Cases43 cases

28 to 32 of 43

1. 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.

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2. 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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3. IL-0086 A deployment meant for a CircleCI test Kubernetes cluster also removed Traefik and Calico resources from the production cluster, taking down the CircleCI UI and runner.circleci.com

   CircleCI2021

   Symptoms

   At 15:35 EST on 11 March 2021 the CircleCI web UI and runner.circleci.com became unavailable. The API, which uses a separate ingress point, stayed reachable, and builds kept running.

   Service outageResources deleted

   Trigger

   An update deployed to a test Kubernetes cluster also removed Traefik and Calico resources from CircleCI's primary production cluster.

   Root cause

   Faulty deployment

   Component

   Ingress controllerCalico

   Contributing factor

   Excessive blast radiusNo runbookMonitoring blind spot

   Detection

   CircleCI engineers were alerted and began investigating. The status page posted its first notice at 20:45 UTC.

   Remediation

   • restored Traefik in the production cluster
   • restored Calico in the production cluster, after which pods served customer requests again

   Action items

   • Improve network-level documentation and runbooks to cover every layer of the Kubernetes networks
   • Improve monitoring and alerting for the network infrastructure
   • Add guardrails that isolate the production and staging clusters so they cannot interfere with each other

   Lessons

   A deployment path that can reach both a test cluster and production can remove shared networking components from production. When the ingress controller and the CNI are both affected, restoring the ingress alone is not enough: engineers had to find the link between Calico and Traefik and restore Calico before pods served traffic again. Time went to DNS and AWS red herrings because nothing linked the outage to the test deployment; CircleCI's answer is better network runbooks, network alerting and guardrails between clusters.

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4. IL-0032 Mutating admission controller generated broken JSON patches, silently blocking deploys for a week until a production service ran down to two pods

   Airbnb2020

   Symptoms

   A production service at Airbnb showed a high error rate and could not be deployed. The deploy failed with a cryptic Kubernetes error about being unable to access invalid index 5.

   High error rateThroughput degradationDeploys failing

   Trigger

   A change to the mutating admission controller, which had been rolled out within the previous month, had gone in seven days before the incident surfaced; when it had to delete two items from an array in a spec, it generated an invalid JSON patch that removed index 2 and then index 3.

   Root cause

   Software defect

   Component

   Admission webhookHorizontal pod autoscaler

   Contributing factor

   Change with a delayed effectMonitoring blind spotIgnored early signal

   Detection

   The affected service reported a high error rate and its deploy failed; the slow degradation of other services over the previous seven days had gone unnoticed.

   Remediation

   • deleted the mutating admission controller from the affected cluster

   Action items

   • Create alerts from the existing metrics that would have shown the problem earlier

   Lessons

   Keep in mind that a mutating admission controller exists in the cluster; a recently added one is easy to forget during an incident. Search for the exact error message early instead of working on the visible symptoms. Page a teammate when progress stalls.

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5. IL-0041 fluent-bit silently stopped shipping application logs from one node to Elasticsearch

   PrometheusKube2020

   Symptoms

   On a Tuesday morning a developer reported that some production logs were missing. Only the logs from a single node were gone; the other nodes kept shipping normally through fluent-bit, the log shipper the team had run for more than three years.

   Monitoring outage

   Root cause

   Software defect

   Component

   Telemetry agentElasticsearch or OpenSearch

   Contributing factor

   Monitoring blind spotUnpatched known bug

   Detection

   A developer reported missing production logs; no alert fired because fluent-bit's metrics showed no errors.

   Remediation

   • added CPU to the Elasticsearch virtual machines, which cleared the write queue rejections
   • rolled out Fluentd one node at a time, using node affinity to place Fluentd and anti-affinity to remove fluent-bit
   • lowered Fluentd's flush_thread_count to 1 and set flush_interval to 5 seconds so the backlog of old logs did not overflow the buffer
   • enabled Fluentd's Position DB so already-ingested data was skipped

   Action items

   • Build monitoring for Fluentd on its Prometheus integration, including a throughput alert with separate day and night thresholds or a black-box log check

   Lessons

   A log shipper can fail without an error message and with metrics that simply stop moving, so error-based alerts never fire; throughput alerts or end-to-end checks can catch it. Open source software can break in ways nobody expects, and sometimes the way out is to switch to a different shipper fast, node by node. A new shipper that starts from scratch replays every old log on the node and needs to be slowed down.

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