Agent 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.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/fabric-data-factory-perf-remediate

SKILL.md

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

Prerequisites

  • Access to Microsoft Fabric workspace with Contributor or higher role
  • Familiarity with the Fabric Monitoring Hub
  • Understanding of Fabric capacity SKUs and their limits
  • PowerShell 7+ for running diagnostic scripts

Diagnostic Workflow

Step 1: Identify the Bottleneck Category

Determine which category your issue falls into:

Category Symptoms Start Here
Copy Activity Slow Low throughput, long transfer duration copy-activity-tuning.md
Pipeline Stuck Activity shows In Progress with no movement pipeline-stuck-resolution.md
Capacity Throttling HTTP 430 errors, jobs queued capacity-throttling-guide.md
Dataflow Slow Dataflow Gen2 refresh takes too long dataflow-optimization.md
Spark Job Queue Jobs stuck in "Not Started" status capacity-throttling-guide.md

Step 2: Collect Diagnostics

Run the diagnostic script to gather baseline metrics:

powershell
./scripts/Get-FabricPipelineDiagnostics.ps1 -WorkspaceId "<guid>" -PipelineName "MyPipeline"

Or manually collect from the Monitoring Hub:

  1. Open Fabric portal and navigate to Monitoring Hub
  2. Filter by pipeline name and time range
  3. Select the run details (glasses icon) for the slow run
  4. Capture the Duration Breakdown for copy activities
  5. Note the queue time, transfer time, and pre/post-copy script duration

Step 3: Apply Targeted Fixes

Based on the bottleneck category, apply the appropriate optimization from the reference guides.

Quick Fixes for Common Issues

Copy Activity Running Slowly

  1. Set Intelligent Throughput Optimization to Maximum (or custom 4-256)
  2. Configure Degree of Copy Parallelism based on source type
  3. Enable Partition Option for SQL sources (Dynamic Range or Physical)
  4. Pre-calculate partition upper/lower bounds to avoid overhead
  5. Enable Staging when sink is Fabric Warehouse

Pipeline Activity Stuck

  1. Cancel the stuck activity and retry
  2. Check source/sink connectivity and credentials
  3. Verify Fabric capacity is not in throttled state
  4. Review if payload exceeds 896 KB limit
  5. Check for connection timeout or network interruption

Capacity Throttling (HTTP 430)

  1. Check current Spark concurrency against SKU limits
  2. Cancel unnecessary active Spark jobs via Monitoring Hub
  3. Consider upgrading to a larger capacity SKU
  4. Distribute pipeline trigger times to avoid burst load
  5. Use job queueing for non-interactive Spark workloads

Dataflow Gen2 Performance

  1. Reduce data volume with query folding and filters
  2. Avoid unnecessary data type conversions
  3. Minimize the number of transformation steps
  4. Use staging for large datasets
  5. Check for connector-specific throttling

Capacity SKU Quick Reference

SKU Max Spark Cores Queue Limit Equivalent Power BI
F2 Limited 4 -
F4 Limited 4 -
F8 Limited 8 -
F16 Limited 16 -
F32 Limited 32 -
F64 Standard 64 P1
F128 Standard 128 P2
F256 Standard 256 P3
F512 Standard 512 P4
F1024 Large 1024 -
F2048 Large 2048 -
Trial P1 equiv N/A (no queue) P1

Copy Activity Performance Settings Reference

Setting Property Range Recommendation
Intelligent Throughput Optimization dataIntegrationUnits Auto, Standard (64), Balanced (128), Maximum (256), Custom (4-256) Start with Auto, increase for large datasets
Degree of Copy Parallelism parallelCopies 1-256 Auto for most; limit to 32 for Fabric Warehouse sink
Partition Option Source settings None, Physical, Dynamic Range Use Dynamic Range for large SQL tables
Enable Staging enableStaging true/false Required for Fabric Warehouse sink
Source Retry Count sourceRetryCount Integer Set 2-3 for transient failures
Fault Tolerance enableSkipIncompatibleRow true/false Enable for non-critical loads

Error Code Quick Reference

Error Meaning Action
HTTP 430 Capacity compute limit reached Reduce concurrent jobs or upgrade SKU
Payload too large Activity config exceeds 896 KB Reduce parameter sizes
TooManyRequestsForCapacity Spark compute or API rate limit Cancel active jobs or wait
Connection timeout Source/sink unreachable Check network, credentials, firewall
Deflate64 unsupported Compression format not supported Re-compress with deflate algorithm

Monitoring Setup

Enable workspace monitoring for ongoing performance analysis:

  1. Go to Workspace Settings > Monitoring
  2. Add a Monitoring Eventhouse and enable Log workspace activity
  3. Query the ItemJobEventLogs table with KQL for pipeline-level insights

Example KQL query for failure trends:

kql
ItemJobEventLogs
| where ItemKind == "Pipeline"
| summarize count() by JobStatus

See workspace-monitoring-setup.md for detailed configuration.

References

  • Copy Activity Tuning Guide
  • Pipeline Stuck Resolution
  • Capacity Throttling Guide
  • Dataflow Optimization
  • Workspace Monitoring Setup
  • remediate Runbook Template

External Resources

Expand your agent's capabilities with these related and highly-rated skills.

Didn't find tool you were looking for?

Be as detailed as possible for better results