Cases45 cases

21 to 25 of 45

1. IL-0473 Jenkins infrastructure went fully down after a pod IP range fix deleted every AKS node pool and could not recreate them

   Jenkins project2023

   Symptoms

   On 7 July 2023 from 11:05 to 15:25 UTC many public Jenkins infrastructure services were completely down, including get.jenkins.io, plugins.jenkins.io, accounts.jenkins.io, javadoc.jenkins.io and incrementals.jenkins.io, while ci.jenkins.io, issues.jenkins.io, repo.jenkins-ci.org and www.jenkins.io were partly or completely disrupted.

   Network unreachableResources deletedCluster or node provisioning stallService outage

   Trigger

   After the upgrade to Kubernetes 1.25 changed the range of the pods' originating IP and LDAP access was blocked, a fix (Azure PR 431) deployed at 10:55 UTC to set a proper set of pod IP ranges removed all node pools of the cluster.

   Root cause

   Configuration change

   Component

   Node poolCNI pluginCloud load balancer

   Contributing factor

   Unverified assumptionNo staged rolloutNo safeguard on destructive change

   Detection

   After the upgrade, at 10:30 UTC, the team noticed that services inside the cluster, such as accounts.jenkins.io, could not reach the LDAP service.

   Remediation

   • Created the cluster again from scratch with a fixed network setup
   • Set a custom pod CIDR in a range separate from the virtual network
   • Moved the services and their DNS records to new public IPs
   • Pushed a pull request that recorded the manual rebuild, including the IP setup, in code

   Action items

   • Protect the public IPs from deletion with a Management Lock
   • Keep the public IPs in a separate resource group and point the Kubernetes-managed load balancers to it with the service.beta.kubernetes.io/azure-load-balancer-resource-group annotation
   • Improve network diagrams and documentation so possible overlaps are visible when preparing operations
   • Avoid changing the configuration of all AKS node pools at once

   Lessons

   The team said that changing one node pool at a time would have shown the problem after the first pool and avoided a full outage, and that the public IPs should change as little as possible because users behind corporate firewalls with allow-lists depend on them. The team also noted that it could rebuild, in under 4 hours, the cluster that hosts almost all public services.

   View case
2. IL-0091 Changing the worker node instance type through Terraform recycled all nodes at once and deleted users' production pods together

   UK Ministry of Justice2023

   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.

   Service outage

   Trigger

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

   Root cause

   Configuration change

   Component

   Node poolTerraform

   Contributing factor

   Excessive blast radiusNo runbook

   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

   View case
3. IL-0163 An API change that slipped through a gap in automated testing made LKE clusters resize to the wrong number of nodes and added billable worker nodes to customer accounts

   Linode2023

   Symptoms

   Resizing an LKE cluster produced an incorrect number of nodes, so some customer clusters were resized in unexpected ways and the extra worker nodes were billed to the customer accounts. The clusters themselves kept functioning. Linode's first status update, at 05:07 UTC on 1 June 2023, advised customers to avoid resizing their clusters if possible.

   Autoscaler misbehaviour

   Trigger

   At about 16:00 UTC on 31 May 2023 a change to the API that caused LKE clusters to scale improperly was pushed to production.

   Root cause

   Faulty deployment

   Component

   Node pool

   Contributing factor

   Gap in automated tests

   Detection

   The first status update, at 05:07 UTC on 1 June, said Linode had been made aware of an issue when resizing LKE clusters, about 13 hours after the change went out.

   Remediation

   • advised customers to avoid resizing their clusters
   • deployed a hotfix at 09:40 UTC on 1 June that corrected the scaling behaviour
   • left the extra worker nodes in place to avoid disrupting customer workloads
   • contacted affected customers by ticket about credit adjustments and further mitigation

   Action items

   • Audit the automated tests
   • Add pre-deployment checklist items so the same failure does not happen again

   Lessons

   An API change that alters scaling behaviour resized customer clusters and added cost while the clusters themselves kept working; Linode announced the issue about 13 hours after the change went out. Removing the extra nodes would have disrupted workloads, so the cost was handled through credits instead.

   View case
4. 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.

   View case
5. IL-0109 A retried node rollover on a DFDS EKS cluster set the Auto Scaling group back to 15 instances, and the default termination policy removed every healthy worker node, leaving the cluster with no nodes

   DFDS2023sev1

   Symptoms

   At 09:33 UTC on 14 February 2023 end users told the platform team that Kubernetes logs were not arriving in CloudWatch as expected. The investigation went through fluentd and found that the nodes were running containerd as their container runtime instead of docker-shim. A scheduled node rollover the day before, at 07:30 UTC on 13 February, had set containerd as the default runtime by accident.

   Service outageResources deletedMonitoring outage

   Trigger

   A scheduled node rollover had accidentally made containerd the default container runtime, which stopped log shipping to CloudWatch; the unscheduled rollover to revert it timed out, and the pipeline run that followed reduced the Auto Scaling group from 30 to 15 instances.

   Root cause

   Configuration change

   Component

   Container runtimeNode launch templateNode poolTerraformTelemetry agent

   Contributing factor

   Automation amplificationUnreviewed defaultsUnrepresentative stagingNo configuration testsNo runbookHarmful manual action

   Detection

   End users reported the missing CloudWatch logs that started the work. The postmortem lists 2 minutes as the time to detection of the node failure.

   Remediation

   • ran the node rollover script to add new nodes, which failed on a timeout from Docker Hub
   • ran the node rollover script a second time, which added new nodes that the load balancer marked healthy at 11:01 UTC

   Action items

   • Document the rollover process, especially what can be done when it goes wrong
   • Investigate options for improving the rollover process
   • Add fluentd log collection to the QA test suite so logs are covered end to end
   • Add alarms for fluentd when too little or no log data is sent
   • Implement a staging environment
   • Implement guards against selecting an invalid container runtime

   Lessons

   When a change goes wrong, rolling back to a known working configuration is safer than rushing a fix, which can make the damage worse. Launching new worker nodes depends on the cloud-init script not failing in any way. The QA configuration differed from production, there was no staging environment, the QA tests did not cover fluentd log collection, and the rollover process had no documentation for when it fails.

   View case

By root cause10