Cases12 cases

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1. IL-0179 With DEBUG logging and synchronous log output, a high-traffic service filled the 64 KB stdout pipe, so request threads blocked in write() while holding database connections and HikariCP ran dry, failing requests in 30-second bursts

   MUSINSA2026

   Symptoms

   The on-call engineer for a high-traffic service was alerted that requests were failing in large batches every 30 seconds.

   High error rateIntermittent timeoutsConnection pool exhaustion

   Trigger

   DEBUG level logging was on in production when traffic surged, raising log volume to about 100 times normal while the service logged synchronously.

   Root cause

   Configuration change

   Component

   Application logging libraryContainer runtimeTelemetry agentDatabase

   Contributing factor

   Unverified assumptionExcessive blast radius

   Detection

   The on-call engineer was alerted that requests were failing in large batches every 30 seconds.

   Action items

   • Replace synchronous logging with TraceAwareAsyncAppender, which captures trace_id and span_id on the calling thread and drops logs instead of blocking when the queue is full (neverBlock=true)
   • Keep the amount of log output at a sustainable level, since an asynchronous queue still fills under sustained overload

   Lessons

   Removing AsyncAppender to keep trace IDs also removed the protection that kept request threads away from stdout back-pressure. A company-wide standard applies the same side effect to dozens of services, so check what a standard rests on and what working behaviour it takes away. ThreadLocal context does not cross into an asynchronous worker, but capturing it on the calling thread before handing the event off keeps both the IDs and the asynchronous output. Under extreme load, dropping log lines is preferable to stopping request handling.

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2. IL-0063 VPN outage after recreating a Redis StatefulSet restarted the whole Redis cluster without readiness checks

   AdGuard VPN2025

   Symptoms

   The day began with an alert that several instances of the Redis cluster were running out of disk space. That part was fixed quickly. The outage came an hour later: right after the Redis StatefulSet was deleted and recreated at 8:10 UTC, Kubernetes restarted every Redis pod within about five minutes, and problems started to appear.

   Service outageOOMKilledProbe failuresHigh latency

   Trigger

   To make Git match the volumes that had been resized by hand, the Redis StatefulSet was deleted with orphan (non-cascading) deletion and recreated with the new storage template; Kubernetes reconciled the new spec by restarting the entire Redis cluster.

   Root cause

   Configuration change

   Component

   Persistent volumes and stateful setsIn-memory cacheContainer memory limit

   Contributing factor

   No health probesUnverified assumptionSingle point of failureRetry stormNo headroom

   Detection

   An alert about Redis instances running out of disk space started the work; the outage itself showed up as backend errors about Redis connections right after the StatefulSet was recreated.

   Remediation

   • made the Redis masters forget obsolete node identities, reset the affected replicas and rejoined them, then waited for replication to catch up
   • identified the component that was actually running out of memory, scaled the backend service and raised memory limits for that component
   • temporarily relaxed probes so backend instances took traffic immediately instead of flapping between ready and not ready
   • reverted the temporary workarounds at 10:00 UTC

   Action items

   • Add startup probes so a Redis pod is not marked ready until its dataset is loaded
   • Build an own control plane for Redis that handles restarted pods stuck to an old master address
   • Reduce dependence on the single Redis cluster: move some important data to other stores, such as a separate Redis cluster per server, and use Kafka for some backend components

   Lessons

   The disk resize was not the problem; the cleanup afterwards was. An immutable field pushes operators toward deleting and recreating the controller, and that can set off a full reconcile. Startup and readiness probes are what slow a rolling restart down to a safe pace; without them a distributed store restarts in the most fragile way. Recovery plans must expect a cluster to heal slowly, and dependent services need to degrade gracefully while it does.

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3. IL-0192 A Crossplane composition merge-policy change for a TLS policy update switched Kubernetes Services from LoadBalancer to ClusterIP and deleted the load balancers behind about 25% of Grafana Cloud services

   Grafana Labs2025

   Symptoms

   At 08:41 UTC on 18 February 2025, several Grafana Labs application teams noticed that some of their endpoints were no longer available. The investigation quickly found that the load balancers for those endpoints were gone.

   Service outageResources deleted

   Trigger

   A change to the merge policy of a Crossplane composition, made so that the default TLS policy of the load balancers could be overridden, was applied to development, staging and production at the same time.

   Root cause

   Configuration change

   Component

   Configuration templatingCloud load balancer

   Contributing factor

   Unverified assumptionNo staged rolloutExcessive blast radiusNo safeguard on destructive change

   Detection

   Application teams noticed at 08:41 UTC that some of their endpoints were no longer available.

   Remediation

   • rolled back the Crossplane composition change
   • recreated the affected Kubernetes Services so that Kubernetes recreated their load balancers

   Action items

   • Add a CI check that blocks a deployment to more than one wave, so any exception to the dev, staging, canary, production order is caught
   • Give higher priority to a more sophisticated wave design that was already under discussion
   • Enable deletion protection on the load balancers, one layer below Crossplane
   • Enable deletion protection on other critical cloud provider resources
   • Develop the Crossplane Managed Resources exporter for change validation and visibility, now in beta testing within Platform engineering; simulated against the change that caused this outage, it shows a clear diff
   • Complete and test support for reconfiguring the TLS policy so application teams can deploy it

   Lessons

   A change that looked small and low-risk had a side effect that only a full end-to-end test through Crossplane and the cloud provider's load balancer controller would have shown; seeing the intended override work was not that test. Staged rollout and blast-radius limits that exist only as process can be skipped, so Grafana Labs moved to enforce waves in CI and to add deletion protection on the load balancers themselves, beneath the Crossplane layer.

