Cases10 cases

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1. IL-0020 During an EKS 1.30 upgrade the descheduler tried to reschedule every pod on the cordoned nodes at once and production workloads went down

   UK Ministry of Justice2025

   Symptoms

   At 09:36 on 18 March 2025, during the upgrade of the live cluster to EKS 1.30, users reported that their pods were being terminated and were not restarting automatically, in both production and non-production environments. Automated infrastructure alerts fired as well, and production services had outages.

   Pod evictionPods PendingService outageUpgrade stall

   Trigger

   Upgrading the live EKS cluster from 1.29 to 1.30, during which the descheduler attempted to reschedule all pods on the cordoned nodes simultaneously.

   Root cause

   Faulty deployment

   Component

   DeschedulerNode poolCluster autoscaler

   Contributing factor

   No headroomNo alert on limitUnreviewed defaults

   Detection

   Users reported at 09:36 that pods were being terminated and not restarting, and automated infrastructure alerts fired.

   Remediation

   • Removed the cordon annotation so pods could be rescheduled
   • Deleted stuck 1.30 nodes to force their recreation
   • Added a new node group of 20 nodes running 1.30 by hand
   • Cordoned and drained all old 1.29 nodes onto the new 1.30 nodes

   Action items

   • Raise an AWS Production System Down support case (Case ID: 174229643100496)
   • Get guidance from AWS support on querying control-plane logs to find the root cause of similar issues
   • Document a runbook for emergency scaling of a new node group in case of unexpected capacity shortages
   • Alert on an imbalance between the autoscaling group and the Kubernetes nodes
   • Review the descheduler configuration to understand why it throws pods off cordoned nodes, and fix it where possible
   • Alert on spikes in the pending pod count

   Lessons

   The write-up lists review actions rather than lessons. They show the team had no documented way to add an emergency node group, no alert on a mismatch between the autoscaling group and the nodes Kubernetes sees, no alert on a spike in pending pods, and no clear understanding of how the descheduler treats cordoned nodes.

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2. IL-0114 An unpinned AWS VPC CNI plugin was updated automatically during a capacity expansion, leaving new pods Pending without IP addresses and stopping CoW Protocol settlements for about 3.5 hours

   CoW Protocol2024

   Symptoms

   At 16:40 UTC on 19 April 2024 CoW Protocol's mainnet production environment stopped producing settlements; the outage officially began then.

   Pods PendingIP address exhaustionPod evictionService outage

   Trigger

   During a cluster capacity expansion, the Infrastructure as Code automation updated the AWS VPC CNI plugin, because the CNI version was not hardcoded in the IaC and the IaC library version had recently changed.

   Root cause

   Configuration change

   Component

   AWS VPC CNINode pool

   Contributing factor

   Unpinned versionOverlapping failures

   Detection

   The CNI version mismatch was identified as the cause at 17:03 UTC, 23 minutes after settlements stopped.

   Remediation

   • upgraded the Kubernetes cluster
   • set up new node groups with a new version of the networking plugin

   Lessons

   Versions in IaC scripts should be specified explicitly so an automation run cannot update a component such as the CNI plugin unintentionally. Changes in production need change management that is easy to revert.

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3. IL-0231 Deleting EKS managed node groups also deleted Karpenter's instance profile, and every Stytch worker node shut down

   Stytch2023

   Symptoms

   On 23 February 2023 Stytch's EKS worker nodes went Ready:Unknown one after another, Karpenter failed to launch replacement nodes, and with fewer and fewer pods scheduled the Live Stytch API went down for 14 minutes, returning 5XX on every call.

   Node NotReadyScale-up failurePod evictionPods PendingService outage

   Trigger

   At 14:21 UTC Stytch landed a change to remove unused EKS managed node groups, because it had decided to run its data plane applications fully on nodes provisioned by Karpenter. Because Crossplane resources use an orphan deletion policy, engineers deleted the node groups in the AWS console, first in staging and then in production.

   Root cause

   Configuration change

   Component

   KarpenterNode poolConfiguration templating

   Contributing factor

   Unverified assumptionShared credentialChange with a delayed effectIgnored early signal

   Detection

   Low-urgency alerts that Karpenter could not find the instance profile fired in staging at 16:06 UTC and in production at 17:48 UTC but were not treated as an incident. The incident process started at 20:26 UTC when node launch failures spiked the Karpenter error rate, and Kubernetes monitoring alerts in production followed at 20:44 UTC. The support team flagged the outage at 21:14 UTC.

