Cases35 cases

26 to 30 of 35

1. IL-0105 Replacing the AWS VPC CNI during a Terraform refactoring detached the ALB target groups, and every service in the Kubernetes cluster returned 503

   DFDS2021

   Symptoms

   At 08:29 UTC on 22 June 2021 alerts fired because all services in the Kubernetes cluster were returning 503. No inbound traffic was reaching the cluster. A customer reported the problem at 08:32.

   Service outageHigh error rate

   Trigger

   The pipeline replaced the AWS VPC CNI as part of a refactoring that moved EKS add-ons from kubectl to native Terraform management.

   Root cause

   Configuration change

   Component

   AWS VPC CNICloud load balancerTerraform

   Contributing factor

   Unverified assumptionNo configuration tests

   Detection

   Alerts fired at 08:29 UTC, eight minutes after the VPC CNI was replaced; a customer reported the issue at 08:32.

   Remediation

   • committed a fix that reverted the infrastructure-modules reference
   • re-triggered the pipeline after it failed on an AWS API timeout
   • let the pipeline reattach the target groups to the ALB

   Action items

   • Revert the ALB de-registration delay to the default of 300 seconds
   • Update the roll-over script to set the ALB de-registration delay to zero temporarily before a roll-over
   • Create an ingress test suite

   Lessons

   The change to the de-registration delay had been weighed mainly for performance. Critical pipeline runs should be watched while they run. Everyone should receive the alerts and react to them, and alert messages that were unclear should be reworded.

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2. IL-0108 An Alcide admission controller applied to the production cluster during a workshop made create and update requests on Deployments time out

   DFDS2020

   Symptoms

   At 14:41 CET on 4 November 2020 users reported timeouts when deploying to Hellman, the production Kubernetes cluster. The timeouts were confirmed at 15:04.

   Deploys failingControl plane lag

   Trigger

   During an Alcide workshop that began at 13:00 CET, an Alcide admission controller was applied to the production cluster at 13:13 in the belief that it would not disrupt anything.

   Root cause

   Configuration change

   Component

   Admission webhookKubernetes API server

   Contributing factor

   No configuration testsUnverified assumptionMonitoring blind spot

   Detection

   Users reported timeouts when deploying to the Hellman cluster at 14:41 CET; the timeouts were verified at 15:04.

   Remediation

   • toggled the Alcide admission controller to verify that it caused the timeouts
   • permanently deleted the Alcide admission controller

   Action items

   • Monitor Kubernetes deployments for timeouts
   • Monitor 5xx status codes from the Kubernetes API server

   Lessons

   New components are applied in sandbox clusters, not in production. The team needs enough Alcide knowledge to maintain the component until it is fully deprecated.

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3. IL-0189 A JVM service moved from EC2 to Kubernetes answered up to ten times slower because KIAM's 15-minute credentials made the AWS Java SDK fetch new credentials on every request

   Adevinta2019

   Symptoms

   After a Spring-based JVM microservice was deployed to Kubernetes and part of production traffic was routed to it, request latency there was up to 10 times higher than on EC2. Behind the NGINX ingress controller the backend took 100 to 200 ms to answer, where the EC2 instances took about 20 ms.

   High latency

   Trigger

   Moving the service onto the Kubernetes platform, where KIAM served IAM credentials to pods with its default 15-minute lifetime.

   Root cause

   Configuration change

   Component

   Credential broker for pods

   Contributing factor

   Unreviewed defaults

   Detection

   After part of production traffic was routed to the Kubernetes deployment, its request latency was seen to be up to 10 times higher than on EC2.

   Remediation

   • reconfigured KIAM to request IAM credentials with a longer expiration period

   Lessons

   KIAM's short credential lifetime for pods and the AWS Java SDK's eager refresh of any credential within 15 minutes of expiry are each reasonable, but together they force a metadata round trip on every request. When latency rises after a move to Kubernetes, the cause is often the interaction of components that never ran together before rather than Kubernetes itself. Here a packet capture from inside the container found what latency metrics and DNS tests had not.

