Cases2 cases

1 to 2 of 2

1. IL-0510 MIT Learn's RDS PostgreSQL ran out of storage after a release and learn.mit.edu returned 503s and 504s for hours

   MIT Open Learning2026

   Symptoms

   On 24 March 2026 learn.mit.edu went down shortly after a regular release. An engineer reported the outage with a linked Sentry issue, and Sentry soon showed many 504 responses from the site.

   Service outageNode disk fullDatabase overloadLock contention or deadlock

   Trigger

   A regular release deployed a query pattern change to the learning resource APIs that put an aggregation inside the main query.

   Root cause

   Faulty deployment

   Component

   Database

   Contributing factor

   Inefficient queryUnrepresentative stagingHarmful manual action

   Detection

   An engineer reported the outage with a linked Sentry issue, and Sentry showed many 504 responses. The RDS FreeStorageSpace metric showed that the database had used up its storage.

   Remediation

   • Rolled back the release's query pattern change
   • Deleted the read replica so the database could flush its buffered WAL files
   • Terminated all active queries running longer than 10 minutes with pg_terminate_backend, after the backup finished and with guidance from AWS Support

   Action items

   • Explore enabling enhanced analytics on the production Learn database
   • Document rollback steps on the platform engineering documentation site
   • Make easy rollback part of the new release management framework
   • Alert on DiskQueueDepth for production databases without making the alert too noisy
   • Alert when API and site response times are more than 30% above normal
   • Run a gameday on an example production database outage
   • Adopt Rootly for incident management, with an automatic channel and an automatic incident transcript
   • Write an outage runbook: start a call, have the on-call engineer watch metrics until they return to baseline, and give one person the communications
   • Put the query that terminates long-running queries, and a version that finds them for selective termination, into a production Postgres runbook
   • Open an issue on redesigning the Learn Resource View Event model, which is only used for counts
   • Use anonymised production data generation tools to bring RC up to production data volume, on separate infrastructure for load testing
   • Change the view count to use a precomputed column

   Lessons

   The change was reviewed by senior engineers and showed no problems locally or on RC, but data scale and load in production are very different, and nothing in the system's health showed that adding a COUNT aggregation would make disk usage explode.

   View case
2. IL-0511 MIT xPro stopped responding after a configuration deploy as pgbouncer logins to RDS failed with 'wrong password type'

   MIT Open Learning2023

   Symptoms

   On 30 October 2023 at 3:51PM, six minutes after a configuration update was deployed to the xPro production Heroku stack, Pingdom alerted the DevOps on-call engineer, who confirmed at 3:52PM that the site was not responding.

   Service outageCredentials unavailable

   Trigger

   A configuration update applied through Salt at 3:45PM found that the Vault lease of the database credentials was about to expire and could not be renewed, so Vault generated new credentials.

   Root cause

   Configuration change

   Component

   DatabaseSecrets store

   Contributing factor

   Unreviewed defaultsChange with a delayed effectConfiguration not in code

   Detection

   Pingdom alerted the DevOps on-call engineer at 3:51PM, and the alert went through OpsGenie; Pingdom closed it automatically at 4:25PM.

   Remediation

   • Created a new database parameter group and applied it to the running RDS instance
   • Cleared the cached credentials and re-applied the Heroku configuration through Salt

   Action items

   • Move the management of xPro resources, including the RDS instance, into Pulumi, where AWS default parameter groups are not used

   Lessons

   Almost none of the configuration for this stack, the RDS instance in particular, was managed as code, and that was one of the main reasons the fix took long. Under Pulumi the instance would not have used an AWS default parameter group, and the fix would have been a change to an attached group.

   View case

By root cause2