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4. IL-0473 Jenkins infrastructure went fully down after a pod IP range fix deleted every AKS node pool and could not recreate them

   Jenkins project2023

   Symptoms

   On 7 July 2023 from 11:05 to 15:25 UTC many public Jenkins infrastructure services were completely down, including get.jenkins.io, plugins.jenkins.io, accounts.jenkins.io, javadoc.jenkins.io and incrementals.jenkins.io, while ci.jenkins.io, issues.jenkins.io, repo.jenkins-ci.org and www.jenkins.io were partly or completely disrupted.

   Network unreachableResources deletedCluster or node provisioning stallService outage

   Trigger

   After the upgrade to Kubernetes 1.25 changed the range of the pods' originating IP and LDAP access was blocked, a fix (Azure PR 431) deployed at 10:55 UTC to set a proper set of pod IP ranges removed all node pools of the cluster.

   Root cause

   Configuration change

   Component

   Node poolCNI pluginCloud load balancer

   Contributing factor

   Unverified assumptionNo staged rolloutNo safeguard on destructive change

   Detection

   After the upgrade, at 10:30 UTC, the team noticed that services inside the cluster, such as accounts.jenkins.io, could not reach the LDAP service.

   Remediation

   • Created the cluster again from scratch with a fixed network setup
   • Set a custom pod CIDR in a range separate from the virtual network
   • Moved the services and their DNS records to new public IPs
   • Pushed a pull request that recorded the manual rebuild, including the IP setup, in code

   Action items

   • Protect the public IPs from deletion with a Management Lock
   • Keep the public IPs in a separate resource group and point the Kubernetes-managed load balancers to it with the service.beta.kubernetes.io/azure-load-balancer-resource-group annotation
   • Improve network diagrams and documentation so possible overlaps are visible when preparing operations
   • Avoid changing the configuration of all AKS node pools at once

   Lessons

   The team said that changing one node pool at a time would have shown the problem after the first pool and avoided a full outage, and that the public IPs should change as little as possible because users behind corporate firewalls with allow-lists depend on them. The team also noted that it could rebuild, in under 4 hours, the cluster that hosts almost all public services.

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5. IL-0231 Deleting EKS managed node groups also deleted Karpenter's instance profile, and every Stytch worker node shut down

   Stytch2023

   Symptoms

   On 23 February 2023 Stytch's EKS worker nodes went Ready:Unknown one after another, Karpenter failed to launch replacement nodes, and with fewer and fewer pods scheduled the Live Stytch API went down for 14 minutes, returning 5XX on every call.

   Node NotReadyScale-up failurePod evictionPods PendingService outage

   Trigger

   At 14:21 UTC Stytch landed a change to remove unused EKS managed node groups, because it had decided to run its data plane applications fully on nodes provisioned by Karpenter. Because Crossplane resources use an orphan deletion policy, engineers deleted the node groups in the AWS console, first in staging and then in production.

   Root cause

   Configuration change

   Component

   KarpenterNode poolConfiguration templating

   Contributing factor

   Unverified assumptionShared credentialChange with a delayed effectIgnored early signal

   Detection

   Low-urgency alerts that Karpenter could not find the instance profile fired in staging at 16:06 UTC and in production at 17:48 UTC but were not treated as an incident. The incident process started at 20:26 UTC when node launch failures spiked the Karpenter error rate, and Kubernetes monitoring alerts in production followed at 20:44 UTC. The support team flagged the outage at 21:14 UTC.

   Remediation

   • Reverted the node group deletion, which recreated the managed node groups
   • Manually scaled up one of the Live API node groups with more and much larger nodes and removed its taints
   • Removed node selectors from the applications one after another so their pods could be scheduled

   Action items

   • Treat Karpenter errors as high-urgency alerts that page the on-call engineer
   • Tune cluster alerting thresholds to send a high-urgency page earlier
   • Add alerts for nodes that stay NotReady or Unknown for long periods
   • Raise the thresholds of other deployment alerts, such as unschedulable pods and replicas not available
   • Give Karpenter its own IAM instance profile, separate from the one used by the node groups
   • Separate other AWS resources that were shared between uses, specifically IAM and security groups
   • Rework the EKS and Karpenter configuration so system instance profiles are unique, static per cluster and generated by Karpenter
   • Introduce a cloud visualization tool for engineers making infrastructure changes
   • Add live system and product metrics to the status page
   • Ask AWS to confirm the undocumented actions and side effects of deleting a node group
   • Correct the shared use of IAM roles and security groups across the infrastructure

   Lessons

   The IAM role for Karpenter's self-managed nodes should never have been the same as the one for the managed node groups; sharing it is what let the node group deletion break Karpenter, and the roles had been left combined for speed and simplicity when Karpenter was first set up. The hours-long delay between the configuration change and its effect made the incident hard to assess, and AWS confirmed that this delay is expected, so Stytch will allow for it in future IAM instance profile changes.

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