Cases10 cases

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1. IL-0310 An Aurora PostgreSQL failover to an upsized reader reversed twice and backend writes failed in read-only transactions

   Hightouch2025

   Symptoms

   At 16:39 EDT on 23 October 2025, Hightouch triggered a failover of its Aurora PostgreSQL cluster in us-east-1 to a newly upsized reader. The AWS Console showed the usual parameter adjustments and instance restarts, but after the page refreshed the original writer was still the primary, and backend services could not run write queries although AWS showed the cluster as healthy.

   Failover failureWrites rejected

   Trigger

   A planned upsize of the Aurora cluster's instances, done without a maintenance window, after the AWS us-east-1 outage of 20 October had left an event backlog that strained the small Postgres instance. The manual failover to the upsized reader at 16:39 EDT started the failure.

   Root cause

   Software defect

   Component

   DatabaseDatabase failover manager

   Contributing factor

   Unrepresentative staging

   Detection

   The AWS Console showed after a refresh that the original writer was still primary, and backend application logs showed write errors on a read-only transaction. Per-instance query monitoring in Datadog and the RDS database logs showed the brief writer advertisement.

   Remediation

   • Restarted the backend services, which cleared the write errors after each failed failover
   • Scaled down every service that writes to the database
   • Triggered the failover again with no concurrent writes, which completed, and upsized the cluster in us-east-1

   Action items

   • Pause writers before any intentional failover, as written into the internal playbooks
   • Monitor for unexpected flips of the instance that advertises the writer role

   Lessons

   Hightouch's takeaways are that a migration can end in the desired state, the starting state or somewhere in between even with services one trusts, so traffic redirection and brief dependency outages should be planned for. The brief writer advertisement could only be found because queries to each instance were monitored in Datadog and the RDS database logs were available. Limiting how much any single component can affect the system helps both uptime and maintenance, and a staging load test, even of the exact procedure, did not reproduce the conditions that triggered the Aurora race condition.

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2. IL-0367 Azure Storage in Central US rejected VM disk I/O, taking down VMs and the SQL Database and Cosmos DB services on them

   Microsoft Azure2024

   Symptoms

   From 21:40 UTC on 18 July 2024, virtual machines in the Azure Central US region lost access to their disks, and the services running on those VMs failed. Azure SQL Database and SQL Managed Instance showed unhealthy nodes and login failures, Cosmos DB requests failed, and service management operations failed across many Azure services.

   Storage disconnected or stale mountsService outageHigh error rateFailover failureStale endpoint routing

   Trigger

   Routine changes to the VM host fleet led to a new allow list of VM host address ranges being generated and published to all Storage scale units in Central US. Recent network configuration changes had made some of the infrastructure file servers that hold the source data unreachable from the server generating the list, so the published list was incomplete.

   Root cause

   Configuration change

   Component

   Cloud block storageDatabaseDatabase failover manager

   Contributing factor

   Unsafe failure behaviourNo staged rolloutExcessive blast radiusMonitoring blind spot

   Detection

   Service monitoring detected the drop in VM availability at 22:06 UTC while the allow list update was being published. SQL monitoring detected unhealthy nodes and login failures within one minute of SQL becoming unavailable, and monitoring flagged the availability drop for Cosmos DB, SQL DB and SQL DB Managed Instance at 22:14 UTC.

   Remediation

   • Halted the allow list update workflow worldwide
   • Paused all deployments in the Central US region
   • Paused compute buildout deployments in all regions
   • Updated the configuration of all Storage scale units in Central US, restoring storage availability by 02:55 UTC
   • Started geo-failovers for SQL databases with automatic failover policies
   • Restarted SQL gateway nodes to refresh their caches and route connections to the right nodes
   • Forced completion of SQL failovers that had not completed
   • Failed over the Cosmos DB control plane and active-passive accounts with a write region in Central US
   • Cancelled customer-triggered graceful switch region operations that blocked Cosmos DB failovers
   • Removed locks on Cosmos DB service metadata to force-complete stuck failovers
   • Repaired impacted Cosmos DB partitions for single-region accounts
   • Repaired backend nodes and failed Cosmos DB accounts back to Central US, redoing failback where it failed

   Action items

   • Make the allow list generation workflow detect incomplete source information and halt
   • Alert on storage requests rejected by allow list checks
   • Deploy allow lists one Availability Zone and storage type at a time, over 24 hours
   • Add VM health checks and an automatic stop to the allow list deployment workflow
   • Reevaluate the policy for Microsoft-managed failover of SQL failover groups
   • Fix the Cosmos DB failback workflow that broke some MongoDB drivers for MongoDB API accounts
   • Fix Cosmos DB failback for accounts with private endpoints so it does not need redoing
   • Make the storage data-plane firewall reject invalid allow lists and keep the last-known-good state
   • Improve Azure NetApp Files monitors so impacting events are detected and classified in time
   • Monitor more Azure NetApp Files service metrics to correlate similar events faster
   • Make the SQL Service Fabric cluster location change notifications reliable under load
   • Make SQL geo-failover workflows more robust so they complete
   • Remove the issues that delayed 5% of Cosmos DB failovers
   • Migrate Azure DevOps customer metadata to the right geography
   • Decouple Azure NetApp Files regional reads and writes to keep this class of issue to one region
   • Evaluate caching to reduce Azure NetApp Files reliance on stored utilization data
   • Add automatic per-partition failover for Cosmos DB multi-region active-passive accounts
   • Build the Resilient Ephemeral OS disk improvement so VMs survive storage incidents better

