Incident Library
Applied filters SymptomData lossFactorAutomation amplificationClear 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

Cases3 cases

1 to 3 of 3

  1. Symptoms

    On 7 August 2017, while checking the application after the maintenance that moved Mackerel from an on-premises data center to AWS, the team found that data updated during a specific time window was missing. Everything written to the PostgreSQL database between 14:30 and 15:30 JST was gone.

    Trigger

    One hour after the application was switched to the newly promoted primary db001, db001 lost network connectivity and the database failed over to the standby db002.

    Root cause
    Component
    Contributing factor
    Detection

    The team found the missing data while checking how the application behaved after the migration work.

    Remediation
    • Tried to restore the lost updates by hand from the table data left on db001 and gave up
    • Tried point-in-time recovery from the base backup and WAL and gave up
    • Built a new replica db003 with db002 as primary to restore redundancy
    • Kept db001 in maintenance state for investigation
    • Watched db002 for some time to confirm the problem did not recur, then completed the migration
    Action items
    • Change the PostgreSQL replica creation script to set recovery_target_timeline = 'latest' in recovery.conf by default
    • Add a check to a server configuration test tool such as Serverspec that recovery.conf contains recovery_target_timeline = 'latest'
    Lessons

    A setting needed only for a rare layout, such as a grandchild replica during a migration, was applied by hand through a script option and was forgotten. Because recovery_target_timeline = 'latest' is harmless on ordinary standbys too, Hatena now sets it by default whenever a replica is created. The staging rehearsal used the same layout and steps but had the setting right, so it could not catch the mistake. Hatena notes that a similar layout may be used again for a future PostgreSQL upgrade or a move to another region.

  2. Symptoms

    After an OpenStack host server went down and took one Elasticsearch node with it, the health check that the API servers run against Elasticsearch returned false, although the Head plugin showed the cluster status as green. The check stayed false after the node was brought back and the cluster was green again.

    Trigger

    An OpenStack host server went down, and one node of the Elasticsearch cluster went down with it.

    Root cause
    Component
    Contributing factor
    Detection

    The health check that the API servers run against Elasticsearch returned false while the Head plugin showed the cluster as green.

    Remediation
    • Migrated the Elasticsearch node's virtual server to another host after the failed host recovered
    • Started the node's Elasticsearch process and let it rejoin the cluster
    • Restarted all nodes in order from node 1, pausing at about the twentieth when the API slowed
    • Restarted all nodes again from node 1, which ended the API delays but left 12 shards unassigned
    • Tried to move an unassigned shard with the allocate command of _cluster/reroute, which failed
    • For index A, copied node 22's shard files to nodes 3 and 10 and set primary to true in node 22's state file
    • For index B, deleted the broken shard files on node 27, copied node 28's files to node 27 and other nodes and marked node 28 primary
    • For index C, copied shards 2 and 4 from nodes 27 and 25 to two other nodes each and marked the copies as not primary
    Action items
    • Upgrade Elasticsearch and stop running such an old version
    Lessons

    Automatic shard reallocation should have been turned off before restarting nodes. After each node restart, the next node should have been restarted only after reallocation had completely finished, not just after the log file looked fine.

  3. Symptoms

    From 12:47 AM PDT on 21 April 2011, a subset of Amazon EBS volumes in one Availability Zone of the US East Region could no longer serve reads or writes, and EC2 instances that tried to use them got stuck as well. AWS called these "stuck" volumes. EBS API calls across the whole US East Region also returned high error rates and latencies during two periods on the first day.

    Trigger

    During a routine network change to upgrade the capacity of the primary EBS network in one Availability Zone, traffic was to be shifted off one of the redundant routers. The shift was executed incorrectly and sent the traffic onto the lower-capacity replication network instead of the other primary router, which could not carry it.

    Root cause
    Component
    Contributing factor
    Remediation
    • Rolled back the incorrect traffic shift, which restored network connectivity
    • Disabled all new Create Volume requests in the affected Availability Zone at 2:40 AM PDT
    • Disabled all communication between the degraded EBS cluster and the EBS control plane from 8:20 AM PDT
    • Stopped EBS servers in the degraded cluster from futilely contacting other servers for free space
    • Changed the EBS control plane so new EBS-backed instance launches stopped failing
    • Moved spare server capacity physically from across the US East Region into the degraded cluster
    • Adjusted the negotiation throttles so the new servers could join without flooding the old ones
    • Built a separate EBS control plane partitioned to the affected zone and finer-grained throttles, then processed the backlog
    • Restored the remaining volumes from S3 snapshots taken early in the event
    • Restored volumes on failed machines that had no snapshot after forensic work
    • Intervened by hand on the RDS multi-AZ instances that did not fail over automatically
    Action items
    • Audit the change process and add automation to prevent the traffic shift mistake
    • Change capacity planning and alarming to keep the extra safety capacity needed for large recovery events
    • Change the retry logic in EBS nodes to back off harder and reconnect to previous replicas instead of searching for new nodes
    • Test and deploy the fix for the race condition that crashed EBS nodes
    • Fix the RDS bug that kept multi-AZ instances from failing over automatically
    • Improve the EBS control plane timeout logic to prevent thread exhaustion when one zone's cluster is slow
    • Make the EBS control plane aware of Availability Zones so it sheds load when over capacity
    • Move more EBS control plane functions into per-cluster services that run in the same zone as the cluster
    • Offer multiple Availability Zones to Amazon VPC customers
    • Provide better tools for building multi-AZ applications that survive the loss of a zone
    • Host free webinars and publish whitepapers on fault-tolerant architecture
    • Build the fine-grained control and throttling used in recovery into the EBS nodes and automate the recovery models
    • Look at changes that keep volumes working while a cluster is degraded, including the ability to take a snapshot of a stuck volume
    • Send more frequent and detailed customer updates and staff developer support more widely during events
    • Develop tools that show through the APIs whether instances are impaired
    Lessons

    AWS writes that with more spare capacity the cluster would have absorbed the re-mirroring requests without a storm, and that it now understands how much capacity large recovery events need. The event also showed that the EBS control plane let a failure in one Availability Zone affect the others, so more work is needed to make zones behave as if completely independent. AWS adds that some customers had critical components in a single zone, and that multi-AZ deployments need to become easier to design and run.

Check your cluster for this

These 3 cases involve Database and Cloud block storage. 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