Cases7 cases

4 to 7 of 7

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-0340 Cloudflare's 1.1.1.1 resolver returned SERVFAIL to some valid DNS queries for four hours

   Cloudflare2023

   Symptoms

   From 07:00 to 11:00 UTC on 4 October 2023, some users of Cloudflare's 1.1.1.1 DNS resolver received SERVFAIL responses to valid queries. This reached users of WARP and Zero Trust and of third-party DNS resolvers that use 1.1.1.1, and the first external reports of unexpected SERVFAILs arrived at 7:57 UTC.

   DNS resolution failuresHigh error rate

   Trigger

   On 21 September 2023, as a planned change in root zone management, a ZONEMD resource record, in effect a checksum of the zone's contents, was added to the root zone for the first time. On 4 October at 07:00 UTC the DNSSEC signatures in the last root zone copy that 1.1.1.1 had loaded expired.

   Root cause

   Software defect

   Component

   Recursive DNS resolver service

   Contributing factor

   Cache-masked failureUnsafe failure behaviourMonitoring blind spotGap in automated tests

   Detection

   External reports of unexpected SERVFAILs started coming in at 7:57 UTC, and Cloudflare declared an internal incident at 8:03 UTC. Nothing had alerted on static_zone serving a stale root zone during the two weeks before.

   Remediation

   • Deployed an override rule meant to stop 1.1.1.1 from answering with the stale root zone, which did not cover forwarded queries
   • Stopped 1.1.1.1 from preloading the root zone file entirely

   Action items

   • Add alerts for when static_zone serves a stale root zone file
   • Re-evaluate how the root zone is ingested and distributed internally so new record types are handled
   • Improve test coverage for what happens when the root zone fails to parse
   • Limit how long stale copies of the root zone can be used, following RFC 8806

   Lessons

   Cloudflare's main lesson is never to assume an input will not change. Modern systems pull in long chains of libraries that may not be ready when their input changes, so they need tests that catch regressions and components that fail gracefully on new input, and format changes in DNS and BGP should be expected to have an impact. Cloudflare also writes that with better monitoring of the stale root zone, the existing caching would have prevented any impact.

   View case
3. IL-0506 UC Berkeley DataHub logins failed and students got empty home directories after the JupyterHub database was overwritten

   UC Berkeley2017

   Symptoms

   At about 1 AM on 9 February 2017, UC Berkeley's DataHub was reported down: users trying to log in got a proxy error. The hub pod was running, but its log was full of sqlite errors.

   Service outageData lossMisrouted requests

   Trigger

   While debugging, an operator ran `.save jupyterhub.sqlite` in sqlite3 inside the hub pod without having attached the database, which replaced the JupyterHub database file with an empty one.

   Root cause

   Operator error

   Component

   DatabasePersistent volumes and stateful setsJupyterHub

   Contributing factor

   No safeguard on destructive changeUnsafe failure behaviourHarmful manual action

   Detection

   DataHub was reported down at about 1 AM, when users got a proxy error at login. At 1:12 AM a user reported that he could log in but all his notebooks were gone.

   Remediation

   • Scaled the hub to 0 replicas
   • Rebuilt the JupyterHub sqlite database by matching Kubernetes PVC names back to user ids
   • Set cookie_id to null instead of a dummy value and attached the rebuilt database to the hub
   • Changed the cookie secret in the hub pod and restarted it to log all users out
   • Deleted all user pods to log everyone out
   • Ran a script that filled in cookie_id for all users, restarted the hub and deleted all user pods again
   • Dropped the new users with a '.' in their name and renamed the older users from '-' to '.'

   Action items

   • Report upstream that JupyterHub uses only part of the cookie secret and discards the rest
   • Report upstream that the cookie_id column of the users table should have UNIQUE and NOT NULL constraints
   • Ask KubeSpawner to support username hashes in PVC and pod names so the names stay the same when the database is deleted
   • Ask OAuthenticator to support using the id from the Google authenticator as the user id, giving stable user ids
   • Switch to Google Cloud SQL, a hosted and managed MySQL database
   • Take regular and tested backups of the database
   • Start an operational FAQ of things to do and not to do
   • Set up better monitoring and paging
   • Document escalation procedures explicitly

   View case
4. IL-0215 Twilio's billing Redis master lost all balances and went read-only, and auto-recharge charged customer cards repeatedly

   Twilio2013

   Symptoms

   At 2:39 AM PDT (9:39 UTC) on 18 July 2013, services that relied on the redis-master of Twilio's billing system began to fail because the load on its host had become extreme. At 2:42 AM PDT monitoring alerted the on-call engineers to a failure in the Redis cluster.

   Database overloadData lossWrites rejected

   Trigger

   At 1:35 AM PDT on 18 July a loss of network connectivity disconnected all billing redis-slaves from the redis-master at once, and all of them requested a full synchronization at the same time. On-call engineers then restarted the overloaded redis-master.

   Root cause

   Configuration change

   Component

   In-memory cacheDatabase replication

   Contributing factor

   Retry stormHarmful manual actionUnsafe failure behaviour

   Detection

   At 2:42 AM PDT monitoring alerted the on-call engineers to a failure in the Redis cluster. At 3:28 AM PDT the billing system monitoring reported the anomalous charges, and at 12:36 PM PDT monitoring detected the recurrence.

   Remediation

   • Restarted the redis-master to relieve the high load, which loaded a wrong configuration
   • Took the billing system offline to stop further credit card charges
   • Restored service to all suspended accounts
   • Restored the lost account balances from the independent double-bookkeeping record in the relational datastore
   • Took billing offline again after the recurrence and reactivated the newly suspended accounts
   • Refunded all erroneous credit card charges
   • Gave all affected accounts a credit of 10% of their last 30 days of spend
   • Replaced the original Redis cluster and corrected the redis-master configuration
   • Activated the billing system progressively for groups of customer accounts

   Action items

   • Disable Redis restarts on the redis-master and recover the master by pivoting a slave instead
   • Add fail-safes so the billing system neither suspends accounts nor charges cards when balances are missing or cannot be written
   • Validate the billing system against the double-bookkeeping databases in real time

   Lessons

   Losing the in-flight balances and the ability to write balances at the same time exposed a flaw in the auto-recharge system: it failed in a dangerous way, charging cards and suspending accounts instead of stopping.

   View case

By root cause5