Cases3 cases

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1. IL-0187 A brief Spring Cloud Config Server downtime failed every client application's liveness probe, because the actuator health check included the config server, and Kubernetes restarted the pods in a kill loop

   Yonghyun Kim2025

   Symptoms

   While the Spring Cloud Config Server was briefly down for an upgrade, every client application began to answer its liveness probe with a failure saying it could not reach the config server.

   Probe failuresContainer crash loopService outage

   Trigger

   A downtime upgrade of the Spring Cloud Config Server made it stop responding for a short time.

   Root cause

   Dependency failure

   Component

   Liveness and readiness probes

   Contributing factor

   Unreviewed defaultsAutomation amplificationExcessive blast radius

   Lessons

   A liveness probe that includes an external dependency turns a short outage of that dependency into a restart loop of every client. Keep external dependencies out of liveness checks and handle temporary problems with readiness probes. Libraries can add health indicators to Spring Boot's actuator health endpoint automatically, so check what the probe path actually reports. The author ran another Kubernetes environment for two years without liveness probes, relying on strict readiness probes and on the application terminating itself on unrecoverable faults.

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2. 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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3. 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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