Incident Library
Applied filters ComponentDatabase proxy and connection poolerSymptomDatabase overloadClear allEvery case under the filters, with no sentence; newest first.
Suggested filters Search, and the values found in your words appear here.

Graph

  • Root cause
  • Component
  • Symptom
  • Contributing factor
  • Case

Cases6 cases

5 to 6 of 6

  1. Symptoms

    At 9:34 UTC on November 23, 2022, RevenueCat started moving traffic from its Aurora PostgreSQL 10.x cluster to a new Aurora PostgreSQL 14.x cluster. By 9:39 UTC all traffic was on the new cluster, latency was bad, and the RevenueCat dashboard and the endpoints used by the RevenueCat SDK stopped working.

    Trigger

    At 9:34 UTC production traffic was switched from the Aurora PostgreSQL 10.x cluster to the new Aurora PostgreSQL 14.x cluster, before ANALYZE had run on its largest tables.

    Root cause
    Component
    Contributing factor
    Detection

    At 9:39 UTC, with all traffic on the new cluster, latency looked bad and the infrastructure team began to investigate.

    Remediation
    • Added a statement timeout to the database user so queries could not hold a connection too long
    • Shed 90% of traffic by returning 503s from the load balancer
    • Dropped indexes that the planner was using wrongly and that were not needed
    • Stopped accepting Apple webhooks for a time
    • Rolled out a release without New Relic to stop its EXPLAIN queries
    • Ran ANALYZE by hand on the biggest tables
    • Raised the values of the affected primary key sequences with a prepared script
    • Stopped the integration event dispatcher by hand
    • Replayed the webhooks that were dispatched but not recorded
    • Restored integration event dispatching, ETLs and other non-web server jobs
    Action items
    • Consider change freezes during business-critical periods
    • Explain better how the SDK behaves during backend outages
    • Tell customers about maintenance and outages in the developer dashboard and by direct email to technical contacts
    • Replay a subset of write traffic in migration dry runs to mimic the cutover
    • Move costly processes to asynchronous work to keep the API fast and stable
    • Re-evaluate table indexes, including unused ones the database may choose for queries
    • Show the load of each endpoint and system in the database dashboards
    • Involve support and customer communications staff during outages
    Lessons

    The new cluster had not been analyzed, and the tests missed it because the test cluster had been up long enough to gather statistics. Dry runs replayed no write traffic, on the belief that writes are simpler than reads, and the team assumed sequence state was replicated with the data. Rolling back at the start would have been better than fixing forward. The migration, timed to finish before Thanksgiving and Black Friday, should have been delayed until the week after, because the US had entered a sensitive period and part of the US support team was already on holiday.

  2. Symptoms

    On March 16, 2022 at 14:09 UTC, write operations across GitHub stopped working, including git operations, webhooks, pull requests, API requests, issues, GitHub Packages, GitHub Codespaces, GitHub Actions and GitHub Pages. Under peak-hour load, the database proxy in front of the shared mysql1 MySQL database had reached its maximum number of connections.

    Trigger

    Increased load on mysql1 during peak hours, combined with poor query performance in specific circumstances, pushed the database proxy to its maximum number of connections.

    Root cause
    Component
    Contributing factor
    Remediation
    • Failed over mysql1 to a healthy replica on March 16
    • Reset the application connections to the new primary on March 17
    • Added an index that fixed the main query performance problem
    • Performed a primary failover on March 22
    • Performed a primary failover on March 23
    • Throttled webhook traffic to reduce load
    Action items
    • Keep throttling webhook traffic at peak load times
    • Audit the load patterns of mysql1 during peak hours and make performance fixes based on the audits
    • Move traffic to other databases to reduce load and speed up failover
    • Review change management, particularly monitoring and changes during high load in production
    • Shard the databases and scale up hardware
Check your cluster for this

These 6 cases involve Database and Database proxy and connection pooler. kubegap audits a Kubernetes cluster for gaps like these, read-only, from Claude Code or Codex; its checks cite public reports like the ones in this library.

By root cause4

Configuration change1 case

Organisation
  1. IL-0574 Aurora MySQL writer CPU stuck near 100% minutes after Safie pointed production at a new Amazon RDS Proxy
    Safie2026

Faulty deployment2 cases

Organisation
  1. IL-0369 Railway's backend API went down when a column migration waited on locks and replicas could not get database connections
  2. IL-0315 Railway's backend API went down when an index build locked a billion-row Postgres table and used up every connection

Breaking change in an upgrade2 cases

Organisation
  1. IL-0498 Clerk's Postgres database had load spikes every 15 minutes and requests failed and slowed intermittently for four days
    Clerk2025
  2. IL-0308 Most RevenueCat backend systems failed after cutover to a new Aurora PostgreSQL 14 cluster as queries became very slow

Capacity exhaustion1 case

Organisation
  1. IL-0302 Peak load on GitHub's mysql1 MySQL cluster maxed out its database proxy's connections and stopped writes in March 2022
    GitHub2022