Cases46 cases

11 to 15 of 46

1. IL-0157 After a release, new nodes could not join Linode Kubernetes Engine clusters with IP ACL enabled, so autoscaling failed on about 20 to 25 clusters

   Linode2025

   Symptoms

   From about 01:00 UTC on 2025-03-05, Linode Kubernetes Engine (LKE) clusters with IP ACL enabled failed to autoscale: new nodes could not join the cluster, and some customers had service disruptions. About 20 to 25 clusters in several regions around the world were affected; the status page lists the US-IAD (Washington), US-ORD (Chicago), US-SEA (Seattle) and IN-MAA (Chennai) LKE components.

   Scale-up failureService outage

   Trigger

   Akamai deployed the latest LKE software release.

   Root cause

   Software defect

   Component

   Cluster autoscaler

   Contributing factor

   –

   Detection

   Customers began having problems at about 01:00 UTC, and the first status post, at 06:49 UTC, said the team was investigating an LKE autoscaling problem when IP ACL is turned on.

   Remediation

   • restarted the gateway pods, which gave only short-term relief
   • rolled back the release on all affected clusters

   Action items

   • Continue investigating the root cause and take preventive actions

   Lessons

   The defect hit only clusters with IP ACL enabled, and it showed when the autoscaler tried to add nodes. Restarting the gateway pods did not hold; rolling back the release ended the incident.

   View case
2. IL-0138 A failed Nvidia driver build left broken kernel packages on the only Kubernetes master node, which hit a kernel panic on reboot after a power outage and took the homelab cluster down for six days

   Barush Mendez2025

   Symptoms

   Every service in the homelab Kubernetes cluster stopped answering: the V-Rising server, Grafana, Jellyfin and Linkding were all unreachable, and the Kubernetes API was down, so the cluster could not be managed at all. The outage was found by hand, about 3 hours after it began, when someone tried to use the services.

   Control plane unresponsiveService outageMonitoring outage

   Trigger

   A power outage forced the Kubernetes master node to reboot.

   Root cause

   Software defect

   Component

   GPU driverLinux kernelKubernetes API server

   Contributing factor

   Ignored early signalChange with a delayed effectSingle point of failureMonitoring blind spot

   Detection

   Manually, when someone tried to access the services; there were no automated alerts.

   Remediation

   • Connected a monitor to the master node and read the boot logs, which showed the kernel panic
   • Booted the previous kernel version, which brought the system back
   • Removed the broken Nvidia packages with sudo apt-get remove --purge '^nvidia-.*' and ran sudo dpkg --configure -a
   • Found remaining broken packages with dpkg -l | grep -v ^ii and removed them by hand
   • Ran sudo apt-get install -f and reinstalled linux-headers-$(uname -r)
   • Rebooted and confirmed the kernel panic was gone

   Action items

   • Make sure GPU driver installations fully succeed, or revert immediately when they fail
   • Move the cluster to a high-availability control plane
   • Expose the Kubernetes API through a load balancer in the HA setup
   • Set up a ticketing system to record incidents and their resolution
   • Write predefined troubleshooting workflows to shorten response time
   • Add infrastructure monitoring such as Prometheus and Grafana
   • Add blackbox HTTP and TCP checks from outside the cluster for critical services

   Lessons

   A driver installation that fails half-way can leave kernel packages broken without any visible effect until the next reboot, which may come weeks later and at the worst time. A failed DKMS build should be fixed or reverted at once. With a single master node and no monitoring from outside the cluster, one unbootable machine meant a total outage that nobody was told about; the fix itself was simple once the boot logs were seen.

   View case
3. IL-0347 About 25% of Scaleway FR-PAR-1 hypervisors lost VPC connectivity when both VPC BGP route reflectors got stuck

   Scaleway2024

   Symptoms

   On 18 October 2024, from 7:50 to 8:01 UTC, about 25% of the hypervisors in Scaleway's FR-PAR-1 availability zone lost VPC connectivity with the rest of the region, and products that use VPC failed with them. Public internet connectivity and Elastic Metal VPC connectivity were not affected.

   Network unreachablePacket lossNode NotReady

   Trigger

   At 6:20 UTC a Top of Rack switch in FR-PAR-1 had a software crash. One of the two BGP route reflectors for VPC ran on a hypervisor in that rack and was left in an abnormal state.

   Root cause

   Software defect

   Component

   Network control plane (SDN)BGP routingNetwork switchDatabaseManaged Kubernetes control plane and provider API

   Contributing factor

   Excessive blast radiusAutomation amplification

   Detection

   Health-check monitoring on both route reflectors detected the anomaly, and the Scaleway Customer Excellence and SRE teams detected the customer impact and opened an incident.

   Remediation

   • Fixed both VPC route reflectors by manual action

   Action items

   • Fixed the autohealing mechanism that had failed to fix route reflectors stuck in a stale state; the fix is https://github.com/FRRouting/frr/pull/17163
   • Run different software versions on the route reflectors so a single bug cannot stop several instances
   • Investigate the software issue that left the route reflectors in a stale state

   View case
4. IL-0495 HubSpot's internal load balancers on Kubernetes were falsely marked unhealthy and the rest collapsed under the traffic

   HubSpot2024

   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.

   Probe failuresHigh latencyHigh error rate

   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

   Software defect

   Component

   Ingress controllerLiveness and readiness probes

   Contributing factor

   Automation amplificationNo headroom

   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.

   View case
5. IL-0148 A kube-scheduler regression in Kubernetes v1.27.14, v1.28.10 and v1.29.5 made the scheduler panic on a pod whose node affinity named a nonexistent node, so no pods were scheduled on affected AKS clusters

   Microsoft Azure2024

   Symptoms

   On AKS clusters running Kubernetes v1.27.14, v1.28.10 or v1.29.5, kube-scheduler panicked whenever the cluster contained a pod with a bad node affinity, and from then on no pod in the cluster was scheduled.

   Pods Pending

   Trigger

   A pod in the cluster with a required node affinity whose matchFields term names a node that does not exist.

   Root cause

   Software defect

   Component

   Pod scheduling and placement

   Contributing factor

   –

   Detection

   The AKS team found the bug; the issue does not say how.

   Remediation

   • AKS engineers fixed the impacted clusters
   • Rolled out a fixed kube-scheduler to all regions, applied to clusters automatically

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