Cases19 cases

9 to 13 of 19

1. IL-0530 Virtual router controllers in us-central1 ran out of memory in a loop, cutting networking for new and migrated VMs

   Google Cloud2023

   Symptoms

   On 5 October 2023 in us-central1, newly created VMs waited a long time before their networking worked, and VMs that had been live migrated lost connectivity for a long time after the migration. Networking telemetry showed cross-region packet loss to and from us-central1 from 03:08 US/Pacific. Health check state of VMs reached load balancers late.

   Packet lossNetwork unreachableOOMKilledStale endpoint routingCluster or node provisioning stall

   Trigger

   A management plane behaviour change, meant to decouple the processing of API updates to Instance Groups and Network Endpoint Groups used as load balancer backends, was deployed in us-central1 after rolling out to several other regions without incident.

   Root cause

   Faulty deployment

   Component

   Network control plane (SDN)Cloud load balancer

   Contributing factor

   Excessive blast radiusNo alert on limit

   Detection

   Engineers were alerted to slowness in the virtual network control plane in us-central1 at 21:45 US/Pacific on 4 October, before the packet loss started, and to controller failures from memory exhaustion at 02:11 on 5 October. Networking telemetry showed cross-region packet loss from 03:08.

   Remediation

   • Increased the memory allocated to the virtual network router controllers
   • Rolled back the management plane change in us-central1
   • Restarted by hand the routers that were still not accepting updates

   Action items

   • Alert proactively on memory risks and unexpected memory increases
   • Refactor the deployment configuration so engineers can reallocate memory much faster
   • Re-evaluate existing practices and add safety mechanisms for API reconciliation
   • Make management plane changes more visible across teams so the changes can be correlated faster
   • Adjust the deployment footprint so a regional API change is less likely to exhaust memory across the region at once
   • Optimise memory use in the traffic routers and their controllers

   View case
2. IL-0019 An EKS Terraform module upgrade shrank node root disks from 100 GB to 20 GB and image pulls failed with no space left on device

   UK Ministry of Justice2023

   Symptoms

   At 13:42 the RootVolUtilisation-Critical alert fired in the high-priority alerts channel. At 14:03 a user reported image pull errors with the message "no space left on device".

   Node disk fullImage pull failuresPod evictionPods stuck in ContainerCreatingIP address exhaustion

   Trigger

   Upgrading the EKS Terraform module to version 18, which changed the node launch template, and draining workloads onto the new nodes it created.

   Root cause

   Configuration change

   Component

   Node root diskNode launch templateNode poolAWS VPC CNICoreDNS

   Contributing factor

   Missed in reviewNo configuration testsNo alert on limit

   Detection

   The RootVolUtilisation-Critical alert fired in the high-priority alerts channel at 13:42, and a user reported "no space left on device" image pull errors at 14:03.

   Remediation

   • Uncordoned the old default node group and drained the new nodes to move workloads back
   • Identified the launch template change that cut the root volume to 20 GB and applied a fix on the manager and live clusters
   • Drained the old node group onto the fixed nodes

   Action items

   • Update the runbook to compare launch template changes during an EKS module upgrade
   • Create a test setup that pulls images of different sizes, like live
   • Update the RootVolUtilisation alert runbook to check the disk space configuration
   • Scale CoreDNS dynamically based on the number of nodes
   • Investigate whether IPv6 can solve the IP prefix starvation problem
   • Add drift testing to identify when a terraform plan shows a change to the launch template
   • Set up logging for the CNI and ipamd logs and alerts on errors related to IP prefix starvation

   Lessons

   The write-up lists review actions rather than lessons. They aim at two gaps: the launch template changes brought by a module upgrade were not compared or drift-tested before rollout, and there were no CNI or ipamd logs or alerts to show the IP prefix starvation the team suspected during the drain.