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3. IL-0291 GitLab.com's redis-sidekiq Sentinel could not elect a primary after a GCP host error, so Sidekiq was down for 30 minutes

   GitLab2023

   Symptoms

   GitLab.com showed widespread, erratic behaviour and more 500 errors for about 30 minutes while its redis-sidekiq Redis was down. Alerts in the #production channel began with Redis client errors and spread to error SLO violations on several services, such as the Webservice and API load balancer and Puma.

   Failover failureHigh error rate

   Trigger

   The VM of the primary node, redis-sidekiq-03-db-gprd, failed on a GCP host error and was reset and moved to another node.

   Root cause

   Cloud provider outage

   Component

   In-memory cacheDatabase failover manager

   Contributing factor

   Single point of failureMonitoring blind spot

   Detection

   Several alerts in the #production channel, first Redis client errors and then error SLO violations on several services, such as the Webservice and API load balancer and Puma.

   Remediation

   • Restarted the failed Redis node so Sentinel had enough nodes to elect a primary

   Action items

   • Alert when the Sentinel service is down
   • Make merge requests robust to Redis Sidekiq outages

   Lessons

   An alert on a down Sentinel node would have kept enough nodes up to form a quorum when failover was needed, and could have avoided the incident entirely. Removing a noisy alert earlier may have let the down node go unnoticed.

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4. IL-0241 A database shard could not elect a new primary, and the Stripe API failed most requests in two periods on one day

   Stripe2019

   Symptoms

   On 10 July 2019 the Stripe API failed a substantial majority of requests twice, from 16:35 to 17:02 UTC and from 21:14 to 22:47 UTC. In the first period automated monitoring detected within a minute that a database cluster had failed to elect a new primary.

   High error rateFailover failureWrites rejectedIntermittent timeoutsSustained high node CPU

   Trigger

   The primary node of a database cluster failed at 16:35 UTC while one shard had several stalled nodes. The second period was set off by rolling the election protocol back to the previous minor version at 20:42 UTC.

   Root cause

   Software defect

   Component

   DatabaseDatabase failover manager

   Contributing factor

   Change with a delayed effectMonitoring blind spotExcessive blast radiusHarmful manual actionUnverified assumptionOverlapping failures

   Detection

   Automated monitoring detected the failed election within a minute, and the team was alerted at 16:36 UTC. The second period was announced at 21:14 UTC by automated alerts that some shards in the cluster were unavailable.

   Remediation

   • Restarted all nodes of the database cluster, which forced a successful primary election
   • Updated the production configuration and restarted the database cluster's nodes
   • Ramped traffic back up, putting services for user-initiated API requests first

   Action items

   • Alert when nodes stop reporting their replication lag
   • Alert when a shard enters a state that could trigger the election fault
   • Work with the database maintainers on a fix for the underlying fault
   • Add circuit breaking on failed operations to particular database clusters
   • Use fault isolation to contain the impact of a single failed shard
   • Limit the resources used by clients that keep retrying failed requests
   • Add procedures and tooling that make rapid configuration changes during incident response safer

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5. IL-0289 A failing SSD made updown.io's primary MongoDB about 200 times slower, no failover happened and the site went down

   updown.io2019

   Symptoms

   At 2:30 am CEST on 3 April 2019, the primary MongoDB server of updown.io started answering queries about 200 times slower than usual, and the website and the monitoring daemons went almost completely down.

   High latencyService outageFailover failure

   Trigger

   One of the three SSDs in the primary MongoDB server's RAID5 array began to fail, slowing the server's IO without taking the server down.

   Root cause

   Hardware failure

   Component

   DatabaseDatabase failover manager

   Contributing factor

   –

   Detection

   The founder, who was asleep when the slowdown began, noticed the problem at 8:45 am CEST and found the IO performance issue by inspecting the primary server.

   Remediation

   • Forced the primary to step down after making sure the secondary was ready to take over
   • Took the failing SSD out of the RAID array, which restored the old primary's performance
   • Asked the hosting provider to replace the SSD
   • Replaced the less powerful secondary with a more powerful server

   Action items

   • Write a script that detects when MongoDB is up but not responsive and forces a step-down automatically
   • Shut down and delete the old secondary once nothing is left to investigate on it
   • Make sure the new secondary can run as primary for several days
   • Test the automatic step-down script once the primary server is healthy again
   • Provide a proper status page for updown.io
   • Replace the custom script with MongoDB's Storage Node Watchdog

   View case

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