Postmortem report on Open Food France's incident on 03/20/2019 02:47 PM UTC

#1

What follows is a brief description of the incident that happened on 03/20/2019 02:47 PM UTC and lasted until on 03/20/2019 04:27 PM UTC.

Summary

Postgres got stuck and didn’t process any new requests causing the app to be down for 1h and 46min. The issue didn’t get resolved until we restarted Postgres for a second time.

Impact

All users using Open Food France at that time impacted.

Root Causes

We don’t have data to claim the hypothesis but possibly a deadlock or a very long UPDATE statement caused Postgres not to respond. See image below.

Trigger

Chances are that the culprit statement/s were issued by a background job.

Resolution

Proceeded to kill what seemed to be the stuck process and restarted Postgres. However, it took a while for the server to actually kill the process. Below you can see a COMMIT statement blocking the restart.

Then, we stopped Unicorn and Nginx to prevent any new requests but Postgres got stuck with the process line postgres: startup process recovering after the restart.

A strace on the main Postgres process pointed out that the process was sort of looping on a bunch of instructions. We then killed that process and started it again through systemd and it finally worked.

We then proceeded to start Unicorn and Nginx back again.

Detection

I saw the fr-prod-happy-apps alarm in #devops-notifications regarding production and when I went check Datadog a saw an abnormal CPU I/O wait. See image below.

You can check out the incident alarm at https://app.happyapps.io/incidents/890519

Action Items

See Change to a Datadog’s paid plan and Enable PostgreSQL detailed logging in Making operations a first-class citizen.

I also suggest we create a postmortem category for these reports.

Lessons Learned

What went well

  • The team acted very quickly and without panicking :muscle::heart:
  • All team members involved contributed with ideas to fix the issue
  • Datadog’s infrastructure monitoring was very useful to spot the impact of the incident.
  • A Slack thread provided to be a great way to communicate while serving as history of the event.

What went wrong

  • It took us long to figure out that the only way to solve it was stopping Postgres.
  • We have no experience in responding to such incidents.
  • We don’t have any mechanism to know when Postgres is not performing as expected so there’s no way to actually know what is going on.

Where we got lucky

  • Stopping, killing and restart processes didn’t cause data loss, as far as we know.

Timeline

Check out the Slack thread

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