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

Cases11 cases

4 to 8 of 11

  1. Symptoms

    From 10:15 am PT on 25 November 2024 a large share of both API and ChatGPT traffic failed with timeouts and 503 errors.

    Trigger

    A global change to Kubernetes namespace labels caused the networking layer to recompute metadata. The change had rolled out to the small clusters without problems.

    Root cause
    Component
    Contributing factor
    Remediation
    • moved workloads out of the impacted clusters by hand
    • with the cloud provider, scaled up the number of control plane nodes while scaling down the number of data plane nodes, which let the control planes recover
    Action items
    • Lock namespace changes so this incident cannot recur
    • Freeze certain types of infrastructure deploys
    • Allowlist identities to prevent a recurrence of this class of incidents
    • Improve the GPU load balancing logic so traffic is re-routed automatically and more effectively when possible
    • Improve change management for fleet-wide infrastructure changes
  2. Symptoms

    At 13:02 UTC on 2024-01-23 DigitalOcean posted that, as of 12:18 UTC, its engineers were investigating an issue with Kubernetes clusters in the FRA1 region and that users might see errors when communicating with their clusters. The control planes of the affected DOKS (DigitalOcean Kubernetes) clusters had become inaccessible.

    Trigger

    An incorrect configuration was applied to an internal infrastructure cluster in FRA1 at 12:21 UTC during a maintenance operation.

    Root cause
    Component
    Contributing factor
    Detection

    Engineers were investigating errors with Kubernetes clusters in FRA1 as of 12:18 UTC and identified the incorrect configuration as the cause at 12:36.

    Remediation
    • restored each affected cluster's etcd from its latest twice-daily backup
    • restored the stateless control plane components after etcd
    • patched the recovery mechanism after unexpected problems during recovery
    • found and fixed an additional small bug during recovery
    • contacted affected customers directly with further instructions, since some might need to reconfigure Kubernetes resources
    Action items
    • Prevent automatic deletion of infrastructure cluster resources under any circumstances in the production environment
    Lessons

    When managed control planes run as resources in another cluster, one configuration mistake in that cluster can delete hundreds of control planes at once through ordinary automation. The etcd backups limited the damage, but their twice-daily schedule set the worst case at 12 hours of lost control plane state, and the recovery tooling itself needed patching during the incident.

  3. Symptoms

    At 10:23 on 6 June 2023 a user of the Cloud Platform reported that all of their production pods had been deleted at the same moment. Several users received Pingdom alerts that their applications were down for a few minutes.

    Trigger

    The team changed the instance type of the cluster's worker nodes through Terraform.

    Root cause
    Component
    Contributing factor
    Detection

    Users reported that their production pods had been deleted at once and that Pingdom alerts showed their applications down; the incident was declared at 11:00.

    Action items
    • Ask AWS, through a support ticket, for the steps to change the node instance type without an outage
    • Plan how to make instance type changes through Terraform without downtime and add a runbook with the steps for changing the node instance type
  4. Symptoms

    The graph of WebSocket connections to messaging-hub, the messaging platform used by the Japanese food delivery service Demaecan, showed sudden deep drops even outside peak traffic. The drops kept coming back at irregular intervals. Messages still reached clients, because messaging-hub switches to Firebase Cloud Messaging when a WebSocket is gone.

    Trigger

    Another service that shared the same L7 load balancer deployed its own load balancer configuration in the Verda dashboard, which reloaded HAProxy; 30 minutes later, at the hard-stop-after limit, the old HAProxy process exited and closed every WebSocket connection it still held.

    Root cause
    Component
    Contributing factor
    Detection

    The developer noticed deep, sudden drops in the WebSocket connection graph that were not tied to peak traffic and kept recurring irregularly. The Nginx packet drops were found through network monitoring.

