Cases43 cases

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1. 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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2. 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 Plus2022

   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.

   Connection resetsDatabase overloadIntermittent connection failuresHigh latency

   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

   Configuration change

   Component

   HAProxyCloud load balancerconntrack tableIngress controller

   Contributing factor

   Change with a delayed effectExcessive blast radiusRetry stormUnverified assumption

   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.

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3. IL-0522 An ingress-nginx chart upgrade deleted the jenkins.io Ingress and Fastly served HTTP/503 errors for hours

   Jenkins project2021

   Symptoms

   At 11:32 UTC on 18 November 2021, a user reported in the jenkinsci/jenkins Gitter channel that https://www.jenkins.io/doc/pipeline/steps/ was answering HTTP/503 errors with the message "Guru meditation" from Fastly's varnish.

   Service outageResources deleted

   Trigger

   The ingress-nginx Helm chart was upgraded from 4.0.6 to 4.0.8 at 10:42 UTC, and the new chart added an admission webhook rule that forbids Nginx configuration blocks in Ingress annotations.

   Root cause

   Breaking change in an upgrade

   Component

   Ingress controllerAdmission webhookHelmCDN and edge network

   Contributing factor

   Unverified assumptionCache-masked failureMonitoring blind spotHarmful manual action

   Detection

   A user reported in the jenkinsci/jenkins Gitter channel at 11:32 UTC that a jenkins.io page answered HTTP/503 errors, and status.jenkins.io reported the incident at 11:49 UTC.

   Remediation

   • Disabled the automated systems, rolled the ingress-nginx chart back to 4.0.6 and deleted the admission webhook by hand
   • Removed the forbidden annotations from the jenkins.io configuration
   • Upgraded the jenkins.io Helm chart to the last version known to work with ingress-nginx 4.0.8
   • Redeployed the jenkins.io Helm chart through the automated system and told Fastly to drop all cached pages

   Action items

   • Always read the changelog in depth when updating the ingress controllers, with two people pairing in real time
   • Add custom Datadog monitoring for www.origin.jenkins.io so that such an outage is detected
   • Make the monitor send the Host header www.jenkins.io so it is not redirected to Fastly
   • Check a set of pages, such as the pipeline steps page, not only the front page
   • Consider an ephemeral k3s end-to-end test before deploying to production

   Lessons

   Trusting a patch version of a Helm chart for the Ingress controller without reading its changelog in depth let a new admission rule remove the jenkins.io Ingress in production. Without monitoring on origin.jenkins.io, a user found the outage. A complete staging cluster with the same DNS setup would have caught the problem before production.

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4. IL-0442 Older pods on LIFULL's KEEL Kubernetes cluster were preempted all at once and the external error rate spiked

   LIFULL2021

   Symptoms

   Shortly after the KEEL team applied new PriorityClasses to KEEL, LIFULL's Kubernetes cluster, and saw pods with the low class being preempted as intended, the team received a flood of alerts from external monitoring: the error rate of requests coming from outside the cluster had risen sharply.

   Pod evictionHigh error rate

   Trigger

   The KEEL team deployed three PriorityClasses to the running cluster: low with value: 100, medium with globalDefault: true and value: 1000, and high with value: 10000.

   Root cause

   Configuration change

   Component

   Pod priority and preemptionIngress controller

   Contributing factor

   Unverified assumption

   Detection

   External monitoring sent the team a large number of alerts about a sharp rise in the error rate of requests from outside the cluster.

   Action items

   • Redefine the PriorityClasses as low (-10), medium (0, globalDefault) and high (10), each with a non-preempting variant

   Lessons

   Adding PriorityClasses to a running cluster needs care because every existing pod has priority 0, and a globalDefault class above 0 makes all pods created before it candidates for preemption. PodDisruptionBudgets do not reliably protect pods from preemption. In a multi-tenant cluster, the permission to deploy PriorityClasses should be restricted, and the PriorityClasses tenants may use should be controlled with ResourceQuota or OPA Gatekeeper.

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5. IL-0209 A too-high HPA CPU target kept GitLab.com web pods from scaling up as traffic moved from VMs to Kubernetes, breaching the web latency SLO for 15 minutes

   GitLab2021

   Symptoms

   The web service breached its latency SLO at 07:30 UTC and its Apdex dropped: some requests to the GitLab.com web front end slowed down for about 15 minutes. This happened while web traffic was being shifted from virtual machines to the web pods on Kubernetes, and the pods did not scale up as the traffic arrived.

   High latencyAutoscaler misbehaviour

   Trigger

   Shifting web traffic from VMs to Kubernetes pods during the GitLab.com web migration.

   Root cause

   Configuration change

   Component

   Horizontal pod autoscaler

   Contributing factor

   Unverified assumption

   Detection

   The web latency SLO breach at 07:30 UTC; an engineer declared the incident in Slack at 07:40.

   Remediation

   • Lowered the target CPU utilisation of the web pods' autoscaler to a more conservative value (merge request gitlab-com/gl-infra/k8s-workloads/gitlab-com!1149)

   Action items

   • Adjust the target utilisation for the web pods (gitlab-com/gl-infra/k8s-workloads/gitlab-com!1149)

   Lessons

   When traffic is moved onto pods that rely on CPU-based autoscaling, a CPU target set too high can keep the pods from scaling as the traffic arrives; GitLab fixed it by setting a more conservative target.

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