Cases13 cases

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1. 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
2. IL-0210 GitHub's MySQL clusters failed over to the US West Coast and the site served slow, stale, inconsistent data for 24 hours

   GitHub2018

   Symptoms

   At 22:54 UTC on 21 October 2018 GitHub's internal monitoring started alerting on many faults at once. By 23:02 UTC the first responders saw that the replication topologies of many MySQL clusters were in an unexpected state: the Orchestrator API showed topologies made only of servers in the US West Coast data center. When connectivity came back, the application tier had immediately started sending writes to the new West Coast primaries.

   Split brainFailover failureReplication lagHigh latency

   Trigger

   At 22:52 UTC on 21 October, routine maintenance to replace failing 100G optical equipment cut connectivity between GitHub's US East Coast network hub and its primary US East Coast data center for 43 seconds.

   Root cause

   DNS or network fault

   Component

   DatabaseDatabase failover managerDatabase replicationDatabase backups and snapshotsNIC, cable and switch port link

   Contributing factor

   Automation amplificationUnverified assumption

   Detection

   GitHub's internal monitoring raised alerts on numerous faults at 22:54 UTC, two minutes after the partition. By 23:02 UTC the first responders had found, by querying the Orchestrator API, that many database clusters had a topology with only US West Coast servers.

   Remediation

   • Locked the internal deployment tooling to stop further changes
   • Paused webhook delivery and GitHub Pages builds to stop jobs writing metadata
   • Restored the affected MySQL clusters from backups into the US East Coast data center and let them replicate from the West Coast
   • Found ways to restore directly from the West Coast to get around the throughput limits of downloading from off-site storage
   • Moved all database primaries back to the US East Coast data center
   • Spread read traffic over additional MySQL read replicas in the US East Coast public cloud so replication could catch up
   • Failed over to the original topology once the replicas were in sync
   • Processed the backlog of webhook events and Pages builds, pausing to raise an internal TTL after about 200,000 webhook payloads were dropped

   Action items

   • Reconcile the writes from the captured MySQL binary logs that were not replicated, automatically where possible and with user outreach otherwise
   • Make sure status updates can be published even when GitHub Pages builds are paused
   • Give more accurate public estimates of the time to repair
   • Configure Orchestrator so it cannot promote database primaries across regional boundaries
   • Move to a status reporting mechanism that shows the status of each component of the platform
   • Serve GitHub traffic from multiple data centers in an active/active/active design with N+1 redundancy at the facility level
   • Test assumptions about the system more proactively
   • Validate failure scenarios systematically, with investment in fault injection and chaos engineering tooling

   Lessons

   Orchestrator did what it was configured to do, but the application tier could not work with primaries on the other side of the country: leader election within one region is generally safe, while the sudden cross-country latency was a major contributing factor. The behaviour emerged from a partition larger than any GitHub had seen. Replication caught up along a power decay curve, not a straight line, so the linear estimates of recovery time were wrong. GitHub concluded that tighter operational controls and faster response are not enough on their own and that failure scenarios have to be validated before they happen.

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3. IL-0388 A Google Cloud live migration took a Discord Redis primary offline, and the failover broke API instances and then guilds

   Discord2017

   Symptoms

   At about 14:01 PDT on 13 October 2017, Discord engineers were alerted to anomalies by real-time metrics and monitoring. A Redis instance that was the primary of a highly available cluster used by the API services had dropped offline after Google Cloud Platform migrated it automatically, and some API instances did not handle the failover to the secondary node correctly.

   Failover failureHigh latencyService outage

   Trigger

   Google Cloud Platform automatically migrated the Redis instance that was the primary of a highly available cluster used by the API services, and the node incorrectly dropped offline.

   Root cause

   Software defect

   Component

   In-memory cacheDatabaseCDN and edge network

   Contributing factor

   Unpatched known bugOverlapping failuresMonitoring blind spot

   Detection

   Real-time metrics and monitoring alerted engineers at 14:01 PDT. The second phase was seen at 15:41 as another anomaly in monitoring, and end user reports of servers appearing offline were escalated at 15:42.