    Remediation
    • separated the Merchant system's token issuance API into its own deployment so reconnect traffic did not delay other Merchant APIs
    • scaled out Nginx with pod anti-affinity and a label selector so each pod ran on a different node, which stopped the nf_conntrack packet drops
    • raised Ingress Nginx proxy-read-timeout and proxy-send-timeout and the load balancer timeout to 3600s, which did not stop the drops
    • moved messaging-hub from the shared L7 load balancer to an L4 load balancer, which ended the WebSocket drops
    Lessons

    A reload of a shared load balancer by a different team can cut long-lived connections, and with hard-stop-after the cut comes 30 minutes later, far from the change that caused it. The author's lesson is not to narrow the scope of the search too early: trusting that the infrastructure was fine kept the investigation inside the team's own systems for days. A reconnect wave from many WebSocket clients can overload the systems that issue connection tokens and fill nf_conntrack on proxy nodes. Scaling Nginx out only helps for conntrack if the pods land on different nodes, and anti-affinity leaves extra replicas Pending once they outnumber the nodes. That messaging-hub problems can still load the connected systems remains an open problem.

  5. Symptoms

    On 25 August 2021, skyscanner.net was unavailable and the Skyscanner mobile apps could not work, for travellers and business partners everywhere at the same time. The full global outage lasted four and a half hours.

    Trigger

    A peer-reviewed change to a rarely changed root-level file of the cells templating configuration, intended as a no-op, that left out the {{ }} delimiters; it was submitted around 15:30 GMT, merged to master and rolled out automatically to every region at once.

    Root cause
    Component
    Contributing factor
    Remediation
    • restored the correct configuration for each cluster and let Argo CD reconcile the cluster back to it
    • restored services through the backup and restoration process
    • brought one region back first with the critical services and served all traffic from it from around 20:30 GMT
    • restored and verified the remaining regions and non-critical services over Thursday and Friday
    Action items
    • Avoid global configuration deploys, including rare change paths like this one
    • Treat templated configuration as code and add testing and linting
    • Plan and wargame more drastic failure scenarios in runbooks
    • Verify backup and restore processes, including access to the backups and the loss of a region
    • Refactor runbooks so they are clear and, where appropriate, idempotent for a stressed engineer in the early morning
    • Reconsider how much configuration is templated across regions, weighing configuration drift against automated global rollout
    Lessons

    Global configuration changes had been prevented in many cases, but not in this rarely used path. Configuration that gains templating and logic has become code and needs tests and at least linting. The failure scenarios and runbooks were not pessimistic enough, a backup only counts once it has been restored, and runbooks need care so they work for a stressed engineer at night. Automation that templates configuration across regions trades drift for the risk of rolling one mistake out everywhere. An experienced incident commander who kept the response calm and blameless made a large difference.

Check your cluster for this

These 11 cases involve Cloud load balancer 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 cause1

Configuration change11 cases

  1. IL-0179 With DEBUG logging and synchronous log output, a high-traffic service filled the 64 KB stdout pipe, so request threads blocked in write() while holding database connections and HikariCP ran dry, failing requests in 30-second bursts
  2. IL-0122 An invalid value in a configuration shared by several ChatGPT services put pods into crash loops and raised error rates
    OpenAI2025
  3. IL-0192 A Crossplane composition merge-policy change for a TLS policy update switched Kubernetes Services from LoadBalancer to ClusterIP and deleted the load balancers behind about 25% of Grafana Cloud services
  4. IL-0118 A global change to Kubernetes namespace labels made the networking layer recompute metadata and overwhelmed the control planes of three of OpenAI's largest GPU clusters
    OpenAI2024
  5. IL-0152 An incorrect configuration applied during maintenance made an internal infrastructure cluster automatically delete the control planes of 200 DOKS clusters in FRA1
  6. IL-0091 Changing the worker node instance type through Terraform recycled all nodes at once and deleted users' production pods together
  7. IL-0177 WebSocket connections to LINE's messaging-hub on Kubernetes dropped all at once whenever another service's change reloaded a shared HAProxy L7 load balancer, and the reconnect wave overloaded a token API and filled nf_conntrack on Nginx
    LINE+2022
  8. IL-0010 A templating change that dropped its {{ }} delimiters made Argo CD delete all 478 Skyscanner services in every region
  9. IL-0008 An unresponsive OPA validating webhook crash-looped the API server during a GKE master upgrade, and node auto-repair then recreated every node
  10. IL-0052 A cryptocurrency miner ran on every node of the development and staging clusters through a public, unauthenticated Weave Scope dashboard
  11. IL-0035 Worker nodes went NotReady after a new ElastAlert rule without memory limits used up node memory
    NU.nl2019