Cases10 cases

1 to 5 of 10

1. IL-0150 A latent race condition in DynamoDB's DNS automation left an empty DNS record for dynamodb.us-east-1.amazonaws.com, and the DynamoDB and EC2 launch failures that followed caused EKS, ECS and Fargate container launch failures and cluster scaling delays in us-east-1

   Amazon Web Services2025

   Symptoms

   At 11:48 PM PDT on 19 October 2025, every system that reached DynamoDB in us-east-1 through the public regional endpoint started getting DNS failures and could not connect. This included customer traffic and internal AWS services that depend on DynamoDB. DynamoDB global table replicas in other regions still answered but fell behind in replication to and from us-east-1.

   DNS resolution failuresHigh error rateScale-up failureIntermittent connection failuresHigh latency

   Trigger

   One DNS Enactor, slowed by unusually high retry delays, applied a much older DNS plan to the regional DynamoDB endpoint just as another Enactor that had applied the newest plan ran its clean-up, which deleted that older plan and with it every IP address of the endpoint.

   Root cause

   Software defect

   Component

   Authoritative DNS servers and recordsDatabaseCloud load balancer

   Contributing factor

   Automation amplificationRetry stormNo runbook

   Detection

   DNS failures to DynamoDB began immediately at 11:48 PM PDT and the engineering teams of affected AWS services were engaged at once; by 12:38 AM they had identified DynamoDB's DNS state as the source. The later NLB health check problem was detected by monitoring at 6:52 AM.

   Remediation

   • applied temporary mitigations by 1:15 AM that let some internal services reach DynamoDB and repaired key internal tooling
   • restored all DynamoDB DNS information by 2:25 AM through manual operator intervention
   • throttled incoming work and selectively restarted DWFM hosts from 4:14 AM so droplet leases could be re-established
   • reduced the load on Network Manager to bring network configuration propagation times back to normal by 10:36 AM
   • disabled automatic health check failover for NLB at 9:36 AM, and re-enabled it at 2:09 PM after EC2 recovered
   • relaxed the EC2 request throttles from 11:23 AM until all EC2 APIs and launches were normal at 1:50 PM

   Action items

   • Disable the DynamoDB DNS Planner and DNS Enactor automation worldwide
   • Fix the race condition and add protections against applying incorrect DNS plans before re-enabling the DNS automation
   • Add a velocity control to NLB that limits how much capacity a single load balancer can remove when health check failures cause availability zone failover
   • Build an additional EC2 test suite that exercises the DWFM recovery workflow at scale
   • Improve throttling in EC2 data propagation systems so incoming work is rate limited by the size of the waiting queue

   Lessons

   A single DNS record that automation can empty is enough to take a widely used regional endpoint off the network, and every service built on it fails in turn. A check made once at the start of a long operation can be stale by the time the operation writes its result. Recovery of the dependency is not recovery of the dependents: systems that lost state during the outage, such as EC2's droplet leases and network propagation backlog, can collapse under their own catch-up work, and container services that rely on new instance launches keep failing to launch and scale until that work is done.

   View case
2. IL-0247 One in a million search requests took 100 times longer on Pinterest's Manas leaf nodes after moving to Kubernetes

   Pinterest2025

   Symptoms

   During performance testing of Pinterest's search system Manas on its new Kubernetes platform, a small but persistent share of search requests timed out. About one request in a million took 100 times longer than usual.

   High latencyIntermittent timeouts

   Root cause

   Software defect

   Component

   Telemetry agentLinux kernel

   Contributing factor

   Unreviewed defaults

   Detection

   Performance testing with traffic sent to a test cluster showed a small but persistent percentage of requests timing out.

   Remediation

   • Disabled cAdvisor's working set size estimation on all PinCompute nodes

   Lessons

   CPU shielding does not fully isolate a process from its neighbours. Showing early that the node image was not the cause narrowed the search and avoided dead ends. Simple blackbox debugging, breaking things until the system stops working, works as a way of bisecting the problem.

   View case
3. IL-0081 API requests timed out during deployment rollouts because the ingress-nginx enable-serial-reloads option held back endpoint updates while a long NGINX reload was running

   Cresta2025

   Symptoms

   During a deployment, traffic into the Kubernetes cluster started hitting dead ends: some API requests timed out and requests were slow and disrupted while the rollout ran.

