Cases7 cases

1 to 5 of 7

1. IL-0188 Rolling updates on EKS returned 502 errors for about 30 seconds because Kubernetes deleted old pods as soon as new pods passed readiness, before the ALB had marked the new pod targets healthy

   Yonghyun Kim2025

   Symptoms

   Every rolling update of the team's microservices on Amazon EKS, behind an Application Load Balancer, was followed by intermittent 502 and 503 errors for users. A Slack message at 3 a.m. read "배포는 성공했는데, 서비스는 죽었다" (the deployment succeeded, but the service died). Every pod was Ready and Datadog was green while users saw errors.

   High error rateService outage

   Trigger

   A rolling update of a Deployment served through an ALB that registers pod IPs as targets, with no pod readiness gates.

   Root cause

   Faulty deployment

   Component

   Cloud load balancerIngress controllerPod termination

   Contributing factor

   Unverified assumptionUnreviewed defaultsMonitoring blind spot

   Detection

   A Slack message at 3 a.m. reported that the deployment had succeeded but the service was down; Datadog dashboards were green at the time.

   Remediation

   • labelled the namespace with elbv2.k8s.aws/pod-readiness-gate-inject=enabled so the AWS Load Balancer Controller injects pod readiness gates and Kubernetes waits for the ALB target to be healthy before deleting old pods

   Lessons

   A pod being Ready in Kubernetes does not mean the load balancer will send it traffic. Without a readiness gate, a rolling update can delete the old pods while the ALB still considers the new targets unhealthy, and dashboards that track pod status stay green during the errors. Making pods wait longer on shutdown reduced the errors but did not fix the start-up gap and made every deployment much slower; the readiness gate ties the pod's Ready state to the ALB's view of the target.

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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-0062 Intermittent 502 errors behind a GKE Ingress because pods shut down before the load balancer stopped sending them traffic

   Ravelin2019

   Symptoms

   After Ravelin moved its API layer from VMs into its GKE cluster behind a Kubernetes Ingress, the integration tests occasionally received 502 errors.

   Intermittent connection failuresStale endpoint routing

   Trigger

   Pods behind the Ingress being removed by their controller, as happens during rolling deploys and scaling.

   Root cause

   Software defect

   Component

   Ingress controllerPod termination

   Contributing factor

   Unverified assumption

   Detection

   Integration tests occasionally received 502 errors.

   Lessons

   Removing a pod's endpoint and signalling the pod happen at the same time, and an ingress can take a long time to catch up. A pod behind an ingress should keep serving after SIGTERM until its grace period ends, and the grace period should be longer than the load balancer's reprogramming time.

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