We are fully down for a subset of customers. We're investigating the issue, and are rolling back a deployment.

Summary

We are fully down for a subset of customers. We're investigating the issue, and are rolling back a deployment.

Incident: An internal system responsible for automatically scaling backend server capacity in one of our compute clusters stopped replacing capacity that had been cycled out during routine maintenance. This caused a gradual reduction in available capacity over several hours. A subsequent deployment was activated with insufficient capacity, causing all new requests for that compute cluster to fail. To mitigate the impact, we reverted to a previous release revision, which still had sufficient capacity. Impact: For approximately 30 minutes, customers whose traffic was handled by this compute cluster saw full downtime; other customers were unaffected. No customer data was lost. Moving forward: We have added additional monitoring to detect this type of capacity-scaling failure much earlier, and have added safeguards to prevent deployments from shifting traffic before sufficient healthy capacity is confirmed. _Our metric considers a weighted average of uptime experienced by users at each data center. The number of minutes of downtime shown reflects this weighted average._

• Started

  Sep 2, 2026 · 6:08 PM

• Resolved

  Sep 2, 2026 · 6:49 PM

• Duration

  41m

• Severity

  Major

• ◐

  Investigating

  Sep 2 · 6:08 PM Asana

  We are currently investigating this issue.

• ◐

  Investigating

  Sep 2 · 6:13 PM Asana

  We are continuing to investigate this issue.

• ◐

  Investigating

  Sep 2 · 6:14 PM Asana

  The rollback seems to have completely resolved errors. We're monitoring closely, but users should be able to access Asana again.

• ◉

  Monitoring

  Sep 2 · 6:14 PM Asana

  A fix has been implemented and we are monitoring the results.

• ✓

  Resolved

  Sep 2 · 6:49 PM Asana

  This incident has been resolved.

• ✓

  Postmortem

  Sep 4 · 7:52 PM Asana

  Incident: An internal system responsible for automatically scaling backend server capacity in one of our compute clusters stopped replacing capacity that had been cycled out during routine maintenance. This caused a gradual reduction in available capacity over several hours. A subsequent deployment was activated with insufficient capacity, causing all new requests for that compute cluster to fail. To mitigate the impact, we reverted to a previous release revision, which still had sufficient capacity. Impact: For approximately 30 minutes, customers whose traffic was handled by this compute cluster saw full downtime; other customers were unaffected. No customer data was lost. Moving forward: We have added additional monitoring to detect this type of capacity-scaling failure much earlier, and have added safeguards to prevent deployments from shifting traffic before sufficient healthy capacity is confirmed. _Our metric considers a weighted average of uptime experienced by users at each data center. The number of minutes of downtime shown reflects this weighted average._