finding it took load testing and the API server access logs.

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