If you haven’t already, check out Arun Ulag’s hero blog “FabCon and SQLCon 2026: Unifying databases and Fabric on a single, complete platform” for a complete look at all of our FabCon and SQLCon announcements across both Fabric and our database offerings.
Introduction
Copy job is the go-to solution in Microsoft Fabric Data Factory for simplified data movement across multiple clouds. With native support for bulk copy, incremental copy, and change data capture (CDC) replication, it can handle a wide range of movement scenarios through an intuitive, easy-to-use experience.Workspace monitoring is a built-in Fabric capability that provides log-level visibility across all items in a workspace. When enabled, it streams execution logs to a Monitoring Eventhouse—a secure, read-only KQL database in your workspace—queryable using KQL (Kusto Query Language) or SQL. Access is limited to workspace users with at least the Contributor role, keeping monitoring data within your governance boundary.
In this article, you’ll learn how Workspace Monitoring for Copy job in Microsoft Fabric delivers end-to-end observability for any data movement from any sources to any destinations—from quick ad-hoc copies to enterprise-scale ingestion across hundreds of data stores and more.
Figure: Screenshot of PBI Report against Fabric Workspace Monitoring metric from Copy job.
Why Workspace Monitoring for Copy job Matters
Data movement is a critical pillar of any modern data platform. As organizations scale from a handful of Copy jobs to hundreds or thousands, the ability to monitor, diagnose, and optimize those operations becomes essential.If you run Copy jobs at scale, Workspace Monitoring helps in several key ways:
- Centralized observability across all Copy jobs - Instead of inspecting Copy jobs one by one in the Fabric, Workspace Monitoring provides a single, queryable log of every Copy job run in the workspace. You can aggregate, filter, slice, and trend across Copy jobs in one place.
- Root-cause analysis for failures - When a Copy job fails, the logs capture the ErrorCode and FailureType for each activity run. With source/destination details and timing, you can quickly determine whether the issue is connectivity, schema mismatch, timeouts, or capacity—without guesswork.
- Performance and throughput analysis - With ThroughputBytesPerSec, DurationMs, DataReadKB, and DataWrittenKB captured per activity, you can spot bottlenecks, track data volumes, and correlate them with throughput across source types and time windows.
- Historical audit trail - Workspace Monitoring retains historical logs in Eventhouse so you can review past runs for compliance, auditing, and capacity planning—especially important for regulated industries.
- Cross-item correlation - Because Workspace Monitoring captures logs for multiple Fabric item types—not just Copy jobs—you can answer end-to-end questions across the data lifecycle. For example: “Did my Copy job CDC replication complete before the Power BI semantic model refreshed?” or “How does ingestion latency into Fabric Lakehouse correlate with Copy job throughput in the same time window?”
- Proactive alerting - With Data Activator, you can build rules on top of monitoring data to get proactive notifications when jobs fail; throughput drops below a threshold, or latency exceeds your SLA.
What gets logged from Copy job in Workspace Monitoring
This section explains how Copy job activity appears in Workspace Monitoring logs.A Copy job can include multiple source-to-destination mappings (tables or files). Each mapping generates a separate activity-run record. For example, if a Copy job moves three source tables to three destination tables, you’ll see three activity-run records per execution—one for each pair.
Each activity-run log entry includes:
| Category | Fields |
|---|---|
| Identity & context | ItemId, ItemName, WorkspaceId, WorkspaceName, CapacityId, Region |
| Run details | CopyJobRunId, RunId, ScheduledTime, StartTime, EndTime, DurationMs, Status |
| Source & destination | SourceType, SourceName, SourceConnectionType, DestinationType, DestinationName, DestinationConnectionType |
| Data movement metrics | RowsRead, RowsWritten, FilesRead, FilesWritten, DataReadKB, DataWrittenKB, ThroughputBytesPerSec |
| Error diagnostics | ErrorCode, FailureType |
How to enable Workspace Monitoring and build reports for Copy job
You can get started with workspace monitoring for Copy job in a few steps:Step 1: Enable Workspace Monitoring
- In your Fabric workspace, open Workspace settings.
- Select the Monitoring tab.
- Turn on Log workspace activity.
Figure: Screenshot of enabling workspace monitoring.
Step 2: Run your Copy jobs
After you enable workspace monitoring, subsequent Copy job runs automatically write to the CopyJobActivityRunDetailsLogs table. No per-job setup is required.
Step 3: Query your logs with KQL
Open the Monitoring KQL database and start exploring your Copy job logs.
For examples, refer to Workspace Monitoring for Copy Job in Microsoft Fabric.
Step 4 (optional): Build a Power BI report
Workspace monitoring is even more useful when you turn logs into dashboards the whole team can use.
Use the Power BI report template (.pbit) as an example. It connects directly to your Monitoring Eventhouse and includes prebuilt visuals for Copy job alongside other Fabric workloads.
To deploy the template:
- Download Fabric Workspace Monitoring Report.pbit from the fabric-toolbox repository.
- Open the template in Power BI Desktop.
- Set the Query URI parameter to your workspace Monitoring Eventhouse KQL database endpoint.
- Publish the report to your Fabric workspace.
Learn more
Ready to get started? Key resources:- Workspace monitoring for Copy job documentation
- Enable workspace monitoring in Microsoft Fabric
- Workspace monitoring overview
- Fabric Workspace Monitoring Report Templates (fabric-toolbox)
- How to monitor a Copy job
Questions or feedback? Let us know in the comment section.