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1. 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

   View case
2. IL-0430 Mackerel's Redis stopped answering during a replication setup, keepalived failed over by mistake, and Mackerel degraded

   Hatena2018

   Symptoms

   On 26 September 2018 at 10:51 JST the whole Mackerel monitoring service stopped working properly and its alive monitoring stopped. The application servers could not connect to Redis, which stores Mackerel's monitoring data, and could not return correct responses.

   Monitoring outageHigh latencyIntermittent timeouts

   Trigger

   Redis memory use had been growing, so operators set up replication in order to scale Redis up. Building the replication took a long time and Redis stopped answering for a while, and keepalived treated this as a node failure and started a failover nobody intended.

   Root cause

   Configuration change

   Component

   In-memory cacheDatabase replicationDatabase failover manager

   Contributing factor

   Automation amplificationOverlapping failures

   Remediation

   • Switched back to the correct Redis and briefly saw the application return
   • Restarted the application servers one after another, which did not improve the symptoms
   • Detected the organizations posting inappropriate metrics and blocked their requests
   • Adjusted the timeout interval of the application servers
   • Temporarily added capacity to Diamond, the TSDB
   • Increased the number of Kinesis shards and Redis Cluster shards
   • Scaled out the API application servers
   • Put Mackerel in maintenance mode, checked it internally and let outside requests back gradually

   Action items

   • Raise the number of keepalived health checks for Redis so a brief load increase does not trigger a failover
   • Scale Redis up
   • Add more application servers
   • Change the application to store only the monitoring data it needs in Redis, reducing Redis memory use
   • Build a way to detect inappropriate API requests quickly and show them on a dashboard
   • Build a function to block organizations making inappropriate requests quickly
   • Keep improving the accuracy of detecting inappropriate requests and consider adding features such as an API limit
   • Strengthen monitoring of the application servers' internal processing so problems are handled before they become outages

   Lessons

   Hatena did not find why recovery took so long, but expects that keeping failover from reacting to short load spikes and giving the application more performance headroom would prevent an outage this long. It also aims to keep problems contained to a small part of the service when a failure does happen.

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