Cases4 cases

1 to 4 of 4

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.

   View case
2. IL-0203 A routine Kubernetes cluster system update made the AWS Load Balancer Controller fail, so new pods were never registered with the ALB and Honeycomb's EU1 ingest and UI went down once the last old pods were replaced

   Honeycomb2024

   Symptoms

   Event ingestion and the Honeycomb UI in EU1 became unavailable at 22:00:10 UTC on April 9, 2024, and the status page reported that the EU1 instance was down. Both the ingestion service and the service behind the web UI stopped at roughly the same moment.

   Service outageStale endpoint routing

   Trigger

   A routine system update to the Kubernetes cluster, rolled out earlier on April 9, followed by a regular deployment that replaced pods one at a time.

   Root cause

   Breaking change in an upgrade

   Component

   Ingress controllerCloud load balancer

   Contributing factor

   Monitoring blind spotUnrepresentative stagingChange with a delayed effect

   Detection

   The first status post, saying the EU1 instance was down, went up at 15:08 PDT (22:08 UTC), about 8 minutes after the outage began. There was no alerting on the AWS Load Balancer Controller.

   Remediation

   • Restarted the AWS Load Balancer Controller
   • Rolled back the Kubernetes cluster system update

   Action items

   • Find the exact cause of the failure so the system update can be deployed safely
   • Add monitoring and alerting on the AWS Load Balancer Controller so on-call engineers learn of a failure quickly and can pause deployments

   Lessons

   A rolling deployment can look healthy while the component that wires new pods into the load balancer is broken; the failure only shows when the last old pod goes away. Honeycomb now treats the AWS Load Balancer Controller as a critical component that needs its own alerting, so deployments can be paused before they remove the last pods that still receive traffic. Extensive testing in development and staging did not reveal the bad interaction.

   View case
3. IL-0111 Switching the main Kubernetes ingress controller from Traefik v1 to v2 stopped X-Forwarded headers being passed, which broke the Okta login flow for every service using Okta and stopped DFDS online bookings for over an hour

   DFDS2021

   Symptoms

   After the switch to Traefik v2, functional tests indicated that everything was fine, and this was reported on Slack at 08:44 UTC. The first sign of trouble came at 09:26 UTC, when a developer reported a high count of HTTP 307 redirects, especially on the Okta service. At 09:32 UTC the team learned that the online booking system was down.

   Service outage

   Trigger

   At 08:22 UTC the AWS load balancers were updated to send requests to the new Traefik v2 reverse proxy as part of the migration away from Traefik v1.

   Root cause

   Configuration change

   Component

   Ingress controllerCloud load balancer

   Contributing factor

   Missed in reviewMonitoring blind spot

   Detection

   A developer reported a high count of HTTP 307 redirects, in particular on the Okta service, at 09:26 UTC, 64 minutes after the change; six minutes later the team was told the online booking system was down. The functional tests run after the switch had not caught it.

   Remediation

   • Rolled back the switch to Traefik v2, putting rollback ahead of investigation because of how critical the booking system is

   Action items

   • Consider how critical announcements can be made more visible
   • Consider whether the ALBs used for testing should have been shared with the teams so they could test their own scenarios

   Lessons

   Cloud Engineering cannot test every application scenario on its own, even after testing its own applications for weeks. A header that changes value behind a new ingress controller, here x-forwarded-proto going from https to http, can break an authentication flow while basic functional tests still pass. DFDS asks whether diffing request headers before and after the migration would have shown the problem in advance.

   View case
4. IL-0052 A cryptocurrency miner ran on every node of the development and staging clusters through a public, unauthenticated Weave Scope dashboard

   JW Player2019

   Symptoms

   Datadog alerted the DevOps team to a high normalised load average, first on the staging cluster (Day 0, 21:06 EST) and the next day on the development cluster (Day 1, 16:53 EST). The load was first put down to a legitimate service that kept scaling up and down in both environments, and because of the volume of identical alerts they were muted until things settled.

   Sustained high node CPUUnauthorised access or a foreign workload

   Trigger

   An automated crawler found the Weave Scope dashboard on a public load balancer that required no authentication. Weave Scope can open a shell in running containers, and its scope-agent containers ran privileged, as root and with the host's root filesystem mounted, so a command started there could run on the host.

   Root cause

   Configuration change

   Component

   Cluster dashboardCloud load balancer

   Contributing factor

   Ignored early signalUnreviewed defaultsExcessive blast radiusMonitoring blind spot

   Detection

   Datadog alerts on high normalised load average, muted at first as noise from a legitimate service; on Day 3 an engineer ran top on a node and found the gcc process at 100% CPU.

   Remediation

   • stopped Weave Scope and removed its deployment from all Kubernetes clusters
   • checked access logs for unauthorised access to the instances
   • confirmed the miner's outbound connections went only to a mining pool
   • isolated one affected node for later investigation
   • rotated out every node in each cluster so all affected hosts were destroyed and rebuilt

   Action items

   • Audit all Kubernetes and deployment YAML files and security groups for services that are unintentionally public or misconfigured
   • Replace load-average alerts with more meaningful monitors and tune them to signal a real anomaly
   • Research tools such as falcon or sysdig for behavioural monitoring and anomaly and intrusion detection
   • Evaluate Istio and Linkerd for observing and controlling end-to-end network traffic
   • Analyse the cost of scanning Docker images and containers for known vulnerabilities
   • Set aside time in architecture discussions to revisit older choices such as running containers as root
   • Share knowledge of large projects, such as Kubernetes version migrations, across the whole team

   Lessons

   Load average was not a useful signal for spotting a problem in the clusters, and muted noisy alerts nearly hid the miner. A load balancer that Kubernetes creates belongs to Kubernetes: a manual security group edit in the AWS console is reverted, so internal exposure must be declared in the Kubernetes YAML. A dashboard that can open shells, in front of privileged agents that mount the host's root filesystem, gives whoever reaches it root on every node.

   View case

By root cause3