   Remediation

   • Reverted the node group deletion, which recreated the managed node groups
   • Manually scaled up one of the Live API node groups with more and much larger nodes and removed its taints
   • Removed node selectors from the applications one after another so their pods could be scheduled

   Action items

   • Treat Karpenter errors as high-urgency alerts that page the on-call engineer
   • Tune cluster alerting thresholds to send a high-urgency page earlier
   • Add alerts for nodes that stay NotReady or Unknown for long periods
   • Raise the thresholds of other deployment alerts, such as unschedulable pods and replicas not available
   • Give Karpenter its own IAM instance profile, separate from the one used by the node groups
   • Separate other AWS resources that were shared between uses, specifically IAM and security groups
   • Rework the EKS and Karpenter configuration so system instance profiles are unique, static per cluster and generated by Karpenter
   • Introduce a cloud visualization tool for engineers making infrastructure changes
   • Add live system and product metrics to the status page
   • Ask AWS to confirm the undocumented actions and side effects of deleting a node group
   • Correct the shared use of IAM roles and security groups across the infrastructure

   Lessons

   The IAM role for Karpenter's self-managed nodes should never have been the same as the one for the managed node groups; sharing it is what let the node group deletion break Karpenter, and the roles had been left combined for speed and simplicity when Karpenter was first set up. The hours-long delay between the configuration change and its effect made the incident hard to assess, and AWS confirmed that this delay is expected, so Stytch will allow for it in future IAM instance profile changes.

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4. IL-0070 Critical pods on core nodes evicted when Prometheus began scraping about 200 nodes after a dask-gateway scale-up

   2i2c2023

   Symptoms

   The hub pod of the prod JupyterHub on the leap cluster (leap.2i2c.org) restarted unexpectedly during a large node scale-up, and a user opened a support ticket. The ingress-nginx and proxy pods kept running.

   Pod evictionPods Pending

   Trigger

   A user's dask-gateway workload added about 100 dask-worker nodes within a minute, and Prometheus started scraping the metrics exporters on about 200 nodes.

   Root cause

   Capacity exhaustion

   Component

   PrometheusNode pool

   Contributing factor

   No headroomExcessive blast radiusMonitoring blind spot

   Detection

   A user support ticket (2i2c Freshdesk ticket 414) about the leap hub; the engineer then looked at Grafana and the cluster's nodes and events.

   Action items

   • Configure CPU and memory requests for the hub and proxy pods (#2127; at least 100m CPU was proposed)
   • Make the Grafana OOMKiller dashboard work (#2213)
   • Move LEAP cloud infrastructure to shared nodes (#2209)
   • Update resource requests and limits, mainly for ingress-nginx and Prometheus (#2324)
   • Decide whether Prometheus should scrape dask worker pods (#2366)

   Lessons

   Prometheus load grows with the number of nodes, so a burst of autoscaled nodes can push a nearly full core node over the edge and evict the pods that matter most. Core pods that request 10m of CPU get a tenth of the CPU share of busy neighbours that request 100m. Kubernetes events expire after an hour, so evidence of OOM kills needs a dashboard that keeps it.

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5. IL-0096 A GKE node pool pinned to the europe-west2-b zone could not scale for 6.5 hours because Google ran out of resources in that zone (ZONE_RESOURCE_POOL_EXHAUSTED)

   2i2c2022

   Symptoms

   A user of the LIS JupyterHub reported a "backoff after failed scale-up" error, and user servers would not start. An engineer opened incident #36, "LIS hub cannot scale", at 5:40 AM Pacific on 14 November 2022.

   Scale-up failurePods PendingService outage

   Trigger

   At 10 AM UK time on 14 November 2022, the B zone of Google Cloud's europe-west2 region (London) ran out of resources to allocate. The LIS cluster's nodes were restricted to that zone.

   Root cause

   Cloud provider outage

   Component

   Node poolCluster autoscaler

   Contributing factor

   Single point of failurePages not delivered

   Detection

   A user reported the "backoff after failed scale-up" error; an engineer opened the incident at 5:40 AM Pacific, about three hours and forty minutes after the zone ran out of resources.

   Remediation

   • edited the node pool in the GCP console to allow node creation in the A and C zones of europe-west2, which were not exhausted

   Action items

   • Either restrict the node pool back to the B zone after the Black Friday event, or move the cluster and the NFS Filestore to the A zone (infrastructure issue #1944)
   • Investigate an enterprise plan that allows a regional NFS, at higher cost (infrastructure issue #1945)
   • Make sure PagerDuty notifications always get through to engineers (team-compass issue #574)

   Lessons

   A node pool pinned to one zone for storage performance cannot scale when the cloud provider runs out of capacity in that zone. The autoscaler's "backoff after failed scale-up" message usually points to quotas, and raising quotas does nothing here; the ZONE_RESOURCE_POOL_EXHAUSTED error in the logs is what identifies a zone without capacity. The review found that one engineer wearing many hats (incident commander, comms and debugging), with pages not reaching the other responders, made the response harder; a team response would have given more support.

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