Individual skill
fabric-lakehouse-perf-remediate
Diagnose and resolve Microsoft Fabric Lakehouse performance issues including slow Spark queries, small file problems, Delta table fragmentation, V-Order configuration, table maintenance (OPTIMIZE, VACUUM, Z-Order), SQL analytics endpoint tuning, Direct Lake performance, resource profile selection, autotune configuration, capacity throttling, and streaming ingestion optimization. Use when asked to troubleshoot Fabric Lakehouse slowness, optimize Delta tables, fix small file problems, configure Spark settings, run table maintenance, or improve query performance in notebooks or pipelines.
skills/fabric-lakehouse-perf-remediate/SKILL.md
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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
- data-databases Derived category
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LICENSE.txtdoc · 11,358 bytesSKILL.mdcore · 10,368 bytesSKILL.mdcore · 10,368 bytesSKILL.mdcore · 10,368 bytesSKILL.mdcore · 10,368 bytesSKILL.mdcore · 10,368 bytesreferences/concurrency-capacity.mddoc · 5,381 bytesreferences/delta-table-health.mddoc · 6,163 bytesreferences/resource-profiles.mddoc · 4,860 bytesreferences/rest-api-maintenance.mddoc · 4,824 bytesscripts/Get-DeltaTableHealth.ps1runs · 5,898 bytesscripts/Invoke-FabricTableMaintenance.ps1runs · 9,043 bytestemplates/maintenance-notebook.pyruns · 4,309 bytestemplates/perf-diagnostic-notebook.pyruns · 8,172 bytes
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# Fabric Lakehouse Performance remediate
Systematic toolkit for diagnosing and resolving performance issues in Microsoft Fabric Lakehouse environments. Covers Delta table health, Spark compute tuning, query optimization, and automated maintenance workflows.
## When to Use This Skill
- Lakehouse queries are running slowly or timing out
- Delta tables have accumulated many small files (small file problem)
- Spark notebooks or jobs are underperforming
- Direct Lake semantic models have cold-start or transcoding delays
- SQL analytics endpoint queries are slow
- Table maintenance (OPTIMIZE, VACUUM) needs to be scheduled or automated
- V-Order, Z-Order, or resource profile configuration is needed
- Capacity throttling or concurrency issues are suspected