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

Cases4 cases

1 to 4 of 4

  1. Symptoms

    From 01:36 UTC on 12 March 2026, GitHub.com returned elevated error rates for Git operations, web requests and related services. At 01:54 UTC the GitHub status page said it was investigating reports of impacted performance for some services.

    Trigger

    During a planned infrastructure upgrade, a configuration issue made newly provisioned Kubernetes nodes run an incompatible version of etcd.

    Root cause
    Component
    Contributing factor
    Detection

    The status page opened the incident at 01:54 UTC, 18 minutes after errors began, citing reports of impacted performance.

    Remediation
    • paused deployments for the duration of the incident
    • identified the newly provisioned nodes running the incompatible etcd version and removed them, which restored cluster consensus
    • ran a validation deploy that confirmed all systems were healthy before resuming normal operations
    Action items
    • Enforce version compatibility programmatically during node replacements
    • Add monitoring that detects split-brain conditions earlier
    • Update the recovery tooling to reduce restoration time
  2. Symptoms

    About two minutes after an engineer started the Kubernetes 1.23 to 1.24 upgrade of the cluster running Reddit's legacy stack, just after 19:00 UTC, the site stopped. The CDN edge request graph, which is kept separate from the cluster, showed traffic by status collapsing. Users saw the error page, a homepage with no posts, or plain errors.

    Trigger

    An in-place upgrade of the legacy cluster from Kubernetes 1.23 to 1.24; in 1.24 the node-role.kubernetes.io/master label is removed even from running clusters.

    Root cause
    Component
    Contributing factor
    Detection

    The site broke about two minutes into the upgrade; an incident was opened immediately and responders were on the call within three minutes, working from CDN edge graphs because the cluster's own metrics were gone.

    Remediation
    • deleted the Open Policy Agent webhook configurations to stop API server timeouts
    • terminated all worker nodes of the cluster
    • restored the control plane from the pre-upgrade backup onto the first control plane node
    • switched off the cluster autoscaler until the control plane was stable
    • generated new TLS certificates so replacement control plane nodes could join etcd
    • brought traffic back in steps from 1% to 100%
    • restarted legacy services that had been stopped by hand
    Action items
    • Codify cluster configuration so every choice has a record, and document in detail what cannot be codified
    • Standardise components across clusters and replace bespoke configurations
    • Build tooling to manage the lifecycle of whole clusters so they can be recreated or replicated
    • Add pre-production clusters that can be tested with confidence
    • Improve the backup restore process and make cluster upgrades safe
    Lessons

    Configuration that exists only in a live cluster, edited by hand through a special tool, can be forgotten, as the route reflector setup was, and then break on an upgrade nobody connects it to. A Kubernetes upgrade cannot be reverted without a restore, so the restore procedure has to be kept current and practised. Consistent, codified clusters are what make upgrades testable; bespoke clusters keep producing outages.

  3. 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.

    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
    Component
    Contributing factor
    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.

  4. Symptoms

    At 14:10 an engineer deployed a change to a service that Monzo's current account needs to process payments, and every request to that service started to fail. Current account customers saw payment failures; the prepaid card was not affected at first because it does not use that service. The change was rolled back at 14:12, but the errors continued.

    Trigger

    At 14:10 an engineer deployed a change to a service needed to process current account payments. Two weeks earlier the etcd cluster had been upgraded and grown from three to nine nodes, and one day earlier another team had scaled a new service down to zero replicas while leaving its Kubernetes service in place.

    Root cause
    Component
    Contributing factor
    Detection

    Payment failures began right after the 14:10 deploy. The team rolled back at 14:12 and declared an outage internally at 14:16. At 15:13, when no service could serve requests, practically all automated alerts fired.

    Remediation
    • Rolled back the payments service change (the errors continued)
    • Activated internal backup processes so most customers could still use their card
    • Restarted all linkerd instances (this made the outage worse)
    • Restarted the three Kubernetes API server processes so replacement linkerd instances could start
    • Began deploying a newer linkerd version with the fix for empty services
    • Deleted the Kubernetes service that had no endpoints, which let linkerd load service discovery again
    Action items
    • Fix the bug in Kubernetes that can trigger timeouts after a cluster reconfiguration
    • Roll out a new version of linkerd that fixes the parsing error
    • Create better health checks, dashboards and alerts for the affected components so they give clearer signals about what is wrong and prevent human error
    • Improve procedures to communicate outages internally and externally as clearly and quickly as possible
    Lessons

    A large failure in a distributed system can be very hard to understand, and well-meant human action can compound it, as restarting every linkerd instance did here by exposing a second incompatibility. Because Monzo deploys often and its network changes constantly, the deployment and request-routing systems have to be trustworthy. Monzo committed to publishing a similar post-mortem for any incident of this severity.

Check your cluster for this

These 4 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.

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