Incident Library
Applied filters Componentconntrack tableSymptomHigh error rateFactorRetry stormClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases2 cases

1 to 2 of 2

  1. Symptoms

    From September 2021, each rollout of an update to Datadog's metrics query service, which serves real-time and historical metric data to the web frontend and to monitor evaluation, came with a rise in errors. Clients retried failed queries, so few errors reached users, but the retries slowed dashboards and monitors. The service's logs showed DNS errors stopping it from connecting to the data stores it depends on.

    Trigger

    Rollouts of the metrics query service, which delete the old pods. The client behaviour behind the failures came from an August 2021 rollout of the metrics query clients that applied round_robin as the new default gRPC load balancing policy.

    Root cause
    Component
    Contributing factor
    Detection

    Errors rose during rollouts of the metrics query service, and the service's logs showed DNS errors when connecting to its data stores.

    Remediation
    • Raised the memory of the node-local-dns pods from 64 MB to 256 MB, which stopped the OOM kills but not the DNS errors
    • Tested larger instance types and confirmed that scaling up the service's infrastructure resolved the errors
    • Removed the custom gRPC reconnect parameters from the clients to restore the defaults
    Action items
    • Contribute a change to Cilium that adds an unreachable route for a deleted pod's IP so clients get an ICMP error
    Lessons

    The errors looked like DNS but were not. ENA metrics and VPC Flow Logs gave the visibility into VPC connection tracking that host metrics did not, and Cilium, Kubernetes and AWS networking interact in ways that can make reverse path filtering drop packets it should allow. DNS propagation time depends on many settings. The causes were changes Datadog had made itself, to work around a dependency bug, to resolve earlier incidents and to override default reconnect parameters, which looked safe at the time and showed their effects much later, when the link was hard to see.

  2. Symptoms

    On 4 February 2019 at about 02:50 UTC, Elastic Cloud customers with deployments in AWS us-east-1 lost stable access to their Elasticsearch clusters, and an increase in HTTP 5xx errors showed on the load balancer. Deployments were partially or completely unavailable until 09:28 UTC, Kibana access was disrupted for most customers in the region, and the Elastic Cloud User Console timed out when customers tried to view their deployments.

    Trigger

    A routine patching procedure in AWS us-east-1 replaced the first and second members of the three-node ZooKeeper ensemble with patched hosts between 02:25 and 02:45 UTC, following the same documented process used in the other 12 regions.

    Root cause
    Component
    Contributing factor
    Detection

    An increase in HTTP 5xx errors on the load balancer was identified at 02:50 UTC, the time the ZooKeeper ensemble lost its leader.

    Remediation
    • Restarted internal services in sweeping restarts at 03:22 and 06:00 to reduce client connection problems
    • Isolated the ZooKeeper ensemble by cutting off client connections
    • Rolled back the remaining ensemble member after its host became unstable
    • Rolled back the second ensemble member after its host became unstable
    • Rebooted the ZooKeeper hosts made unresponsive by the runc CPU softlocks
    • Re-established ZooKeeper quorum by removing client load and operator debugging, then reintroduced client load gradually
    • Increased the initLimit setting of the ZooKeeper observer layer used by the proxies
    • Scaled the proxy fleet up and out to handle the increased traffic
    • Applied a runbook that restarted the internal proxying containers and Kibana instances and set sysctl limits
    Action items
    • Reduce the dataset size carried by the ZooKeeper ensembles by over 60%
    • Reduce the number of health checks and intervals needed before a healthy proxy node joins the load balancing layer
    • Stop counting ZooKeeper connectivity in the proxy health checks once a proxy has its configuration and routes
    • Canary the rewritten proxy v2 architecture, which decouples the proxy service from ZooKeeper state, in production regions
    • Improve visibility into ZooKeeper with better logging and metrics for the ZooKeeper processes, the JVM and the container and host systems
    • Make Kibana route discovery more resilient
    • Fix the Kibana issues that amplify internal HTTP requests during availability events
    • Fix the Kibana issues that leak connections
    • Make internal monitoring agents use backoff with jitter
    • Formalize a maintenance matrix with set timeframes per region, so failures of critical services fall in non-critical times
    • Give runbooks for coordination layer maintenance a better decision criteria matrix
    • Set up a feedback loop with support leadership for incident communications through support and the status page
    Lessons

    Service metrics that reported the ZooKeeper hosts healthy were not enough to show the state of individual hosts or of the ensemble, so they gave a false signal that maintenance could continue. Because the platform depended on the coordination layer, losing its quorum caused a major service disruption in which every Elasticsearch cluster in the region saw some failures, and fixes that worked one by one fell short at the scale of the failure.

Check your cluster for this

These 2 cases involve conntrack table and Linux kernel. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause2