Individual skill
fabric-data-factory-perf-remediate
Diagnose and resolve Microsoft Fabric Data Factory pipeline performance issues. Use when pipelines are slow, copy activities timeout, dataflows stall, activities are stuck, throughput is low, capacity is throttled, or jobs queue indefinitely. Covers copy activity tuning (parallelCopies, DIU, ITO, partitioning), pipeline monitoring via Monitoring Hub and workspace monitoring, Spark job queueing, capacity SKU limits, error code resolution, and dataflow optimization. Keywords include Fabric pipeline slow, copy activity performance, Data Factory throttling, pipeline timeout, activity stuck, TooManyRequestsForCapacity, HTTP 430, pipeline troubleshoot, dataflow performance, copy parallelism, intelligent throughput optimization.
skills/fabric-data-factory-perf-remediate/SKILL.md
Source commit cee03dc1199cd2a9765b439fa41930d480e5989d
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- Last checked
- Nov 6, 2026
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- Repository last updated
- Jun 7, 2026
- License
- MIT
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- claude Repository topic
- claude-skills Repository topic
- copilot Repository topic
- copilot-skills Repository topic
- fabric Repository topic
- microsoft-fabric Repository topic
- data Derived category
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LICENSE.txtdoc · 11,358 bytesSKILL.mdcore · 9,812 bytesSKILL.mdcore · 9,812 bytesreferences/capacity-throttling-guide.mddoc · 5,958 bytesreferences/copy-activity-tuning.mddoc · 8,233 bytesreferences/dataflow-optimization.mddoc · 5,529 bytesreferences/pipeline-stuck-resolution.mddoc · 6,812 bytesreferences/workspace-monitoring-setup.mddoc · 5,375 bytesscripts/Get-FabricPipelineDiagnostics.ps1runs · 12,625 bytestemplates/troubleshooting-runbook.mddoc · 3,428 bytes
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# Microsoft Fabric Data Factory Performance remediate
Systematic approach to diagnosing and resolving performance issues in Microsoft Fabric Data Factory pipelines, copy activities, and dataflows.
## When to Use This Skill
- Pipeline execution takes longer than expected
- Copy activities are slow or appear stuck
- Activities show "Not Started" status for extended periods
- Capacity throttling errors (HTTP 430, TooManyRequestsForCapacity)
- Throughput is lower than expected for copy operations
- Dataflow Gen2 refresh is slow or timing out
- Pipeline monitoring shows performance degradation over time
- Need to optimize parallelism, DIU, or partitioning settings
