Cases33 cases

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1. IL-0590 F5 load balancers cached a path MTU of 296 after Rackspace reboots, and Mailgun connections failed intermittently

   Mailgun2014

   Symptoms

   On Saturday, September 27, 2014 at 6:50 p.m. UTC, Mailgun saw that all its database replicas and the internal traffic between its environments in all regions were broken and reporting timeouts. Once Rackspace began rebooting cloud instances in its Chicago data center (ORD), Mailgun customers had intermittent connection failures.

   Intermittent connection failuresIntermittent timeoutsPacket loss

   Trigger

   Rackspace, Mailgun's parent company and hosting provider, rebooted cloud instances in its Chicago data center (ORD), and the cloud maintenance triggered an error condition on Mailgun's F5 load balancers.

   Root cause

   DNS or network fault

   Component

   Cloud load balancerDatabase replication

   Contributing factor

   –

   Detection

   Mailgun noticed at 6:50 p.m. UTC on September 27 that all database replicas and the internal traffic between its environments were broken and reporting timeouts.

   Remediation

   • The Rackspace networking team cleared the cached path MTU on Mailgun's F5s and on some Rackspace dedicated customers' F5s
   • Set up a new virtual IP for Mailgun services
   • Changed Mailgun's DNS settings, which forced the remote F5s to clear their caches

   Action items

   • Finish the root cause analysis of the F5 path MTU problem with Rackspace
   • Make sure maintenance of Mailgun's cloud infrastructure has no impact on Mailgun customers

   View case
2. 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
3. IL-0589 Every Kickstarter MySQL replica on Amazon RDS stopped replicating on a duplicate-key error in the backings table

   Kickstarter2013

   Symptoms

   On Thursday, March 7th, all of Kickstarter's MySQL replicas on Amazon RDS stopped applying updates, not just one replica that could be replaced. Most of Kickstarter's traffic is served from these replicas, so the site ran on stale copies of the database.

   Replication lag

   Trigger

   A later unsafe query on the backings table made MySQL switch to row-based replication for that query, and replaying the full row on the replicas collided with sequence values that already differed from the primary.

   Root cause

   Software defect

   Component

   DatabaseDatabase replication

   Contributing factor

   –

   Detection

   The team saw that the replicas had stopped updating, and SHOW SLAVE STATUS showed the duplicate-key replication error.

   Lessons

   Databases are intricate. In the Rails community they are sometimes treated as simple data stores hidden behind ActiveRecord and ActiveRelation, and Kickstarter's engineers concluded that it pays to learn how the database carries out what it is asked to do.

   View case
4. IL-0303 GitHub's MySQL master failed over to a node with a cold buffer pool during a schema migration and GitHub.com went down

   GitHub2012

   Symptoms

   On Monday, September 10th, 2012, during a schema migration, the health checks on GitHub's MySQL master failed and Percona Replication Manager moved the 'active' role to another node of the new three-node cluster. That node's InnoDB buffer pool was cold and it performed poorly, its health checks failed in turn, and the role failed back to the original server. GitHub.com went down.

   Failover failureDatabase overloadHigh latencyReplication lagSplit brainService outage

   Trigger

   A schema migration on Monday, September 10th put more load on the master database than earlier migrations had, and Percona Replication Manager's health checks on the master failed.

   Root cause

   Software defect

   Component

   DatabaseDatabase failover managerDatabase replication

   Contributing factor

   Automation amplificationDependence on a warm cacheHarmful manual actionOverlapping failures

   Detection

   On the morning of September 11th, a developer told the operations team that the 'standby' node was returning incorrect query results.

   Remediation

   • Enabled Pacemaker's maintenance-mode so no health checks or automatic failovers ran, and let the buffer pool warm
   • Powered off the out-of-date node 'c' to end the partition
   • Stopped Pacemaker and Heartbeat on nodes 'a' and 'b' and started them on node 'a' only
   • Started MySQL on node 'a' in the active role
   • Removed the events leaked to wrong dashboards and audited the wrongly routed repositories
   • Contacted the owners of the exposed private repositories

   Action items

   • Change the Pacemaker configuration so the active database role fails over only when an operations engineer starts it
   • Find a way to warm the InnoDB buffer pool of slave databases so failovers do not hurt performance
   • Audit the Pacemaker and Heartbeat stack, focusing on the code path behind the segfault
   • Run hardware tests on the server where the segfault happened

   Lessons

   GitHub concluded that automated failover is not the right strategy for its primary production database: for every failover in this incident, any member of the operations team would have said it should not happen. Failovers that must happen, in an emergency or during maintenance, should not hurt performance.

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