Cases2 cases
1 to 2 of 2
- Symptoms
From 7:30 AM PST on 7 December 2021, AWS services in us-east-1 that communicate between AWS's internal network and its main network saw rising latency and errors. The AWS operations teams lost real-time monitoring data at once, and the first thing found in the logs was elevated internal DNS errors.
- Trigger
At 7:30 AM PST an automated activity that scales the capacity of one AWS service hosted in the main AWS network triggered unexpected behaviour from a large number of clients inside the internal network.
- Root cause
- Component
- Contributing factor
- Detection
The congestion immediately cut off real-time monitoring data for the AWS operations teams, who turned to logs and first identified elevated internal DNS errors.
- Remediation
- Moved internal DNS traffic away from the congested network paths
- Isolated the top sources of traffic onto dedicated network devices
- Disabled some heavy network traffic services, including EventBridge event delivery
- Brought additional networking capacity online
- Disabled the automated scaling activities that triggered the event
- Action items
- Keep the triggering scaling activities off until all remediations are deployed
- Fix the latent issue that kept networking clients from backing off
- Deploy network configuration that protects the affected networking devices in a similar congestion event
- Keep API Gateway servers healthy when the internal network is unavailable and speed up their recycling
- Release a new Service Health Dashboard that makes service impact easier to understand
- Run the support system actively across multiple AWS regions
IL-0222Google Cloud US regions had heavy packet loss and some went unreachable after the network control plane was descheduledGoogle Cloud2019- Symptoms
On Sunday 2 June 2019, with user impact beginning between 11:47 and 11:49 US/Pacific, Google Cloud projects in several US regions saw elevated packet loss from network congestion, and some regions became unreachable. Customers saw higher latency, intermittent errors and lost connectivity to instances in us-central1, us-east1, us-east4, us-west2, northamerica-northeast1 and southamerica-east1, while us-west1, Europe and Asia had no regional congestion.
- Trigger
At 11:45 US/Pacific a relatively rare type of datacenter maintenance event started in one physical location, and the automation that runs it descheduled logical clusters that also held network control plane jobs in other physical locations.
- Root cause
- Component
- Contributing factor
- Detection
Google engineers were alerted to the failure two minutes after it began and started the incident process used for the most serious production incidents. The first customer notice appeared on the status page at 12:53 US/Pacific.
- Remediation
- Lowered the priority of less critical network traffic classes to reduce congestion
- Halted the datacenter automation software responsible for the maintenance event
- Rescheduled the network control plane and its supporting infrastructure in each location
- Rebuilt and redistributed the lost network control plane configuration, rolling it out from 14:03
- Directed service traffic away from the affected regions
- Moved the Cloud VPN control plane in three regions out of its fail-safe state
- Action items
- Keep the maintenance automation off until safeguards stop it descheduling jobs in several physical locations at once
- Harden the cluster management software to reject such requests whatever their origin
- Reconfigure the network control plane to reject maintenance requests of the type involved
- Make the network control plane in each location persist its configuration
- Let the network stay in fail static mode longer when the control plane is lost
- Review, update and test emergency response tooling and procedures, including customer communication tooling, for such network failures
- Extend continuous disaster recovery testing to this and similarly catastrophic failures
These 2 cases involve Backbone network (WAN) and BGP routing. 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 cause1
Software defect2 cases
- Component
- Contributing factor
- Organisation