Diagnose Fabric Data Warehouse workloads with the SQL DW operations skill (Generally Available)

Microsoft Employee

25 days ago

When a warehouse slows down, the investigation usually starts with more questions than answers. Was there a capacity spike? Did a specific query suddenly become expensive? Are requests failing, being canceled, or simply taking longer than usual?

Answering those questions often requires switching between the Fabric Capacity Metrics app, Query Insights, and SQL pool diagnostics while manually correlating time ranges across multiple tools. The SQL DW operations skill brings those investigations into a single workflow and is now generally available.

Available through the open-source Microsoft Fabric skills repository, the SQL DW operations skill lets you describe a problem in natural language using a compatible AI coding tool such as GitHub Copilot CLI. The skill runs bounded, read-only diagnostics and returns a structured diagnosis, supporting evidence, recommended actions, and validation steps.

What you can do with the SQL DW operations skill

The SQL DW operations skill helps you:

failure-analysis: Separate failed queries from canceled requests, identify affected workloads, and resolve engine error codes.
resource-consumers: Find recurring resource-consuming query patterns, regressions, and changes in execution volume or per-run cost.
capacity-metrics-correlation: Connect a Capacity Metrics spike to warehouse activity in the same time window.
pool-pressure: Diagnose contention and identify workloads that might benefit from custom SQL pools.
lakehouse-health: Find lakehouse tables with small-file, deleted-row, or checkpoint issues.
query-reference: Use the appropriate read-only system views and Query Insights queries for bounded operational analysis.
scenarios: Combine the diagnostics into guided workflows for common warehouse incidents.

Each response separates the diagnosis, evidence, ruled-out causes, recommendations, and customer follow-ups. Measurements are tied to their source, and zero-row results are treated as valid evidence instead of prompting an invented explanation.

Common use cases

Start with the operational question rather than selecting system views or writing diagnostic SQL.

Figure: GIF depiction of how the SQL DW operations skill connects a natural-language prompt to bounded, read-only diagnostics and customer follow-up actions.

Investigate failed and canceled queries

Analyze failed and canceled queries in SalesWarehouse during the last 24 hours.

The skill uses Query Insights to identify affected users, applications, query patterns, and SQL pools. It resolves failed engine codes through sys.messages and keeps cancellations separate because they can reflect a user-initiated cancellation, a client timeout, or resource pressure.

Explain a performance slowdown

Explain why FinanceWarehouse was slow between 09:00 and 11:00 UTC yesterday.

The skill checks SQL pool pressure, overlapping requests, CPU, elapsed time, and storage scans. It distinguishes contention from a directly expensive query or a broad increase in workload.

Find resource-consuming query patterns

Find the top resource-consuming queries in SalesWarehouse and compare them with the previous seven days.

The skill groups requests by query shape and separates higher execution volume from increased per-run cost, new query patterns, and one-time expensive runs.

Investigate a capacity spike

Use the Fabric Capacity Metrics app to investigate the CU spike from 14:00 to 15:00 UTC, then identify expensive SQL users and query patterns.

Following the warehouse metering update introduced in August 2026, Capacity Metrics shows when consumption occurred and how much was reported based on allocated warehouse compute over time. Query Insights explains what ran during the same period.

The skill discovers the installed Capacity Metrics model, identifies a costly warehouse or SQL analytics endpoint, and analyzes Query Insights requests that overlap its time window. It doesn't join Capacity Metrics operation identifiers to Query Insights statement identifiers. Capacity consumption and warehouse CPU are complementary signals, not interchangeable measurements.

Assess custom SQL pool candidates

Assess whether recurring workloads in SalesWarehouse are candidates for custom SQL pools based on the last 30 days.

If repeated pressure is associated with a consistent application name, such as an ingestion service or reporting application, the skill can recommend testing that workload in a custom SQL pool. It identifies the application to isolate and the pressure, latency, CPU, scan, and failure measures to compare before and after the pilot.

Get started

Prerequisites

Before you start, make sure you have:

GitHub Copilot CLI or another compatible AI coding tool.
An active Fabric warehouse or lakehouse SQL analytics endpoint.
Contributor or higher access to the workspace.
The Microsoft Fabric Capacity Metrics app installed for capacity-spike investigations.

Add the Microsoft Fabric skills marketplace in GitHub Copilot CLI:

/plugin marketplace add microsoft/skills-for-fabric

Install the Fabric skills bundle:

/plugin install fabric-skills@fabric-collection

Then open Copilot CLI in a project folder and describe the warehouse issue you want to investigate. Include the workspace, warehouse or SQL analytics endpoint, and UTC time range when possible.

For detailed permissions, setup, supported scenarios, and diagnostic time limits, see Diagnose warehouse workloads with the SQL DW operations skill.