Cases3 cases

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1. IL-0285 Clever Cloud's Pulsar brokers stalled in a minor upgrade, then hypervisors overloaded and crashed with kernel panics

   Clever Cloud2024

   Symptoms

   On 2 August 2024, two minutes after Clever Cloud's data team started a minor rolling upgrade of its Apache Pulsar messaging cluster to release 3.3.1, monitoring showed connection problems with the messaging platform. Producing data into the event bus failed, the backlog grew while no new producers or consumers succeeded, and agents on hypervisors, log forwarders on load balancers and deployments were affected. At 10:20 CEST the Pulsar cluster was declared defective.

   Deploys failingSustained high node CPUMemory pressureNode kernel panicOOMKilledAutoscaler misbehaviourMonitoring outage

   Trigger

   At 10:06 CEST the data team began a minor rolling upgrade of Apache Pulsar to release 3.3.1 that also switched on a new balancer for bundle placement: the extensible load manager (loadManagerClassName=org.apache.pulsar.broker.loadbalance.extensions.ExtensibleLoadManagerImpl) with the TransferShedder load shedding strategy instead of the native OverloadShedder.

   Root cause

   Configuration change

   Component

   Message brokerTelemetry agentLinux kernelAutomated capacity manager

   Contributing factor

   No configuration testsMonitoring blind spotIneffective rollbackUnreviewed defaultsAutomation amplificationRetry stormCircular dependency

   Detection

   Monitoring showed connection issues to the messaging platform at 10:08 CEST, two minutes after the upgrade began, and engineers confirmed at 10:09 that producing data into the event bus failed. Monitoring did not catch the first broker's failure to create the system topic, because that broker stayed up.

   Remediation

   • Rolled back the new unload strategy while keeping Pulsar 3.3.1
   • Shut down the client proxies to release the brokers
   • Switched deployment notification events to RabbitMQ as a workaround
   • Stopped all brokers and started only one, which loaded the conflicting system topic so it could be deleted, then started all brokers
   • Restarted the messaging proxies, after which messages flowed again
   • Stopped the watchdog so it would not reload every failed component, and started components one by one
   • Disabled Metrics API ingestion to protect its storage cluster
   • Stopped the long-term storage for observability metrics (the Warp10/FoundationDB cluster) to free resources
   • Put all monitoring instances in all regions into maintenance so they stopped sending events to the orchestrator
   • Killed the overloaded small VMs one by one
   • Flagged 12 hypervisors to drain workload and shut down some load balancers to free CPU and memory
   • Cleaned zombie VMs to speed up recovery
   • Cleared the monitoring alert queue so queued events would not flood the orchestrator
   • Added parked hypervisors to EU-FR-1 to relieve the overloaded ones
   • Removed an overloaded RabbitMQ node from the cluster used by the orchestrator
   • Rolling-restarted every regional L7 load balancer and every L4 load balancer
   • Restarted all HV agents and the add-on provider APIs
   • Destroyed all dangling VMs stuck in the stopping state
   • Re-enabled Metrics API ingestion with a ramp-up QoS policy

   Action items

   • Track KPIs for Pulsar broker and cluster health, hypervisor load, I/O and kernel panic reboots, zombie VMs, RabbitMQ broker and cluster health and deployment queue consumption, each by time of event, detection, decision and resolution
   • Deal with too many monitoring alerts
   • Look at a backup bastion, because a regional bastion is vulnerable
   • Rework the control plane recovery process
   • Rework the correlation between monitoring and orchestration
   • Revisit fault domain separation against multi-tenancy
   • Rethink runtime images and the role of the hypervisor
   • Isolate waved release upgrades of Pulsar
   • Redesign runtime images with better hypervisor integration
   • Regionalise observability for redundancy
   • Set Vector's buffer.max_events and buffer.max_size for small VMs
   • Switch Vector's buffer.type from memory, the default, to disk
   • Change Vector's buffer.when_full from block, the default, to drop_newest
   • Tune journald verbosity and SystemMaxUse on small VMs
   • Add cgroups restrictions for better process control
   • Add I/O restrictions for the VM manager
   • Detect zombie VMs better

   Lessons

   The simulation process that validates non-minor releases was not applied to minor upgrades or to small configuration changes, and this one went straight to production. Running Clever Cloud on Clever Cloud turned into a chicken-and-egg situation: recovery needed the scheduler to carry out large actions while the control plane was itself slowed and the infrastructure had no free resources. Measuring each key indicator by time of event, detection, decision and resolution showed where the team had lacked visibility or reaction and challenged established rules.

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2. IL-0223 A connection surge congested the devices between AWS's internal and main networks in us-east-1, breaking EC2 APIs

   Amazon Web Services2021

   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.

   Control plane lagHigh latencyHigh error rateMonitoring outageDNS resolution failures

   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

   Software defect

   Component

   Transit gateway or network interconnectAutomated capacity manager

   Contributing factor

   Retry stormCircular dependency

   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

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3. IL-0220 An overloaded AWS Transit Gateway dropped packets on 4 January 2021, and Slack's web tier saturated and went down

   Slack2021

   Symptoms

   During the Americas' morning of 4 January 2021, an external monitoring service paged Slack because error rates were creeping up. While the investigation was starting, Slack's own dashboarding and alerting service became unavailable, so responders had to work without their usual dashboards and alerts.

   High error rateMonitoring outagePacket lossService outageScale-up failureFile descriptor exhaustionCloud API rate limit exhausted

   Trigger

   On the first working day after the holidays, Slack's traffic went from the quietest time of the year to one of its biggest days overnight, with cold client caches pulling more data than usual, and one of Slack's AWS Transit Gateways did not scale fast enough for it.

   Root cause

   Cloud provider outage

   Component

   Transit gateway or network interconnectAutomated capacity manager

   Contributing factor

   Circular dependencyAutomation amplification

   Detection

   An external monitoring service paged Slack when error rates started creeping up during the Americas' morning. AWS engineers were separately alerted to the packet drops by AWS's internal monitoring.

   Remediation

   • Disabled automated downscaling of the web tier to keep serving capacity and allow investigation
   • Cleared up the broken, partly provisioned instances that filled the autoscaling groups
   • Repaired provision-service so new web tier instances could be provisioned and enter service
   • AWS engineers increased the Transit Gateway capacity manually across all Availability Zones

   Action items

   • AWS reviews its Transit Gateway scaling algorithms for large packet-per-second increases
   • Request a preemptive upscaling of the Transit Gateways at the end of the next holiday season
   • Run the dashboard service instances in the same VPC as their database to remove the Transit Gateway dependency
   • Load test provision-service regularly
   • Reevaluate health-checking and autoscaling configurations so they cannot overload provision-service again

   Lessons

   Monitoring has to stay as independent as possible of the infrastructure it watches, or it fails when it is needed most. Here the dashboard and alerting services failed because they ran in a different VPC from their databases and so depended on the Transit Gateways. provision-service had been load tested before, but this event exceeded the earlier scale-ups.

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