   Intermittent timeoutsStale endpoint routingHigh latency

   Trigger

   A deployment rollout changed backend endpoints while a long-running NGINX full reload was in progress, with the enable-serial-reloads option enabled on the ingress-nginx controller.

   Root cause

   Software defect

   Component

   Ingress controller

   Contributing factor

   –

   Remediation

   • restarted the NGINX Ingress controller as an attempt to resolve the problem

   Action items

   • Open an issue in kubernetes/ingress-nginx describing how enable-serial-reloads blocks dynamic endpoint updates

   Lessons

   A flag meant only to serialise full reloads also delayed endpoint updates, which opened a window during rollouts in which the ingress routed to pods that no longer existed. Options that change how the ingress controller applies configuration need to be checked against what happens to endpoint updates during a long reload.

   View case
4. IL-0495 HubSpot's internal load balancers on Kubernetes were falsely marked unhealthy and the rest collapsed under the traffic

   HubSpot2024

   Symptoms

   Between 14:20 and 15:16 UTC on 27 August 2024, some HubSpot customers could not log in to their accounts, reach their content or use HubSpot tools. Requests were slow or failed because HubSpot's internal load balancers, which run on Kubernetes and spread traffic across the backend services, were overloaded.

   Probe failuresHigh latencyHigh error rate

   Trigger

   Routine operation of a critical component of HubSpot's traffic management system, from about 14:08 UTC, ran path handling updates in the load balancer stack, and an issue in that stack made those updates block health check responses.

   Root cause

   Software defect

   Component

   Ingress controllerLiveness and readiness probes

   Contributing factor

   Automation amplificationNo headroom

   Detection

   Monitoring detected widespread performance degradation across the platform at 14:23 UTC and the incident response team was mobilised. HubSpot says it had identified the issue internally by 14:20 UTC. The status page was not updated until 14:44 UTC, which left customers with outdated information.

   Remediation

   • Tried to increase the capacity of the remaining load balancer instances
   • Brought new load balancer instances online, which relieved the pressure and let traffic return to normal

   Action items

   • Change the health check configuration so health checks do not time out falsely
   • Redesign the health check system so health checks get priority and keep running during operations such as configuration updates
   • Increase the capacity of the load balancers for sudden traffic spikes
   • Change the load balancing architecture to detect traffic surges earlier and distribute load dynamically in real time
   • Update the status page automatically for large-scale outages
   • Integrate the monitoring systems more tightly with the communication tools
   • Expand load testing to simulate high-traffic scenarios
   • Introduce chaos engineering to test platform resilience regularly
   • Add traffic pattern metrics, including the ratio of current connections to the maximum allowed
   • Add auto-scaling that adjusts resource capacity to traffic patterns

   Lessons

   HubSpot concluded that earlier detection of the abnormal traffic surge could have prevented the cascading failure, and that health checks have to keep running during operations such as configuration updates so that working load balancers are not removed together. The late status page update caused confusion for customers.

   View case
5. IL-0141 gke-metadata-server versions 0.4.272 to 0.4.280 flooded Cloud Logging with "Unable to sync sandbox" debug logs on GKE clusters with Workload Identity, using up logging quota and adding billable usage

   Google Cloud2023

   Symptoms

   Google Kubernetes Engine (GKE) customers with Workload Identity enabled saw a high logging rate. Debug log lines containing the string "Unable to sync sandbox" were ingested into Cloud Logging, used up the Cloud Logging ingestion quota and, beyond the free monthly allotment, produced extra billable usage. Workload Identity is opt-in on GKE Standard and always enabled on GKE Autopilot.

   Log floodHigh latency

   Trigger

   GKE clusters ran gke-metadata-server versions 0.4.272 to 0.4.280, which contained an incorrect configuration that wrote "Unable to sync sandbox" debug logs at a high rate.

   Root cause

   Software defect

   Component

   Credential broker for pods

   Contributing factor

   –

   Detection

   The first status update was posted at 13:32 US/Pacific on 2023-11-02, and the updates told customers how to check a cluster from the version annotation on the gke-metadata-server DaemonSet.

   Remediation

   • rolled out a fix across the GKE fleet so the excess logs were no longer ingested into Cloud Logging
   • offered GKE Rapid channel customers a control plane upgrade to 1.28.2-gke.1157000 or above, or 1.27.7-gke.1038000 or above, as a workaround

   View case

By root cause1