Cases20 cases

11 to 15 of 20

1. IL-0556 A transaction left open during database maintenance stopped uploads and then downloads on Storj's US1 satellite

   Storj2024

   Symptoms

   At 14:56 UTC on 20 May 2024, write operations on the Storj US1 satellite began to fail, so uploads stopped working, and downloads failed after them. The on-call team was paged at 14:59 UTC, while the AP1 and EU1 satellites kept working normally.

   Lock contention or deadlockService outage

   Trigger

   During routine, manual database maintenance on the US1 satellite that began at 14:55 UTC, a transaction was left open by mistake while other work was being done.

   Root cause

   Operator error

   Component

   Database

   Contributing factor

   –

   Detection

   The on-call team received a page at 14:59 UTC, three minutes after writes started failing.

   Remediation

   • Found and closed the open transaction at 15:22 UTC, after which the satellite recovered

   Action items

   • Review and update database maintenance procedures and training so that every transaction is closed before moving on to other tasks
   • Add monitoring and alerts for open transactions that last longer than a set duration
   • Look for further process and system improvements, including tools that reduce or remove the need for manual maintenance

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2. IL-0217 Honeycomb's main MySQL database locked up under cache-miss reads and ran out of connections, a 68-minute total outage

   Honeycomb2023

   Symptoms

   Hours after a routine switch between two clusters of Retriever, Honeycomb's storage and query engine, late on 24 July 2023, the internal SLO for Shepherd, the ingest service, began to burn slowly. The performance was only marginally slow and inconsistent, with no good explanation, so engineers treated it as minor and left it for the morning.

   High latencyDatabase overloadLock contention or deadlockService outage

   Trigger

   Late on 24 July Honeycomb switched between two Retriever clusters to avoid a subtle bug, and the new cluster stopped writing the last-written timestamps the schema cache depends on. On the morning of 25 July a feature flag flip meant to move those writes back stopped the remaining writes entirely.

   Root cause

   Software defect

   Component

   DatabaseIn-memory cache

   Contributing factor

   Dependence on a warm cacheIgnored early signalHarmful manual actionUnverified assumption

   Detection

   Hours after the cluster switch, the internal SLO for the ingest service Shepherd started burning slowly. Engineers left it for the morning, when a chart showed that Retriever's database calls updating the last-written records had stopped.

   Remediation

   • Flipped only the writes back to the other Retriever cluster with a feature flag, which did not fix the problem
   • Set up circuit breakers that denied all Shepherd traffic with a 5xx error to protect the database
   • Failed the hard-locked database over to a replica
   • Restarted all Retriever hosts so they could provide data for the cache
   • Set the last-written timestamp of every schema with traffic in the last day to now, so the schema store reloaded the cache
   • Removed the circuit breaker and restarted the query hosts that failed internal checks

   Action items

   • Finish the Retriever cluster migration and remove all code that could disable writes behind the cache
   • Explore ways to strengthen the cache further
   • Lower the contention put on the database during update storms from new schemas
   • Stabilise the performance costs of some operations in the system
   • Study instrumentation and experimentation that detect and handle such edge cases better

   Lessons

   Locally good decisions combined into the outage: the query engine wrote the timestamps because it already saw all the data, the shared cache helped scale ingest and untangle the main database, the cluster switch was done to avoid a bug, frequent deploys hid the feature flag bug, pausing deploys during the investigation kept hosts from restarting, and past near-misses made the team expect a slow failover. Feature flags, frequent deploys, pausing deploys during incidents and learning from near-misses all contributed, although they are among the practices Honeycomb trusts most. For a rare lockup of this kind a database failover is the fastest recovery. Several recent Honeycomb incidents started from trying to avoid a subtle bug.

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3. IL-0483 Replicate's website and API returned slow responses and HTTP 500s for two hours as PostgreSQL connections ran out

   Replicate2023

   Symptoms

   From 05:45 UTC on 11 May 2023, for about two hours, many Replicate customers got slow responses or HTTP 500 errors from the API and the replicate.com website and had trouble running predictions. Monitoring paged an engineer at 05:46 UTC, a minute after the database connection pool became fully saturated.

   High error rateHigh latencyLock contention or deadlock

   Trigger

   A little after 05:00 UTC on 11 May, normal variations in traffic pushed the stacking INSERT queries past their tipping point.

