Cases3 cases

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1. IL-0447 An every RDS for MySQL instance slowed badly when its gp2 EBS BurstBalance ran out and IOPS fell to the baseline

   every2024

   Symptoms

   The BurstBalance of an RDS instance began to fall rapidly and finally ran out, and the database's performance dropped sharply. The instance ran MySQL 5.7.44 on db.t3.medium with general purpose SSD (gp2) storage of 30GiB.

   Database overloadThroughput degradation

   Trigger

   A complex SELECT query began writing large amounts of data to temporary tables, which raised WriteIOPS and used up the burst credits.

   Root cause

   Capacity exhaustion

   Component

   DatabaseCloud block storage

   Contributing factor

   Inefficient query

   Action items

   • Consider tuning the query by reviewing indexes and rewriting it
   • Consider moving the storage from gp2 to gp3 or increasing its size to raise the baseline IOPS
   • Consider adjusting tmp_table_size and max_heap_table_size
   • Consider moving to a more powerful instance type
   • Consider monitoring BurstBalance with CloudWatch alerts and adding external monitoring such as Pingdom

   Lessons

   A complex query can have a large effect on I/O, so database design and queries need continuous improvement, and query performance needs regular monitoring.

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2. IL-0488 Kit's RDS MySQL write latency rose 100x and running threads jumped from 9 to 900, backing up Sidekiq job queues

   Kit2022

   Symptoms

   At 5:20 am EST on December 24, 2022, Kit's infrastructure team got its first page because the number of MySQL threads running on its RDS MySQL primary in us-east-2 had jumped 100x, from 9 to 900, at a time of day when Kit's traffic is very low. Sidekiq queues were backing up.

   Database overloadThroughput degradation

   Trigger

   An EBS interruption on the standby of the Multi-AZ RDS instance, reported by AWS as an LSE at 02:12:47 UTC on 2022-12-24, started a replaceSecondaryHostAndVolumesTask that replaced the secondary host and volumes.

   Root cause

   Cloud provider outage

   Component

   DatabaseCloud block storageDatabase replication

   Contributing factor

   Ignored early signal

   Detection

   A page fired at 5:20 am EST because MySQL threads running jumped from 9 to 900. An AWS RSS feed alert in Slack about degraded EC2 and EBS in use2-az1 had arrived the evening before and was not acted on.

   Remediation

   • Scaled the RDS storage from 12.5 TB to 13.75 TB, which put the instance through "optimizing storage" and brought write latency back to 1-2 ms

   Lessons

   Multi-AZ RDS keeps data consistent and durable, but synchronous replication means each write also waits for the standby, so a degraded EBS volume on the standby while it is being replaced slows writes on the primary. Large databases recover more slowly from such events than small ones. A single-AZ instance would not have been hit by a standby problem, but would have suffered hours of downtime if its own zone failed, and that trade-off has to be weighed when deploying production RDS instances.

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3. IL-0218 GitLab.com's primary PostgreSQL data was wiped by mistake and, with no working backup, the site was down about 18 hours

   GitLab2017

   Symptoms

   From around 19:00 UTC on 31 January 2017, load on GitLab.com's PostgreSQL database rose, which GitLab suspected was spam, and many users could not post comments on issues and merge requests. Around 23:00 UTC the replication of the PostgreSQL secondary fell behind and then failed, because WAL segments it still needed had already been removed from the primary.

   Database overloadReplication lagData lossService outage

   Trigger

   While trying to restore replication to the secondary, an engineer ran the removal of the PostgreSQL data directory on the primary, db1.cluster.gitlab.com, believing it was the secondary.

   Root cause

   Operator error

   Component

   DatabaseDatabase replicationDatabase backups and snapshotsCloud block storage

   Contributing factor

   Untested backupSingle point of failureNo runbookPages not deliveredUnverified assumptionUnreviewed defaults

   Detection

   The engineer who ran the deletion on the primary noticed the mistake and stopped it a second or two later.

   Remediation

   • Raised max_wal_senders from 3 to 32 and lowered max_connections from 8000 to 2000 so PostgreSQL would restart
   • Stopped the deletion on the primary a second or two after noticing it
   • Restored the database from the LVM snapshot taken about 6 hours before the outage by copying the PostgreSQL data directory from staging
   • Restored the webhooks from a separate database built from the snapshot and imported them as a SQL dump
   • Incremented all database sequences by 100,000 so IDs used before the outage could not be reused
   • Re-enabled GitLab.com gradually
   • Rebuilt projects created after 17:20 UTC in basic form from their Git repositories on the NFS cluster

   Action items

   • Change the shell prompt (PS1) on all hosts to show more clearly which host and environment is in use
   • Monitor backups with Prometheus
   • Set PostgreSQL's max_connections to a sane value
   • Investigate point-in-time recovery and continuous archiving for PostgreSQL
   • Take LVM snapshots of the production databases every hour
   • Take Azure disk snapshots of the production databases
   • Move staging to the ARM environment
   • Recover the production replicas
   • Test recovery of PostgreSQL database backups automatically
   • Improve the PostgreSQL replication documentation and runbooks
   • Investigate pgbarman for PostgreSQL backups
   • Investigate WAL-E for database backup and realtime replication
   • Build a streaming database restore
   • Assign an owner for data durability
   • Set up multiple secondaries and balance load among them with pgpool-II
   • Provide a tool for developers to run and revert Rails migrations on staging
   • Build owned recovery procedures for the rest of the GitLab.com infrastructure, not only the database
   • Publish a backup monitoring dashboard and add more backup data to it
   • Improve the abuse reporting and response system so removal for spam does not hard delete
   • Redact engineers' names in future public incident documents

   Lessons

   GitLab split the incident into two problems: GitLab.com went down because the primary's data directory was removed by mistake during a manual, undocumented replication rebuild, and recovery took over 18 hours because the backups had failed silently, disk snapshots were not enabled and the only copy sat on slow staging disks. The backup procedure was never tested because no one owned it. GitLab chose to focus on fast, regularly practised recovery and on making it obvious which host an engineer is on, rather than on blocking commands, since a safer rm only protects against one of many ways to lose data.

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