Cases3 cases

1 to 3 of 3

1. IL-0155 Some DOKS clusters in NYC1 saw intermittent DNS timeouts and NodeNotReady events because CoreDNS ran on shared-CPU Droplet worker nodes

   DigitalOcean2026

   Symptoms

   From 20:31 UTC on July 9, 2026, DigitalOcean reported a problem with Kubernetes deployments in its NYC1 region. Application workloads could see intermittent DNS failures and NodeNotReady events.

   DNS resolution failuresIntermittent timeoutsNode NotReady

   Root cause

   Capacity exhaustion

   Component

   CoreDNSNode pool

   Contributing factor

   Unknown limit

   Lessons

   Cluster DNS is sensitive to latency, and CoreDNS on shared-CPU nodes can time out intermittently. DigitalOcean's advice is to place CoreDNS on dedicated-CPU node pools and to run enough CoreDNS replicas.

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2. IL-0161 A faulty earlier API update made new LKE cluster provisioning in Toronto time out for three days, leaving clusters with no node pools or the wrong number of nodes

   Linode2024

   Symptoms

   At about 14:05 UTC on 22 April 2024, Linode's team noticed that new LKE clusters were failing to provision in the Toronto data center.

   Cluster or node provisioning stallIntermittent timeouts

   Trigger

   A previous update to the API did not work as intended and caused timeouts when new LKE clusters were provisioned.

   Root cause

   Software defect

   Component

   Node pool

   Contributing factor

   –

   Detection

   Linode's team noticed new LKE clusters failing to provision in the Toronto data center at about 14:05 UTC on 22 April 2024.

   Remediation

   • disabled the affected section of Toronto infrastructure from provisioning new LKE clusters
   • implemented a fix for the faulty API update
   • put the disabled infrastructure back into use after the fix

   Lessons

   The fault was in an earlier API change, not in the infrastructure that showed it, but most failures concentrated on one backend resource in one data center. Taking that resource out of provisioning limited the impact while the root cause was found, which took three days.

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3. IL-0190 Cortex distributors kept a stuck connection to a dead etcd leader after a Kubernetes upgrade terminated its node, failing writes to Hosted Prometheus for 12 minutes

   Grafana Labs2020

   Symptoms

   About a minute after the etcd leader changed, two replicas of the Cortex distributor started logging "context deadline exceeded" when they tried to read keys from etcd. Writes from some customers that landed on those two replicas failed, while the other distributor replicas kept working, so the service saw an error rate of about 20% on writes to the London region of Hosted Prometheus.

   High error rateIntermittent timeouts

   Trigger

   A scheduled Kubernetes version upgrade abruptly terminated the node that ran the etcd leader at 11:19:00 UTC.

   Root cause

   Software defect

   Component

   etcdNode pool

   Contributing factor

   Unreviewed defaultsNo safeguard on destructive change

   Detection

   An SLO-based alert paged the on-call engineer at 11:31, 11 minutes after the errors started. At a 20% error rate the monthly SLA would have taken about 18 hours to breach.

   Remediation

   • Restarted the two affected Cortex distributor replicas at 11:32, which stopped the errors

   Action items

   • Enable gRPC keepalive probes in the Cortex etcd client (DialKeepAliveTime 10s, DialKeepAliveTimeout, PermitWithoutStream)
   • Make the Kubernetes upgrade process terminate pods and machines gracefully, including the etcd pods managed by the etcd operator

   Lessons

   When a node dies abruptly, clients holding TCP connections to it are not told; without keepalive probes an etcd client can keep sending requests into a dead connection long after a new leader exists. A failover that works on the server side still needs clients that detect the dead peer. Node replacement during cluster upgrades should drain pods gracefully, including pods owned by operators that the upgrade scripts do not know about, and should give instances enough time to shut down.

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