Cases21 cases

9 to 13 of 21

1. IL-0404 All BSEE SaaS customer pods on EKS crash-looped after Karpenter moved nodes to Bottlerocket v1.26.0, which broke Java

   PortSwigger2024

   Symptoms

   On 24 October 2024 every BSEE SaaS customer instance showed the Environment Unavailable message, and the SaaS Uptime Over Time metric dropped sharply at 04:45. The Technology Team learned of the outage when the Growth team posted about it at 08:07 and a member of the Product team told the Technology Team verbally at 08:15.

   Container crash loopService outage

   Trigger

   AWS made Bottlerocket v1.26.0 the latest Bottlerocket AMI in eu-west-1 between 02:00 and 04:30, and at 04:00 Karpenter saw the new version and started replacing the EC2 nodes of the production EKS cluster with it.

   Root cause

   Breaking change in an upgrade

   Component

   Node operating system imageKarpenter

   Contributing factor

   Unpinned version

   Detection

   The Growth team reported the outage in the BSEE cloud onboarding issues channel at 08:07, and a member of the Product team told the Technology Team verbally at 08:15. The SaaS Uptime Over Time metric had already dropped at 04:45.

   Remediation

   • Reverted all EC2 instances in the SaaS production account to Bottlerocket v1.25.0
   • Deployed Bottlerocket 1.25.0 across all EKS clusters and rolled out new EKS nodes

   Action items

   • Change the Karpenter resources to deploy a specific versioned Bottlerocket AMI instead of the latest released AMI
   • Add the Bottlerocket release ATOM feed to an internal tooling release dashboard
   • Set up a public status page to communicate with customers

   View case
2. IL-0232 Calico pods in the codfw WikiKube cluster hit their resource limits and crash-looped, taking nodes out one by one

   Wikimedia Foundation2024

   Symptoms

   At 05:01 UTC on 9 October 2024 a page fired for GatewayBackendErrorsHigh, elevated 5xx errors from page-analytics_cluster in codfw, followed by a growing number of KubernetesCalicoDown alerts for WikiKube nodes not running the calico-node pod and by MediaWikiMemcachedHighErrorRate. For about an hour uncached MediaWiki requests, such as those of logged-in users, edits and API calls, saw high latency or errors.

   High error rateHigh latencyContainer crash loopProbe failuresControl plane lag

   Trigger

   An operator used the new mwscript-k8s utility to run a batch of video transcode maintenance, the TimedMediaHandler requeueTranscodes.php script. mwscript-k8s deploys a whole helm release for every script invocation, so the batch created close to 2k Calico NetworkPolicies along with many other resources over several hours.

   Root cause

   Capacity exhaustion

   Component

   CalicoHelmJobs and CronJobs

   Contributing factor

   Change with a delayed effectNo runbook

   Detection

   Automated monitoring detected the issue and paged the on-call SRE: GatewayBackendErrorsHigh at 05:01:36 UTC, 16 KubernetesCalicoDown alerts at 05:03:32 UTC and MediaWikiMemcachedHighErrorRate at 05:04:15 UTC.

   Remediation

   • Raised the resource limits of the Calico and Typha pods and applied the change with helmfile, which redeployed all Calico pods

   Action items

   • Stop mwscript-k8s from creating so many resources

   Lessons

   The incident came close to a full outage. Automated monitoring caught it and many responders found the cause, but end users were affected and responders were unsure whether they could switch over to eqiad. The problem was noticed just before the hand-off from Americas to EMEA SRE shifts, a period with a long-known lack of coverage, and it helped that the transcodes were not queued on a Friday evening in the US.

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3. IL-0110 A Grafana Agent pod's high memory use and crash-looping Hangfire pods drove a Kubernetes node into system OOM and NotReady, twice in one day

   DFDS2024

   Symptoms

   At 10:01 UTC on 2024-03-13 a Kubernetes node entered NotReady state, with CPU requests at 78% and memory requests at 82%. An alert fired in Slack at 10:03 and was picked up at 10:05. An attempt to SSH into the node at 10:13 failed because it was unresponsive; it started responding again at 10:19.

   Node NotReadyContainer crash loopOOMKilledMonitoring outage

   Trigger

   Pods of a dev container that used Hangfire to trigger jobs failed with OOM and crash-looped on a node where a Grafana Agent pod was already using a lot of memory.

   Root cause

   Capacity exhaustion

   Component

   Telemetry agentContainer memory limitDatabase

   Contributing factor

   Excessive blast radiusNo resource requests or limitsHarmful manual actionMonitoring blind spot

   Detection

   A Slack alert fired two minutes after the node went NotReady and was picked up two minutes later; the second node's NotReady at 15:03 also raised a Slack alert.

