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High severitycapacityMicrosoft Fabric

Microsoft Fabric Error:
HTTP 430

What does this error mean?

A Spark notebook, job, or pipeline in Fabric was rejected with HTTP 430 because the workspace has exceeded its allocated Compute Units (CUs) for Spark workloads.

Common causes

  • 1Multiple Spark sessions running simultaneously in the workspace, exhausting the concurrent job limit for the capacity SKU
  • 2A large-scale ETL operation consuming Compute Units beyond the SKU allocation
  • 3Orphaned or stalled Spark sessions left running in the background, consuming CUs without doing work
  • 4Capacity SKU is too small for the current Spark workload demands
  • 5All capacity CUs consumed by other workloads in the same workspace

How to fix it

  1. 1Stop orphaned or stalled Spark sessions in the Fabric workspace (Workspace settings > Spark > Active sessions).
  2. 2Enable Autoscale Billing for Spark workloads — this offloads Spark jobs to dedicated serverless resources and eliminates CU consumption from capacity.
  3. 3Stagger Spark job schedules to avoid peak-time overlap where multiple heavy jobs run simultaneously.
  4. 4Upgrade the Fabric capacity SKU if your sustained Spark workload regularly exceeds the current CU allocation.
  5. 5Use Fabric capacity metrics (Capacity Metrics app) to identify which workloads are consuming the most CUs and optimize them.

Frequently asked questions

Does this error mean I need to upgrade my capacity?

Not necessarily — capacity errors can be caused by query parallelism, large models, or concurrent refreshes. Optimize heavy datasets and schedule refreshes off-peak before upgrading.

Does this error affect all workspaces on the capacity?

Yes — Premium and Fabric capacities are shared. Heavy usage in one workspace can cause capacity errors in others on the same SKU.

Can I retry a failed refresh without waiting for the next schedule?

Yes — go to the dataset in Power BI Service and click 'Refresh now'. If the capacity issue was transient, the retry succeeds.

Does Power BI automatically retry capacity-related failures?

Power BI does not automatically retry failed refreshes. You need to trigger a manual refresh or wait for the next scheduled slot.

Source · learn.microsoft.com/en-us/fabric/data-engineering/troubleshoot-permissions-capacity

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