Cases15 cases

11 to 15 of 15

1. IL-0174 After an upgrade to Fluent Bit 2.0, logging sidecars that used the Kafka output plugin kept restarting with SIGSEGV because the plugin read a corrupted record as a map without checking its type

   Hyperconnect2023

   Symptoms

   Hyperconnect upgraded the Fluent Bit sidecar of one service with little user impact to Fluent Bit 2.0 and watched it for several days. Only the containers that used the Kafka output plugin were being restarted, each time on SIGSEGV. The stack trace printed at the crash pointed into the Kafka output plugin, but no core file was left behind, because Fluent Bit ran inside Kubernetes.

   Container crash loop

   Trigger

   Upgrading the Fluent Bit logging sidecar to version 2.0 (the 2.0.3 image) on a service with low user impact.

   Root cause

   Software defect

   Component

   Telemetry agent

   Contributing factor

   Limited debug access

   Detection

   The team monitored the upgraded sidecars for several days after the upgrade and saw that the containers using the Kafka output plugin were restarting with SIGSEGV.

   Remediation

   • patched the Fluent Bit Kafka output plugin to skip data that is not a map before calling produce_message()
   • ran a custom build with the patch as the sidecar, which stopped the segmentation faults
   • submitted the patch upstream as fluent-bit pull request 6452, which was merged eight days later

   Lessons

   A segmentation fault in a container can be debugged from its core file, but Kubernetes does not keep one by default: a volume mounted into the pod and a core_pattern pointing into it on the node are needed first. The debug image of the same version, run locally on the same CPU architecture with the matching source checkout, gives a gdb environment that matches production. Core files contain part of the process memory and may hold sensitive data, so they should be shared with care.

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2. IL-0107 Kyverno stuck in a crash loop behind a webhook with failurePolicy fail blocked every change to Kubernetes Service objects for 88 minutes

   DFDS2022

   Symptoms

   At 11:38 UTC on 3 August 2022 an end-user team told the platform team that applying a Service resource to one of the Kubernetes clusters failed.

   Deploys failingContainer crash loop

   Trigger

   A certificate chain in a third-party application expired, through no action of DFDS, and the outdated Kyverno installation got stuck in a crash loop.

   Root cause

   Certificate or credential expiry

   Component

   Policy engineAdmission webhook

   Contributing factor

   Deferred upgradesUnreviewed defaultsMonitoring blind spotIgnored early signal

   Detection

   An end-user team alerted the platform team at 11:38 UTC that applying a Service resource failed; the platform team started looking into it at 11:50 UTC.

   Remediation

   • reproduced the issue in a sandbox cluster and deployed the fix there first
   • updated Kyverno to a newer Helm chart version in the affected production cluster

   Action items

   • Implement monitoring on Kyverno
   • Create internal documentation on the Kyverno setup
   • Investigate the exact certificate issue in the third-party application
   • Consider changing the failurePolicy on ClusterPolicy resources going forward

   Lessons

   Operational issues should be added to the 'Ops Day to Day' board from the start.

   View case
3. IL-0093 Ingress controller pods crash-looped one after another because the leader pod had exhausted its shared memory

   UK Ministry of Justice2020

   Symptoms

   At 10:43 on 14 August 2020 two of the six ingress controller pods in the cluster were in a crash loop. Restarting those pods did not fix them.

   Container crash loop

   Root cause

   Capacity exhaustion

   Component

   Ingress controller

   Contributing factor

   Harmful manual actionSingle point of failure

   Detection

   Two of the six ingress controller pods were seen crash-looping at 10:43; the incident was declared at 11:01.

   Remediation

   • restarted the leader ingress controller pod so the other replicas could connect and get the latest nginx configuration

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4. IL-0176 Prometheus in a 235-node Kubernetes cluster crash-looped because over two million series exhausted host memory and the kernel OOM killer chose it first, as Burstable QoS gave it oom_score_adj 999

   LINE2020

   Symptoms

   One Monday morning the author opened the Prometheus dashboard to check a Kubernetes cluster for alerts and could not reach it. The Prometheus pod was in CrashLoopBackOff: kubectl get pods showed it 1/2 ready with 950 restarts over 3d20h on worker3.

   Container crash loopOOMKilledMonitoring outageProbe failures

   Trigger

   After start, the Prometheus time series count rose to 2,162,256 within five minutes and its memory use filled the 8GB host.

   Root cause

   Capacity exhaustion

   Component

   PrometheuskubeletLinux kernel

   Contributing factor

   No resource requests or limitsNo capacity planning

   Detection

   The author found it on a Monday morning when the Prometheus dashboard, opened to check the cluster for alerts, could not be reached.

   Remediation

   • removed most of the unnecessary settings from the Prometheus ConfigMap, after which the container stopped crashing

   Action items

   • Set appropriate resource requests and limits on the Prometheus pod
   • Reduce unneeded metrics by adjusting scrape targets or scrape interval
   • Estimate Prometheus memory needs, provide dedicated hosts with a node label such as deploy-topology: Prometheus, and pin the Prometheus pod to them with a nodeSelector

   Lessons

   Exit code 137 together with an OOM event in the kubelet log means the kernel killed the container, not kubelet. Under node memory pressure the kernel kills the process with the highest score, and kubelet derives each container's oom_score_adj from the pod's QoS class: a container without a memory request in a pod where another container has one ends up Burstable with a score near 1000, so it is killed first. In a large cluster, Prometheus memory needs to be estimated from the expected series count and requested explicitly.

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5. IL-0074 All AirMap platform services down as worker nodes went NotReady and pods crash-looped on network and DNS failures

   AirMap2018

   Symptoms

   At about 15:00 UTC on 19 July 2018, monitoring alerted on rising 5xx responses from several APIs, most notably pilot and tiles. Logins failed first, because the pilot service fetches the user's profile, and from there all services became unresponsive. Every affected API ran on the production Kubernetes cluster.

   High error rateNode NotReadyDNS resolution failuresContainer crash loopService outage

   Root cause

   Software defect

   Component

   kubelet

   Contributing factor

   Unpatched known bug

   Detection

   Monitoring alerted on an increase in 5xx responses from several APIs, most notably pilot and tiles.

   Remediation

   • restarted the kubelets on the stuck worker nodes, which did not last
   • restarted all worker nodes in a staggered order starting at about 18:00 UTC, which took about 1.5 hours

   Action items

   • Restart nodes on a rolling schedule to keep nodes and kubelets healthy until the fixes land upstream and reach the cloud provider, Microsoft Azure

   Lessons

   When nodes keep falling back to NotReady after kubelet restarts and pods fail on network and DNS errors, a known upstream bug may be the cause; matching the symptoms to the upstream issue tracker, with help from the community, found the cause and the fix candidates.

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