   Remediation

   • Ran a rolling restart of all API instances to clear the Redis connection issues
   • Corrected the misconfigured edge caching rule for the expensive API route
   • Disabled the problem API endpoint on the edge network
   • Recovered the Cassandra cluster
   • Ran a second rolling restart of all API instances for the latency left by the Cassandra issues
   • Removed the misbehaving guilds node from the service hashring
   • Forcefully restarted the misbehaving guilds node
   • Restarted the whole service, forcing all users to reconnect
   • Blocked traffic that relied on the failing push component to reduce its load
   • Corrected the API setting that lets users reconnect quickly and safely

   Action items

   • Fix the known issues with Redis failover within the coming weeks
   • Change the cached route so this type of error does not degrade other services
   • Monitor the signals that would have warned of the cascading failure
   • Improve the reliability and failure handling of the affected services
   • Roll out an update of the library with the suspected flaws

   View case
4. IL-0219 GoCardless's API and Dashboard failed every request for 1 hour 50 minutes when Pacemaker did not promote a replica

   GoCardless2017

   Symptoms

   At 15:09 BST on 10 October 2017, GoCardless's monitoring detected a total outage of its API and Dashboard: every request failed and returned an error. By 15:11 engineers saw evidence of a disk array failure on the primary Postgres node, but the Pacemaker cluster had not failed over to the synchronous replica as it should have.

   Service outageFailover failure

   Trigger

   The RAID controller of the primary Postgres node lost 3 disks of its array at once, so all reads and writes on the primary failed.

   Root cause

   Hardware failure

   Component

   DatabaseDatabase failover manager

   Contributing factor

   Overlapping failuresUnverified assumption

   Detection

   GoCardless's monitoring detected the total outage of the API and Dashboard at 15:09 BST, and engineers began investigating.

   Remediation

   • Powered off the broken primary Postgres node
   • Cleared the Pacemaker error counts with crm resource cleanup, which had no effect
   • Edited recovery.conf on the synchronous replica under maintenance mode several times, which Pacemaker reverted
   • Put the cluster into maintenance mode, configured the synchronous replica as primary and started Postgres by hand
   • Reconfigured the backend applications to connect to the new primary's actual IP address
   • Bootstrapped a third node as an asynchronous replica
   • Added a VIP managed by hand by the infrastructure team for manual failover
   • Verified data integrity and found no corruption
   • Migrated to a new Pacemaker-managed database cluster in a maintenance window and decommissioned the old one

   Action items

   • Express the Backup VIP rule as an INF preference for a replica instead of a -INF preference against the primary
   • Replace the VIPs with proxies on the application servers that route traffic by the state of the cluster
   • Run harsher fault injection tests of the Postgres cluster and consider automation that injects failures continually
   • Consider adding arbitrary restrictions to game day exercises, such as automation that has failed and a problem that cannot be diagnosed, so engineers practise bringing the service back another way

   Lessons

   A rule that two resources must not run together does not behave like the opposite of a rule that they must run together, and in some failure conditions the difference stopped Pacemaker from promoting a replica. A misconfiguration that shows only when two processes crash at almost the same time will not appear in basic tests or daily operations, only through fault injection. After two years in which the automation had handled every failure, the team's skill at controlling the cluster by hand had faded, and a runbook unused for years would likely have been out of date.

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5. IL-0335 A bugcheck in the primary SQL Server put the Stack Exchange network into read-only mode and then offline for 12 minutes

   Stack Exchange2017

   Symptoms

   On January 24, 2017 at 17:53 UTC the Stack Exchange network, including Stack Overflow, went into read-only mode for about 5 minutes and then went offline for 12 minutes. It took the team 2 minutes to notice the problem, 5 minutes to locate its source and 10 minutes to restore service.

   Writes rejectedService outageFailover failureData loss

   Trigger

   At 17:53 UTC the primary SQL Server, NY-SQL02, triggered a bugcheck in the SQL Server process.

   Root cause

   unknown

   Component

   Database

   Contributing factor

   Single point of failure

   Remediation

   • Restarted the SQL service on NY-SQL02, which brought the network back online in read-only mode
   • Put the sites back into read-write mode after a sanity check of SQL health
   • Brought the network online without waiting for the memory dump to complete
   • Took NY-SQL02 out of production for testing, including a memory test, and ran the normal load on NY-SQL01
   • Brought the SQL cluster up to 2016 SP1 CU1

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