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4. IL-0008 An unresponsive OPA validating webhook crash-looped the API server during a GKE master upgrade, and node auto-repair then recreated every node

   Jetstack2019

   Symptoms

   Jetstack was upgrading the master of a development cluster that many teams use to test their apps during the working day, a regional Google Kubernetes Engine (GKE) cluster in europe-west1. The upgrade ran through Jetstack's GKE Terraform pipeline and did not finish before the 20-minute Terraform timeout, while the GKE console still showed the cluster as upgrading.

   Upgrade stallControl plane unresponsiveNode recreation loopService outage

   Trigger

   A planned master upgrade of the shared development cluster. The same upgrade had been done on another pre-production environment earlier that day, and no API downtime was expected.

   Root cause

   Configuration change

   Component

   Admission webhookGKE control planeKubernetes API serverkubelet

   Contributing factor

   Excessive blast radiusNo health probesMonitoring blind spotAutomation amplification

   Detection

   The first sign was the master upgrade missing the 20-minute Terraform timeout; re-running the pipeline returned the kube-apiserver unhealthy error. The cause was identified with the help of Google Support.

   Remediation

   • Deleted the OPA ValidatingAdmissionWebhook resource during a window of API server access

   Action items

   • Limit the OPA webhook to the namespaces where the policy applies and development teams have access
   • Enable the webhook only for Ingress and Service resources, the only resources the policy validates
   • Add a liveness probe so OPA is restarted when it stops responding, and update the OPA documentation
   • Follow the open upstream Kubernetes issue about this behaviour

   Lessons

   With alerting on API server response times, the team might have seen CREATE and UPDATE requests slow down across the board as soon as the OPA-backed webhook was first deployed. Every workload needs probes: OPA looked so simple to deploy that the team skipped the Helm chart, which adds a livenessProbe for the admission controller containers among other adjustments to the tutorial configuration. Others had hit the same problem, and an upstream issue to improve it was still open.

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5. IL-0004 A new default pod priority let a new Cortex cluster preempt every production ingester in a cascade, taking Grafana Cloud Hosted Prometheus down

   Grafana Labs2019

   Symptoms

   On Friday 19 July 2019 the Grafana Cloud Hosted Prometheus service, which is built on the Cortex project, was down for 26 minutes. New error-budget-based Prometheus alerts paged the on-call engineer within 4 minutes of the start.

   Pod evictionHigh error rateService outageOOMKilled

   Trigger

   An engineer created a new dedicated Cortex cluster for a large customer. Its configuration did not include the new pod priorities, so all its pods got the default medium priority, and the Kubernetes cluster did not have enough free resources to fit it.

   Root cause

   Configuration change

   Component

   Pod priority and preemption

   Contributing factor

   Partial rolloutAutomation amplificationMissed in reviewNo headroomRetry storm

   Detection

   New error-budget-based Prometheus alerts paged the on-call engineer within 4 minutes of the start of the outage.

   Remediation

   • Scaled up the underlying Kubernetes cluster to fit both the new and the production Cortex clusters
   • Diagnosed and fixed the out-of-memory errors in the authenticating reverse proxies in front of Cortex

   Action items

   • Give the production ingesters the high priority class, which should have been done before medium became the default
   • Have more people review changes to configuration that is global to the cluster
   • Require a design document for every configuration change outside a namespace
   • Automate the sizing of the frontend authenticating reverse proxy so it does not run out of memory under overload
   • Investigate the default backoff and scaling behaviour of Prometheus to prevent a stampeding herd of retries

   Lessons

   Medium should not have become the default priority until the production ingesters had the high priority, and that designation should have reached production sooner. The change was considered too minor for a design document and was only discussed in a GitHub issue; cluster-global configuration needs more scrutiny. On the positive side, once Cortex had enough capacity it recovered by itself, and Grafana Loki helped confirm that the ingesters exited gracefully.

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