fabric-data-factory-perf-remediate — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited fabric-data-factory-perf-remediate (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Systematic approach to diagnosing and resolving performance issues in Microsoft Fabric Data Factory pipelines, copy activities, and dataflows.
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 |
Run the diagnostic script to gather baseline metrics:
./scripts/Get-FabricPipelineDiagnostics.ps1 -WorkspaceId "<guid>" -PipelineName "MyPipeline"Or manually collect from the Monitoring Hub:
Based on the bottleneck category, apply the appropriate optimization from the reference guides.
Maximum (or custom 4-256)| 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 |
| 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 | 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 |
Enable workspace monitoring for ongoing performance analysis:
ItemJobEventLogs table with KQL for pipeline-level insightsExample KQL query for failure trends:
ItemJobEventLogs
| where ItemKind == "Pipeline"
| summarize count() by JobStatusSee workspace-monitoring-setup.md for detailed configuration.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.