   Root cause

   Faulty deployment

   Component

   Database

   Contributing factor

   Change with a delayed effect

   Detection

   Monitoring detected the saturated database connection pool almost immediately and paged an engineer at 05:46 UTC.

   Remediation

   • Switched off all asynchronous prediction update features with a feature flag at 07:31 UTC, after which the database recovered

   Action items

   • Keep the asynchronous prediction update feature disabled and redesign it so it no longer sends stacked INSERTs
   • Review lock contention and other database hotspots that could cause similar problems
   • Publish detailed reports after major incidents

   Lessons

   The system ran in a degraded state that looked successful until it tipped into a full failure. The same asynchronous update work that triggered the outage also partly protected customers who used webhooks, and the stacked INSERTs came directly from a latency improvement: removing 100-150ms brought two updates of one prediction to the database almost together.

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4. IL-0524 An index migration locked Open Collective's whole Transactions table and degraded the service for nearly an hour

   Open Collective2023

   Symptoms

   At 09:20 UTC on 4 April 2023, seven minutes after a deployment was triggered, Open Collective's service degraded: a migration in the deployment had locked the entire Transactions table in the production database.

   Lock contention or deadlockDatabase overload

   Trigger

   A deployment ran a migration that dropped indexes on the Transactions table and re-created them with CONCURRENTLY, excluding soft-deleted rows.

   Root cause

   Faulty deployment

   Component

   DatabaseSchema migration

   Contributing factor

   Missed in reviewUnrepresentative staging

   Detection

   The degradation of service was noticed at 09:20 UTC, seven minutes after the deployment was triggered.

   Remediation

   • Killed the migration, though the table remained locked
   • Put the frontend into maintenance mode to limit queries
   • Closed the other connections to the database
   • Cancelled the new index creation and restored the old index
   • Restored the frontend and confirmed the issue was resolved

   Action items

   • Add a script that simulates production load locally, using a tool like vegeta
   • Run this kind of migration during specific maintenance windows
   • Create the new index first and drop the old one afterwards in future migrations
   • Insist on a review from another engineer before merging such a pull request

   Lessons

   Dropping the old index before creating the new one was too optimistic under constant production queries, even with CONCURRENTLY, and an unreviewed pull request let it through. Tests locally and on staging did not show the problem because there were no tools to run migrations in stressed environments. Putting the frontend in maintenance mode limited the impact while showing users a clear message.

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5. IL-0314 Daily's newly upgraded Aurora MySQL database deadlocked on meeting-event queries and its call servers kept restarting

   Daily2023

   Symptoms

   At 9:47 AM Eastern (14:47 UTC) on 7 February 2023, Daily's database alerts reported a performance problem under normal operational load: a high level of lock contention on a database that had been upgraded the weekend before and had run normally since Monday. Users could get websocket connection errors when joining calls, and REST API requests could time out or return 5xx errors.

   Lock contention or deadlockHigh error rateIntermittent timeouts

   Trigger

   Database maintenance the weekend before had upgraded the database to a MySQL point release with a low-level behaviour change, and on 7 February, under normal load, that change produced the deadlocks Daily saw on Aurora MySQL 2.11.0.

   Root cause

   Breaking change in an upgrade

   Component

   Database

   Contributing factor

   Unrepresentative stagingAutomation amplificationRetry stormChange with a delayed effect

   Detection

   Database alerts at 9:47 AM Eastern reported a performance issue with high lock contention on the newly upgraded database.

   Remediation

   • Disabled MySQL binlog replication to the old database and restarted the database to reduce load
   • The database restarted by itself at 10:47 AM, the SFUs dropped the stale meeting updates without restarting, and the platform recovered
   • Rate-limited the POST /rooms endpoint to the same limit as DELETE /rooms/:name
   • Updated an index on the affected table in production on the Saturday evening to work around the MySQL behaviour change

   Action items

   • Work with AWS so the Aurora MySQL 2.11.0 deadlock issue is documented, understood and fixed in a future release
   • Add more API request patterns to the testing workload used for infrastructure changes
   • Add production monitoring alarms on more fine-grained database metrics

   Lessons

   Daily tests infrastructure changes under production-like workloads, but its synthetic workload did not have the shape that triggers these deadlocks. A deadlock behaviour change in MySQL 5.7 that was already known turned out far more severe in production than either Daily or the AWS Aurora team expected.

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