Cases9 cases

7 to 9 of 9

1. IL-0021 GKE GPU nodes on Container-Optimized OS could not download NVIDIA drivers (403 Forbidden) and came up without working GPUs

   Google Cloud2024

   Symptoms

   From 08:00 US/Pacific on 12 March 2024, GKE GPU nodes running Container-Optimized OS (COS) that were newly created or recreated came up with GPU drivers that did not work, so workloads that used the GPUs could not run. GKE showed elevated errors.

   GPU unavailableNode NotReady

   Root cause

   Dependency failure

   Component

   GPU driverNode operating system imageNode pool

   Contributing factor

   Automation amplification

   Detection

   The report does not say how Google detected the issue. Affected users saw "Failed to download GPU driver installer, status: 403 Forbidden" on the GPU node when installing the driver.

   Remediation

   • Halted automatic node recreations, which attempt GPU driver downloads, until the issue was mitigated
   • Worked with the driver partner to resolve access to the driver download bucket

   Lessons

   The status page report states no lessons or follow-up actions.

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2. IL-0039 New Kubernetes worker nodes could not join any cluster because a package URL hardcoded in kops nodeup broke

   FREE NOW2019

   Symptoms

   At 16:00 CEST a developer reported in the #ask-platform Slack channel that a deployment to the Prelive cluster was failing, and a second report followed at 16:06.

   Pods PendingScale-up failure

   Trigger

   Roughly two to three days earlier, the CentOS repository mirror was restructured and container-selinux-2.68-1.el7.noarch.rpm moved, which made the static download URL hardcoded in kops nodeup invalid.

   Root cause

   Dependency failure

   Component

   Node operating system imageNode pool

   Contributing factor

   Monitoring blind spot

   Detection

   Developers asked for help in the #ask-platform Slack channel because their deployments were failing.

   Remediation

   • downloaded the package by hand on the Prelive nodes so their bootstrap could finish
   • changed the cluster AMI from Amazon Linux 2 to Debian and applied it to all clusters

   Action items

   • Create an alert that shows when nodes cannot join the cluster, possibly from information the cluster autoscaler already has
   • Document the external dependencies of node startup and look for ways to reduce them
   • Change the AMI back to Amazon Linux 2 Minimal once kops fixes the issue
   • Document node troubleshooting better: what happens during bootstrap and where the logs are

   Lessons

   Applying cluster changes through kops and Jenkins worked well, and troubleshooting quickly showed that the failing deployments came from missing cluster capacity. What went wrong was that nobody noticed, over a long period, that some autoscaling groups held more worker instances than Kubernetes had nodes. The team was lucky that no large number of production spot instances was terminated during the problem and that it was noticed during office hours.

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3. IL-0073 Intermittent Kafka connectivity overloaded Docker daemons, set off a node rescheduling cascade and poisoned the Consul gossip mesh

   Target2019sev1

   Symptoms

   An upgrade of the network subsystem under Target's datacenter OpenStack, meant to cause only a brief disruption, ran into problems and left network connectivity disrupted for several hours. Kafka, which runs on that OpenStack, became intermittently available.

   Node NotReadyLoad imbalanceHigh latencyCredentials unavailable

   Trigger

   A network subsystem upgrade in the datacenter OpenStack infrastructure disrupted connectivity for several hours and made Kafka intermittently available.

   Root cause

   Dependency failure

   Component

   Container runtimeService discoveryTelemetry agentCredential broker for pods

   Contributing factor

   Excessive blast radiusAutomation amplificationSingle point of failureUnpatched known bug

   Remediation

   • enabled gossip encryption on Consul so messages from the poisoned mesh were rejected
   • stabilized the deployment engine and redeployed the development environment with encryption, terminating instances without it
   • upgraded Consul in place to 1.2.3 and then to 1.3.0

   Action items

   • Reduce how much of an outage a single Docker daemon can cause, together with running smaller and more numerous clusters

   Lessons

   Smaller and more numerous clusters limited the damage: the smaller development clusters and production were not hit the same way as the one large cluster, and dev and prod on one cluster would have been far worse. A Docker daemon shared by many workloads is a brittle failure point. Per-workload logging and metrics sidecars were judged the right design; a shared cluster-level agent would almost certainly have made the problem worse and harder to fix.

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