Cases3 cases

1 to 3 of 3

1. IL-0102 CoreDNS pods on a production EKS cluster ran out of memory under a burst of new pods, endpoints and nodes, taking down the Buildkite web UI, APIs and job dispatch

   Buildkite2026

   Symptoms

   From 22:47 UTC on 25 August 2026 the Buildkite web interface, REST API, Agent API, job queue and notifications stopped working for every customer. No one could create a build from the UI or the REST API, job dispatch was delayed, and some builds that were already running when the outage began stayed stuck until the services recovered.

   Service outageDNS resolution failuresOOMKilledAutoscaler misbehaviour

   Trigger

   At 22:44 UTC an application deploy created a surge of new pods, which used up the free capacity on the existing nodes and made the EKS cluster scale out. Background worker pools with unusually high maximum replica counts were scaling out at the same time and kept asking for more pods while new nodes were still being provisioned. Together they produced an unusually high rate of change in applications, network endpoints and nodes, and with it a sudden rise in demand on CoreDNS.

   Root cause

   Capacity exhaustion

   Component

   CoreDNSContainer memory limitHorizontal pod autoscalerNode pool

   Contributing factor

   No headroomAutomation amplificationRetry stormMonitoring blind spot

   Detection

   The first status post, at 22:55 UTC, eight minutes after the outage began, said something had gone wrong, and at 23:05 UTC the status page said a sitewide outage was being investigated. CoreDNS query duration had been rising as the cluster grew, but a defect in a key monitoring query and too little monitoring of query volume meant this went unnoticed before the outage.

   Remediation

   • paused further application deploys
   • scaled CoreDNS from three to twelve pods
   • raised each CoreDNS pod's memory limit from 512 MiB to 2 GiB
   • expanded the system node pool that runs CoreDNS

   Action items

   • Increase immediate CoreDNS headroom: twelve pods instead of three, a 2 GiB memory limit instead of 512 MiB, and a larger system node pool
   • Enable EKS-managed CoreDNS autoscaling with a tested minimum replica count and enough capacity to spread the replicas across nodes and availability zones
   • Add direct alerts on CoreDNS query duration, query volume, goroutine growth, memory pressure, OOM restarts and available replicas, and track longer-term trends in capacity planning
   • Find other cluster-critical services that lack tested capacity, direct alerting, spread across failure domains, and either safe autoscaling or documented static headroom, and fix them

   Lessons

   A CoreDNS deployment sized once and left at a fixed size can carry a growing cluster for months and then fail on the first burst of churn it cannot absorb. When query processing slows, pending queries take up memory, the pods hit their limits and restart, and client retries keep the service down after the restart. Server-side DNS query duration and volume need their own alerts: here client-side latency was masked by unrelated application speed-ups, and a broken monitoring query hid the server-side trend. Maximum replica counts raised as a temporary measure remove the cap that normally stops runaway scaling when new nodes are slow to arrive.

   View case
2. 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 recordsApplication databaseCloud 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
3. IL-0001 Cluster-wide DNS outage after CoreDNS pods were OOM-killed again and again under a burst of DNS queries

   Zalando2019

   Symptoms

   Customers of the Zalando Fashion Store got a high rate of errors on all web product pages and outfit pages for more than an hour. The errors came from the main data aggregation layer service, which runs in one of Zalando's Kubernetes clusters.

   High error rateDNS resolution failuresOOMKilledMonitoring outage

   Trigger

   Calls from the aggregation layer to a single, not very important downstream service started timing out. The aggregation layer returned 404s for them, clients retried, and the resulting spike in requests became a spike in DNS queries to CoreDNS.

   Root cause

   Capacity exhaustion

   Component

   CoreDNSContainer memory limitClient-side DNS resolver and cache

   Contributing factor

   Unknown limitNo cachingRetry stormUnreviewed defaultsExcessive blast radiusMonitoring blind spot

   Detection

   The on-call engineer for the aggregation layer phoned the on-call Kubernetes engineer. Automatic paging did not happen because the cluster's monitoring and alerting ran inside the cluster and failed along with DNS. The Kubernetes engineer then saw that the CoreDNS pods were being OOM-killed.

   Remediation

   • Raised the CoreDNS memory requests and limits by hand from 100Mi to 2000Mi

   Action items

   • Introduce a more resilient DNS setup: CoreDNS fronted by dnsmasq on every node
   • Improve high-level alerting from outside the clusters, so that a cluster problem is known before or at the same time as applications are affected
   • Improve incident response processes and tooling so that any on-call engineer can escalate directly to other teams when automatic paging fails, for example through a chat bot

   Lessons

   The Kubernetes DNS setup was far from resilient enough: a single application could take down DNS for everything in the cluster. The blast radius of one application sending more DNS queries should be limited to one node at most, ideally to single pods. Known Kubernetes DNS problems, such as Linux kernel races in conntrack handling and the ndots 5 problem, were familiar to the team and partly mitigated, but their combined effect on the DNS infrastructure was worse than the team had understood. Monitoring that runs inside the cluster was not robust enough: when the cluster's DNS broke, it could not page anyone, and recovery took longer than it should have.

   View case

By root cause2