   View case
3. IL-0043 Application logs missing in Kibana after a newer Fluent Bit version changed its chunk drop strategy

   UK Ministry of Justice2023

   Symptoms

   At 09:14 on 4 August 2023, users of the Cloud Platform reported in the #ask-cloud-platform Slack channel that Kibana was missing their application logs for long periods.

   Monitoring outage

   Trigger

   The newer Fluent Bit version in use had changed its chunk drop strategy; the fix that followed handled memory buffer overflow.

   Root cause

   Capacity exhaustion

   Component

   Telemetry agent

   Contributing factor

   No alert on limitMonitoring blind spot

   Detection

   Users reported long periods of missing logs in Kibana in the #ask-cloud-platform Slack channel at 09:14; the incident was declared at 10:09.

   Remediation

   • configured Fluent Bit to handle memory buffer overflow by writing buffered logs to the file system
   • made Fluent Bit flush logs in smaller chunks

   Action items

   • Push notifications from the logging clusters to #lower-priority-alerts (#4704)
   • Add an integration test that checks logs are being sent to the logging cluster

   View case
4. IL-0016 Prometheus on the live cluster ran out of memory and was OOMKilled, and the monitoring node it ran on went NotReady

   UK Ministry of Justice2023

   Symptoms

   At 14:05 on 25 July 2023, a high-priority PagerDuty alert from Pingdom reported that the "Prometheus - live healthcheck" was DOWN. Prometheus on the live cluster was unavailable, and the Cloud Platform lost its monitoring for a while.

   Monitoring outageOOMKilledNode NotReady

   Trigger

   The growing number of namespaces and Prometheus rules raised Prometheus' memory needs beyond what its node instance size could hold.

   Root cause

   Capacity exhaustion

   Component

   PrometheusNode poolContainer memory limit

   Contributing factor

   No alert on limit

   Detection

   A Pingdom health check on Prometheus failed and raised a high-priority PagerDuty alert.

   Remediation

   • drained the monitoring node, moving Prometheus to another monitoring node
   • changed the node instance size to r6i.4xlarge
   • raised the Prometheus memory limit to 100Gi
   • set the Prometheus container limits to 12 CPU cores and 110Gi of memory

   Action items

   • Add an alert on node memory usage and on a pod using up most of a node's memory (issue #4538)

   View case
5. IL-0500 UToronto JupyterHub logins and server starts returned 500 errors when the hub's sqlite database disk filled up

   2i2c2022

   Symptoms

   On 31 October 2022 at 6:27 PM Pacific time, users of the UToronto JupyterHub run by 2i2c could no longer log in or start their servers, and the hub answered with 500 errors. Users who were already logged in could keep using the hub.

   High error ratePersistent volume full

   Trigger

   The JupyterHub log file, written to the same 10G disk as the hub's sqlite database, grew until the disk was completely full.

   Root cause

   Capacity exhaustion

   Component

   DatabasePersistent volumes and stateful setsJupyterHub

   Contributing factor

   No alert on limit

   Detection

   A user emailed 2i2c support at 7:13 PM that users could not log in; the team acknowledged the issue at 8:33 PM. There was no alert for the problem.

   Remediation

   • Compressed the hub log file into /tmp from a shell in the hub pod, because it could not be compressed in place on the full disk
   • Copied the compressed log to a local machine so the hub pod could be restarted without losing it
   • Resized the hub database disk (the hub-db-dir PVC) from 10G to 60G
   • Restarted the hub pod, which came back with the larger disk and restored service

   Action items

   • Stop keeping hub logs on the same disk as the hub database
   • Add a Grafana graph of free space on the JupyterHub database disk
   • Alert on elevated error rates

   Lessons

   Kubernetes dynamic volume resizing let the hub database disk grow from 10G to 60G without much effort. The risk of keeping logs on the database disk had been identified during the earlier migration, but the team had no solid process for following it through, and because no alert existed the team had to wait for a person to report the outage.

   View case

By root cause6