Cases2 cases

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1. IL-0205 The GKE cluster autoscaler could not add nodes to GitLab.com's production cluster because Google Cloud ran out of SSD persistent disks in us-east1

   GitLab2021

   Symptoms

   At 08:05 UTC on 2021-06-21 the API service's Apdex (the share of requests that finish within a target time) and Rails request queuing began trending the wrong way. At 09:01 the team found the API deployment unhealthy: it needed more pods for the day's growing traffic, but no new nodes could be added to give it pod capacity. Users saw slow responses; the review found no sign that error rates rose.

   Scale-up failureHigh latencyPods PendingDeploys failing

   Trigger

   Google Cloud ran out of SSD persistent disk stock in us-east1, the region GitLab.com runs in, while the API service needed more nodes for rising user traffic.

   Root cause

   Cloud provider outage

   Component

   Cluster autoscalerNode pool

   Contributing factor

   Monitoring blind spotLimited debug accessOverlapping failures

   Detection

   There was no alert on resource availability. Apdex and Rails queuing began trending the wrong way at 08:05 UTC and an engineer declared the incident in Slack at 08:43; finding the cause took a lot of log digging: cluster autoscaler errors about node pools in backoff, then ZONE_RESOURCE_POOL_EXHAUSTED at the instance-group level, and finally Google Cloud support naming SSD as the exhausted resource.

   Remediation

   • added a node pool that uses pd-standard disks
   • scaled the new node pool by hand across all three zones to relieve the API
   • brought more pd-standard node pools online for the other blocked workloads
   • stopped production deployments and opened a Google Cloud support case about the cluster autoscaler not working with the new node pools
   • changed node pools and nodeSelectors so the remaining workloads ran on pd-standard nodes
   • removed the SSD-backed node pools after a day without problems

   Action items

   • Move Kubernetes services to pd-standard disks (delivery#1837)
   • Capture resource exhaustion errors as a metric

   Lessons

   A cloud region can run out of one specific resource, here SSD persistent disks, and the only error may be a generic ZONE_RESOURCE_POOL_EXHAUSTED that does not name it. GitLab could neither monitor nor reserve resource availability, so detection took 22 hours and the cause came from Google Cloud support. The workloads ran fine on pd-standard disks. A second problem found on the way, a cluster autoscaler that does not fall back to another matching node pool when one cannot scale, slowed the move to the new node pools.

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2. IL-0505 kubectl logs failed on GKE with "No SSH tunnels currently open" and mybinder.org build logs stopped reaching users

   Binder Project2019

   Symptoms

   On 20 February 2019 at 08:03 CET, `kubectl logs -f <pod>` stopped working for every pod in the mybinder.org cluster on GKE. Because pod logs could not be read, build logs were no longer forwarded to users, although the builds themselves ran normally.

   Monitoring outageDeploys failing

   Root cause

   Cloud provider outage

   Component

   GKE control planeKubernetes API server

   Contributing factor

   Limited debug access

   Remediation

   • Cordoned node gke-prod-a-users-b921bb88-rd5d so it would be removed from the pool once empty
   • Drained the node and removed it from the pool, after which kubectl logs worked again

   Action items

   • Test that kubectl logs works and notify when it does not
   • Add the command for retrieving API server logs to the SRE guide
   • Describe in the SRE guide how to identify suspicious node networking status

   Lessons

   The root cause was very difficult to identify, partly because it appears to sit in the Kubernetes master or the GKE service itself. Capturing `kubectl describe node` for the suspicious node would have allowed a comparison with healthy nodes, and a node that reports no ExternalIP or InternalIP in its status was likely a direct symptom of the problem and can be used as a diagnostic in the future.

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