Incident Library
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Cases4 cases

1 to 4 of 4

  1. Symptoms

    On 2025-03-12 from 10:58 UTC, alerts for high backend response times came in, and the MediaWiki deployments mw-api-int, mw-parsoid and mw-jobrunner, which serve MediaWiki for non-user-facing purposes, showed high latency and database errors. The External Storage cluster, whose hosts store the compressed text of wiki page revisions, had a sharp rise in load and connections. The same happened again on 2025-03-13 from 11:15 UTC.

    Trigger

    At 10:44 UTC on 12 March a Scap deployment of the PHP 8.1 rollout for mw-api-int, mw-parsoid and mw-jobrunner was run with the flag -Dbuild_mw_container_image:False; the rollout was deployed with Scap again at 11:15 UTC on 13 March.

    Root cause
    Component
    Contributing factor
    Detection

    Alerts for high backend response times started at 10:58 UTC on 12 March, 14 minutes after the Scap deployment; 2 on-call engineers were paged. The MediaWikiMemcachedHighErrorRate alert that pointed at the cause fired only briefly because its log pipeline was overloaded.

    Remediation
    • Deployed a patch to cirrus-streaming-updater that reduced SUP parallelism
    • Reduced the concurrency of the categoryMembershipChange job in changeprop-jobqueue
    • On 12 March, reverted 1126607 and 1126650 and re-ran Scap
    • On 13 March, rolling-restarted changeprop-jobqueue
    • Rolling-restarted mw-api-int
    • Disabled the categorymembership job in changeprop-jobqueue
    • Reverted 1127476 and 1127478
    • Redeployed mw-api-int to pick up the revert
    • Increased the number of mw-api-int replicas
    • Redeployed mw-jobrunner to pick up the revert
    • Redeployed mw-parsoid to pick up the revert
    Action items
    • Reduce the number of messages sent through channel:Memcached during failures
    • Add helm rollback functionality to Scap
    • Decide whether Scap should update helmfile-defaults when -Dbuild_mw_container_image:False is set
    • Consider removing envvars.inc from MediaWiki images
    • Consider "Why" dashboards that give an overview of a group of related components together with relevant links to follow
    • Coordinate incident responders better
    • Be able to work with MediaWiki developers during incidents
    Lessons

    The write-up puts the weight not on the technical root cause but on why the team could not see, even after the 12 March incident, that three MediaWiki deployments were running without Memcached. Alert dashboards showed what was happening, such as many busy PHP workers, but not why; dashboards linking components that affect each other, such as SQLBlobStore keys and External Storage, would have helped. The alert that pointed in the right direction did not stay firing and would probably have been lost among 78 others. The incident coordinator could not tell who was working on what or who had joined or left, the channels were noisy, the external impact was judged more critical than it was, and trace.wikimedia.org was not used although it might have helped.

  2. Symptoms

    Right after the primary datacenter was switched from EQIAD to CODFW at 14:00 UTC on 20 September 2023, on-wiki search on all Wikimedia wikis became delayed or unavailable for a subset of users. At 14:08 the alert "CirrusSearch codfw 95th percentile latency - more_like" fired and reached IRC and the Search Platform email list as "PROBLEM alert - graphite1005/CirrusSearch codfw 95th percentile latency - more_like is CRITICAL".

    Trigger

    At 14:00 UTC the primary datacenter was switched from EQIAD to CODFW. more_like queries that were expected to go to eqiad, the non-primary datacenter, went to codfw instead, apparently because RESTBase sent them as POST rather than GET.

    Root cause
    Component
    Contributing factor
    Detection

    Automated monitoring caught the problem, but not quickly enough to prevent user-facing impact: the Grafana alert "CirrusSearch codfw 95th percentile latency - more_like" went to IRC and the Search Platform email list at 14:08. No one was paged; SREs were already watching closely because of the datacenter switchover. At 14:14 Hashar pinged #wikimedia-search and engineers began troubleshooting.

    Remediation
    • Banned the overloaded node elastic2044 from the Elasticsearch cluster
    Action items
    • Work out which Elasticsearch steps are needed before a datacenter switchover
    • Update the Elasticsearch section of the datacenter switchover documentation
    • Review the suggested switchover improvements in T285347 and decide whether to implement them
    • Make the RESTBase /related/{article} endpoint send GET instead of POST so the CirrusSearch query cache stays warm in both datacenters
    • Review the shard balance of busy wikis, especially enwiki_content
    Lessons

    Monitoring caught the problem, but not quickly enough to prevent user-facing impact. The heightened attention during the switchover meant the impact was recognised immediately, and banning a single node was quick and easy. The mitigation was not guided by an existing runbook, and the shards on the overloaded host were not checked before it was banned.

  3. Symptoms

    On 15 February 2019 a slave node of the AWS ElastiCache Redis Cluster behind Apollo, Grab's driver-side state machine for transport bookings, failed and had to be replaced. For about one minute only roughly 1 in 21 calls to Apollo succeeded, a call failure rate above 95% against the Redis Cluster, and Grab rides were significantly down.

    Trigger

    A slave node of Apollo's Redis Cluster failed and needed to be replaced.

    Root cause
    Component
    Contributing factor
    Lessons

    Having several replicas did not protect Apollo, because the client side, not the Redis Cluster server, caused the failure. Grab suggests three ways to avoid it: a separate Redis Cluster client used only for pipelining with RouteByLatency set to true, so pipelined reads go through the master nodes when latency is under 1ms, watching master CPU because they take more load; checking the error of each command in a pipeline instead of failing the whole call, so successful queries are not affected; and changing the Go-Redis library so that the pipeline path reloads the nodes' state when an error happens, as defaultProcessor already does.

  4. Symptoms

    Reports came in of more WORKER_JOB_ERROR errors, which tell Transloadit there is a communication problem between its Uploaders, the machines that receive files and orchestrate Assemblies, and its Drones, the machines that run encoding tasks. Many Assemblies became much slower because retries with exponential back-off kicked in, and a few could not be replayed.

    Trigger

    A steep increase in HLS traffic, together with more Drones online processing the same volume faster, which put more load on the central Redis nodes.

    Root cause
    Component
    Contributing factor
    Detection

    Reports of an increased number of WORKER_JOB_ERROR errors.

    Remediation
    • Re-added lost messages and relaxed heartbeat monitoring as a stopgap
    • Upgraded Redis to the latest stable version
    • Doubled the Redis cluster to six nodes and then added three more, which made it worse
    • Brought the number of read replicas down to one, which cut traffic and failure rates
    • Capped how far Drones scale up in each region
    Action items
    • Add logging and alarms for approaching saturation
    • Find ways to decentralise the traffic between the Redis nodes and the Drones and Uploaders
    • Add sharding per Uploader on top of the sharding per region
    Lessons

    To handle more traffic Transloadit had to use fewer Redis nodes, not more: each added replica multiplied the replication traffic from the single leader that takes every write, so scaling up the number of nodes was the wrong call. Bandwidth had not been among the monitored Redis metrics.

Check your cluster for this

These 4 cases involve In-memory cache and CI system. 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.

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