   Remediation

   • marked the EC2 instance unhealthy so a new node started
   • cordoned and force-drained the NotReady node and terminated its EC2 instance
   • removed the new LimitRange from the Grafana Agent namespace and restarted the Grafana Agent pod
   • scaled the dev container to 0 replicas, after which EC2 network traffic returned to normal
   • after the second NotReady, scaled the dev container to 0 replicas again and added a new node
   • emailed the team that owns the dev container, which confirmed it was working on a fix

   Action items

   • Move grafana-agent to the monitoring node group
   • Add alerts for when bandwidth across the cluster reaches a certain threshold
   • Investigate whether memory limits can be set on the grafana-agent Helm chart
   • Investigate grafana-agent memory usage
   • Ask Grafana support whether grafana-agent should use a PVC
   • Consider pushing node logs to Loki with limited retention
   • Create a wiki page with common metrics and log queries to check when investigating issues with Kubernetes nodes

   Lessons

   Dev workloads mixed with production let one crash-looping dev container take down nodes that production also used, and a monitoring agent outside its dedicated node group added to the memory pressure. Scaling the suspect container back up before its owners had fixed it brought the failure back on the replacement node. The team also noted that action items from earlier post-mortems need follow-up, and that knowledge of useful CloudWatch metrics had not been shared, which made the diagnosis harder.

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4. IL-0202 A burst of queries and database writes exhausted connection pools and memory on Honeycomb's ingest hosts, and Kubernetes crash-loop back-off kept failed hosts offline so ingest capacity stayed too low to recover

   Honeycomb2023sev1

   Symptoms

   Standard alerting paged Honeycomb's on-call engineers about the performance and stability of event ingestion, and the automated load-shedding mechanisms tripped and sent further notifications. The status page described a higher than normal error rate and response time on the ingestion service.

   High error rateHigh latencyContainer crash loopService outageDatabase overload

   Trigger

   An abnormally large number of queries arrived from many separate connections within a few minutes.

   Root cause

   Capacity exhaustion

   Component

   DatabaseIn-memory cache

   Contributing factor

   Retry stormAutomation amplification

   Detection

   Standard alerting notified the on-call engineers about ingestion performance and stability, and the automated load-shedding mechanisms added notifications when they tripped. The first status post, about alerts on a higher than normal error rate and response time, went up at 18:28 PST (02:28 UTC), 13 minutes after the 02:15 UTC start.

   Remediation

   • Scaled the ingest fleet up manually and aggressively
   • Cut off most ingest for a few minutes so the ingest hosts could come back with enough capacity
   • Temporarily lowered the rate limits for the most aggressive traffic sources until their traffic subsided

   Action items

   • Keep the ingest fleet scaled up to prevent a repeat while longer-term fixes are worked on
   • Decide on the projects that will address these failure paths

   Lessons

   Load shedding and auto-scaling were in place, yet a burst that arrived faster than the cache could spread its writes still took the ingest hosts down. During recovery, Kubernetes' crash loop back-off worked against the operators: the hosts that had failed stayed offline while the fleet needed every host. Clients that retry whole OTel batches after a partial drop can multiply traffic many times over, so per-source rate limits were what finally stabilised ingest.

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5. IL-0437 Old pods from an unfinished Argo Rollouts canary could not start with a Helm-updated ConfigMap and died in a cascade

   Gunosy2023

   Symptoms

   During a traffic surge from a breaking news alert, pods of a Gunosy service on Kubernetes could not start because the containers could not read their settings from the ConfigMap. The pods that kept running took the extra load and were restarted, failed to start again, and pod after pod died.

   Container crash loop

   Trigger

   A breaking news alert increased traffic and pods were scaled out automatically while a release that removed an old database's settings from the ConfigMap had been rolled out to only one canary pod.

   Root cause

   Faulty deployment

   Component

   ConfigMaps and SecretsHelmProgressive delivery controller

   Contributing factor

   Partial rolloutAutomation amplification

   Action items

   • Configure Argo Rollouts to roll out automatically, with setWeight 1, a one-hour pause and then setWeight 100
   • Add the "helm.sh/resource-policy": keep annotation so Helm keeps past versions of the ConfigMap
   • Build and use a Helm plugin, helm-clear, that keeps only the last few ConfigMap versions by the revision number in their names, set to keep 5 in CD

   Lessons

   Gunosy holds that a review that only resolves to be careful next time would soon be followed by the same failure, because human attention cannot be relied on, so each incident gets a permanent fix built into the system. Keeping past ConfigMap versions also made it possible to roll back quickly without going through CI/CD, which a ConfigMap change had previously prevented.

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