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

Cases4 cases

1 to 4 of 4

  1. Symptoms

    Between 14:20 and 15:16 UTC on 27 August 2024, some HubSpot customers could not log in to their accounts, reach their content or use HubSpot tools. Requests were slow or failed because HubSpot's internal load balancers, which run on Kubernetes and spread traffic across the backend services, were overloaded.

    Trigger

    Routine operation of a critical component of HubSpot's traffic management system, from about 14:08 UTC, ran path handling updates in the load balancer stack, and an issue in that stack made those updates block health check responses.

    Root cause
    Component
    Contributing factor
    Detection

    Monitoring detected widespread performance degradation across the platform at 14:23 UTC and the incident response team was mobilised. HubSpot says it had identified the issue internally by 14:20 UTC. The status page was not updated until 14:44 UTC, which left customers with outdated information.

    Remediation
    • Tried to increase the capacity of the remaining load balancer instances
    • Brought new load balancer instances online, which relieved the pressure and let traffic return to normal
    Action items
    • Change the health check configuration so health checks do not time out falsely
    • Redesign the health check system so health checks get priority and keep running during operations such as configuration updates
    • Increase the capacity of the load balancers for sudden traffic spikes
    • Change the load balancing architecture to detect traffic surges earlier and distribute load dynamically in real time
    • Update the status page automatically for large-scale outages
    • Integrate the monitoring systems more tightly with the communication tools
    • Expand load testing to simulate high-traffic scenarios
    • Introduce chaos engineering to test platform resilience regularly
    • Add traffic pattern metrics, including the ratio of current connections to the maximum allowed
    • Add auto-scaling that adjusts resource capacity to traffic patterns
    Lessons

    HubSpot concluded that earlier detection of the abnormal traffic surge could have prevented the cascading failure, and that health checks have to keep running during operations such as configuration updates so that working load balancers are not removed together. The late status page update caused confusion for customers.

  2. Symptoms

    At 08:00 UTC on 2021-09-06 every service in DFDS's Kubernetes cluster answered with 404. Investigation started five minutes later.

    Trigger

    The automated Kubernetes node rollover on 2021-09-06 restarted all the Traefik v2 pods, five days after a malformed IngressRoute manifest had been applied.

    Root cause
    Component
    Contributing factor
    Detection

    All services returned 404 from 08:00 UTC and root cause investigation started at 08:05. Time to detection was 5 minutes.

    Remediation
    • changed the ALB health check path, which made the targets healthy but did not stop the 404s
    • rolled back by hand to Traefik v1 as the main ingress controller
    • deleted the malformed IngressRoute by hand and confirmed the Traefik v2 bug
    • applied the changes upstream
    Action items
    • Upgrade Traefik to v2.5, where the bug is fixed, and verify that it removes the bug
    • Change the Traefik v2 health check path to something more robust
    • Set up an external liveness probe on the ingress controller
    • Consider workload segmentation to limit the blast zone
    • Look into monitoring the Traefik v2 API for rapid changes
    • Look into smoke testing during and after node rollover
    Lessons

    A malformed IngressRoute did nothing visible for five days and then took down all ingress when every Traefik v2 pod had restarted during a node rollover. Because Traefik v2 failed gracefully, the first signals pointed at the ALB health checks instead of at Traefik. On incident handling, the team concluded that appointing an incident manager could have helped, that the war room meeting should be recorded and a log book kept, that people not involved should only make suggestions in writing, and that a short first round of sharing thoughts and gut feelings is useful.

  3. Symptoms

    While the old nodes of a GKE cluster were being drained to move workloads to a newly created node pool, none of the services in the cluster could be reached through ingress-nginx any more.

    Trigger

    Cordoning and draining the old node pool removed those nodes from the GCP load balancer backend while the ingress-nginx pods were still running on them.

    Root cause
    Component
    Contributing factor
    Detection

    The team noticed during the drain that no service in the cluster was reachable through ingress-nginx.

    Remediation
    • deleted the nginx-ingress-controller pods still running on the old nodes so they were rescheduled on the new, ready nodes
    Lessons

    With externalTrafficPolicy: Local, the load balancer can only reach nodes that run an ingress pod, and cordoned nodes leave the load balancer backend immediately; if the ingress pods stay behind on cordoned nodes, all ingress traffic stops. Before any change that might touch traffic, look twice into the documentation.

  4. Symptoms

    On 30 November 2017 at 16:59 PST, mybinder.org operators noticed that Grafana looked wrong and that launching a new server failed with an error that a temporary user could not be created. Pods that were already running kept running, but no new ones were being created.

    Trigger

    A build container, which ran without a memory limit, most likely used up all the memory on the node that ran the proxy pod.

    Root cause
    Component
    Contributing factor
    Detection

    An operator happened to look at Grafana at 16:59 PST, saw that it looked wrong, and confirmed the error by launching a new server.

    Remediation
    • Cordoned the node that had run out of memory
    • Uncordoned the node once the proxy was working
    Action items
    • Limit the memory available to build pods
    • Change the JupyterHub configuration so user pods are not cleaned up when the jupyterhub pod restarts
    • Nominate one person to drive the response, possibly in a shared terminal, so only one person changes the cluster
    • Alert when something is wrong with the cluster, for example by counting 4xx responses on the jupyterhub pod
Check your cluster for this

These 4 cases involve Ingress controller and Cloud load balancer. 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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