Cases12 cases

5 to 9 of 12

1. IL-0151 A latent defect in the AWS Lambda Frontend, set off when one us-east-1 cell scaled past a size never reached before, raised errors for Lambda and for services that depend on it, including new EKS cluster provisioning

   Amazon Web Services2023

   Symptoms

   From 11:49 AM PDT on 13 June 2023, Lambda function invocations in the Northern Virginia (us-east-1) Region returned more errors and took longer. Customers that triggered functions from asynchronous or streaming event sources saw their event backlogs grow because the events were not being processed.

   High error rateHigh latencyCredentials unavailable

   Trigger

   At 11:49 AM PDT, while adding capacity for normal daily traffic growth, the Lambda Frontend fleet in one cell crossed a capacity threshold that no single cell had reached before.

   Root cause

   Software defect

   Component

   Serverless function platform

   Contributing factor

   Unknown limit

   Detection

   Engineering teams were engaged immediately and began investigating; by 12:26 PM PDT they had identified the latent defect and its effect on provisioning compute capacity.

   Remediation

   • scaled the Lambda Frontend fleet down to a size that no longer triggered the latent defect

   Action items

   • Disable the Lambda Frontend scaling activities that triggered the event
   • Fix the latent bug and deploy the fix to all Regions
   • Complete action items addressing the immediate concern with cellular scaling
   • Bound all cells to a well-tested size to avoid unexpected scaling issues

   Lessons

   A fleet that scales automatically can grow into a size that was never tested, and a defect that only appears at that size stays hidden until ordinary daily growth reaches it. AWS's answer is to cap every cell at a well-tested size. For EKS users, the event shows that provisioning new clusters in us-east-1 depended on Lambda, while clusters that were already running were not affected.

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2. IL-0132 A faulty resource cleanup process marked Vertex AI prediction endpoints as deleted worldwide, undeploying customers' models and failing predictions for 4 hours 20 minutes

   Google Cloud2022

   Symptoms

   From 10:10 US/Pacific on 2 June 2022, Vertex AI Online Prediction returned errors for 30% up to 100% of requests per region, depending on how each customer used the service.

   High error rateResources deletedService outage

   Trigger

   A faulty resource cleanup process marked Vertex Prediction Endpoints as deleted, globally.

   Root cause

   Software defect

   Component

   Model request routing

   Contributing factor

   Automation amplificationExcessive blast radius

   Detection

   The first public status update was posted at 13:58 US/Pacific and gave the start as 10:20 US/Pacific; the later mini incident report gives 10:10.

   Remediation

   • restored the Vertex Prediction Endpoints that had been marked as deleted

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3. IL-0106 A malformed Traefik IngressRoute triggered a Traefik v2 bug once a node rollover restarted every Traefik pod, and all Kubernetes services returned 404

   DFDS2021

   Symptoms

   At 08:00 UTC on 2021-09-06 every service in DFDS's Kubernetes cluster answered with 404. Investigation started five minutes later.

   Service outageHigh error rateProbe failures

   Trigger

   The automated Kubernetes node rollover on 2021-09-06 restarted all the Traefik v2 pods, five days after a malformed IngressRoute manifest had been applied.

   Root cause

   Software defect

   Component

   Ingress controllerCloud load balancer

   Contributing factor

   Change with a delayed effectNo configuration testsExcessive blast radius

   Detection

   All services returned 404 from 08:00 UTC and root cause investigation started at 08:05. Time to detection was 5 minutes.

   Remediation

   • changed the ALB health check path, which made the targets healthy but did not stop the 404s
   • rolled back by hand to Traefik v1 as the main ingress controller
   • deleted the malformed IngressRoute by hand and confirmed the Traefik v2 bug
   • applied the changes upstream

   Action items

   • Upgrade Traefik to v2.5, where the bug is fixed, and verify that it removes the bug
   • Change the Traefik v2 health check path to something more robust
   • Set up an external liveness probe on the ingress controller
   • Consider workload segmentation to limit the blast zone
   • Look into monitoring the Traefik v2 API for rapid changes
   • Look into smoke testing during and after node rollover

   Lessons

   A malformed IngressRoute did nothing visible for five days and then took down all ingress when every Traefik v2 pod had restarted during a node rollover. Because Traefik v2 failed gracefully, the first signals pointed at the ALB health checks instead of at Traefik. On incident handling, the team concluded that appointing an incident manager could have helped, that the war room meeting should be recorded and a log book kept, that people not involved should only make suggestions in writing, and that a short first round of sharing thoughts and gut feelings is useful.

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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-0190 Cortex distributors kept a stuck connection to a dead etcd leader after a Kubernetes upgrade terminated its node, failing writes to Hosted Prometheus for 12 minutes

   Grafana Labs2020

   Symptoms

   About a minute after the etcd leader changed, two replicas of the Cortex distributor started logging "context deadline exceeded" when they tried to read keys from etcd. Writes from some customers that landed on those two replicas failed, while the other distributor replicas kept working, so the service saw an error rate of about 20% on writes to the London region of Hosted Prometheus.

   High error rateIntermittent timeouts

   Trigger

   A scheduled Kubernetes version upgrade abruptly terminated the node that ran the etcd leader at 11:19:00 UTC.

   Root cause

   Software defect

   Component

   etcdNode pool

   Contributing factor

   Unreviewed defaultsNo safeguard on destructive change

   Detection

   An SLO-based alert paged the on-call engineer at 11:31, 11 minutes after the errors started. At a 20% error rate the monthly SLA would have taken about 18 hours to breach.

   Remediation

   • Restarted the two affected Cortex distributor replicas at 11:32, which stopped the errors

   Action items

   • Enable gRPC keepalive probes in the Cortex etcd client (DialKeepAliveTime 10s, DialKeepAliveTimeout, PermitWithoutStream)
   • Make the Kubernetes upgrade process terminate pods and machines gracefully, including the etcd pods managed by the etcd operator

   Lessons

   When a node dies abruptly, clients holding TCP connections to it are not told; without keepalive probes an etcd client can keep sending requests into a dead connection long after a new leader exists. A failover that works on the server side still needs clients that detect the dead peer. Node replacement during cluster upgrades should drain pods gracefully, including pods owned by operators that the upgrade scripts do not know about, and should give instances enough time to shut down.

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