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Outage in Astro

Degraded Worker Autoscaling on Hosted Shared Azure Cluster (US-East2)

Resolved Minor
March 04, 2026 - Started 3 days ago - Lasted 1 day
Official incident page

Incident Report

We are currently investigating an issue affecting Airflow worker autoscaling for some deployments hosted on the Shared Azure Cluster in the US-East2 region. As a result of this issue, worker pods may not scale up as expected in response to workload demand. This can lead to tasks remaining in a queued state longer than usual and, in some cases, failing due to queued timeouts. Our engineering team is actively working to identify the root cause and restore normal autoscaling behaviour. We will provide further updates as more information becomes available. Impact: • Affected deployments may experience delayed task execution. • Worker pods may not scale up from zero or may not scale as expected under load. We will continue to share updates on this page as we make progress toward resolution.

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Latest Updates ( sorted recent to last )
RESOLVED 1 day ago - at 03/05/2026 11:05PM

This incident has been resolved.

MONITORING 2 days ago - at 03/05/2026 04:49PM

Azure confirmed that the fix has been successfully deployed to East US 2 region. We are monitoring the results.

IDENTIFIED 3 days ago - at 03/04/2026 02:31PM

We have identified the root cause of the autoscaling issue affecting certain deployments on the Shared Azure Cluster in the US-East2 region. The issue is related to underlying infrastructure behaviour within the cloud provider environment.

Azure has acknowledged the issue and is currently rolling out a hotfix across regions. We are actively monitoring the rollout and will provide further updates as they become available.

INVESTIGATING 3 days ago - at 03/04/2026 02:10PM

We are currently investigating an issue affecting Airflow worker autoscaling for some deployments hosted on the Shared Azure Cluster in the US-East2 region.

As a result of this issue, worker pods may not scale up as expected in response to workload demand. This can lead to tasks remaining in a queued state longer than usual and, in some cases, failing due to queued timeouts.

Our engineering team is actively working to identify the root cause and restore normal autoscaling behaviour. We will provide further updates as more information becomes available.

Impact:
• Affected deployments may experience delayed task execution.
• Worker pods may not scale up from zero or may not scale as expected under load.

We will continue to share updates on this page as we make progress toward resolution.

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