Cases45 cases

36 to 40 of 45

1. IL-0143 GKE nodes upgraded to certain 1.13 and 1.14 versions had an elevated number of kernel panics, fixed by releases that downgraded the Container-Optimized OS image

   Google Cloud2019

   Symptoms

   Some nodes in Google Kubernetes Engine clusters that had recently been upgraded showed an elevated number of kernel panics. The status page described it as kernel panics following an upgrade in GKE version.

   Node kernel panic

   Trigger

   Upgrading GKE node pools to one of the affected 1.13 or 1.14 versions.

   Root cause

   Software defect

   Component

   Node operating system imageLinux kernel

   Contributing factor

   –

   Remediation

   • advised affected users to downgrade to a patch release not on the affected list, with support helping Release Channel users
   • released GKE 1.13.11-gke.14, 1.13.12-gke.8, 1.14.7-gke.23 and 1.14.8-gke.12, which downgraded Container-Optimized OS to cos-73-11647-293-0
   • rolled the fixed versions out to node pools with auto-upgrade enabled; clusters on manual upgrades had to upgrade their nodes themselves

   Action items

   • Ship a GKE release with an upgraded kernel that fixes the panics

   Lessons

   Downgrading the node operating system image was used as a temporary mitigation until a kernel fix was available.

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2. 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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3. IL-0011 HAProxy ingress piled requests onto the same pods because a Go template visited the backend map in sorted pod IP order

   Skyscanner2019

   Symptoms

   On a Sunday, a team using one of Skyscanner's Kubernetes clusters manually paged the out-of-hours Kubernetes support because their service showed elevated latency, worst at the p90 and maximum levels.

   High latencyLoad imbalanceOOMKilledIntermittent connection failures

   Trigger

   Upgrading the HAProxy ingress controller to v0.6 and going back from Service virtual IPs to individual pod IPs as backends, on the understanding that the sort-backends flag introduced in v0.5, false by default, meant backends were randomly shuffled.

   Root cause

   Software defect

   Component

   Ingress controllerHAProxyConfiguration templating

   Contributing factor

   Unrepresentative stagingUnverified assumptionIgnored early signal

   Detection

   A cluster user manually paged the out-of-hours Kubernetes support about elevated latency; Prometheus queries then showed the uneven request distribution across pods.

   Remediation

   • switched the affected service from pod IPs back to the Service virtual IP through a config change in the internal deployment tool Slingshot
   • patched the controller to keep each backend's servers in an insertion-ordered slice and changed the template to iterate over that slice
   • tested the patch in sandbox clusters and rolled it out to the production clusters

   Action items

   • Run the internal controller patch in production and return to pod IPs as the default backends
   • Raise the problem upstream with a GitHub issue and pull request
   • Test changes to cluster components against the specific behaviour and conditions that matter

   Lessons

   The team already knew that sorted backends cause hot-podding and still did not test the new flag well enough to see that it did not work; changes to cluster components need tests aimed at the exact behaviour that matters, under conditions like production. A keyword can behave differently in different parts of a language: range over a map is unordered in Go code but sorted in text/template. A small cluster component can do outsized harm to every user of the cluster and, in the end, to customers.

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4. IL-0030 Most nodes of a cluster went NotReady together for 15 minutes while the API server sat behind an AWS ELB

   Zalando2019

   Symptoms

   Fewer than 20% of the nodes in one Zalando cluster were available. Most nodes reported NotReady at the same moment, and only a handful stayed Ready.

   Node NotReady

   Root cause

   Software defect

   Component

   Kubernetes API serverCloud load balancer

   Contributing factor

   Unpatched known bug

   Remediation

   • none; the nodes recovered on their own after about 15 minutes

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5. IL-0050 Pods on Kubernetes failed to resolve an external Redis hostname because of ndots:5, the musl resolver in Alpine images, and Netty's DNS resolver

   Toyota Connected2018

   Symptoms

   Services that used the team's Redis-dependent library crashed on start-up, and their teams reported it to the ops members. The Spring Boot logs showed the applications failing to resolve the Redis hostname during bean initialisation.

   DNS resolution failuresIntermittent connection failures

   Root cause

   Software defect

   Component

   Client-side DNS resolver and cache

   Contributing factor

   Unreviewed defaultsUnverified assumption

   Detection

   Service teams reported start-up crashes to the ops members of the team; later the resolution failures were seen in Kibana.

   Remediation

   • set ndots to 4 with a dnsConfig block in the Kubernetes deployment manifests
   • corrected the maximum connection pool size in the Redis library, cutting Redis connections by about 70%

   Action items

   • Test Debian glibc-based base images added to the image library to see whether they resolve the DNS problems
   • Update dependencies to newer Netty versions

   Lessons

   With ndots:5, a name outside the cluster that has fewer than five dots is first tried with every cluster search domain. Adding a trailing dot avoids that, but only if every library in the path accepts it, and the Netty version in use did not. The ndots change is a workaround that will not hold forever. The author would like better alerting for this kind of failure but notes that alerts on one-off DNS failures are not wanted.

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