Introducing SQL Pool Insights in Microsoft Fabric Data Warehouse

[Mariyaali]

SQL Pool Insights is a powerful new monitoring capability in Microsoft Fabric Data Warehouse designed to give you actionable insights into SQL pool performance and resource utilization. This feature is part of the Query Insights (QI) schema, extending the monitoring experience customers already know and love.

SQL Pool Insights addresses a long-standing customer need: understanding whether your pools are under pressure and how configuration changes impact workloads.
With SQL Pool Insights, you can now track resource allocation, monitor pressure events, and correlate performance trends — all within the Query Insights framework.

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Why SQL Pool Insights Matters

Modern analytics workloads demand transparency and control. Until now, customers had limited visibility into how their out-of-the-box pools (SELECT and NON SELECT) behaved under varying conditions.
Query Insights already provides historical query execution data and performance metrics.

SQL Pool Insights complements this by adding pool-level telemetry

• Real-time monitoring of pool health and pressure states.
• Historical data for configuration changes and capacity adjustments.
• Event-based logging for pressure periods lasting more than one minute.
• Resource isolation validation between SELECT and NON SELECT pools.

Meaning faster troubleshooting, better capacity planning, and improved performance for your most critical queries.

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Key Capabilities

• OOTB Pool Coverage (Coming Soon): Monitor SELECT and NON SELECT pools today, with support for custom pools.
• Schema Details: Access fields like sql_pool_name, timestamp, max_resource_percentage, and is_pool_under_pressure for granular analysis.
• Correlate Performance Issues: Combine insights from SQL Pool Insights with other Query Insights views (e.g., exec_requests_history, long_running_queries) for a complete picture of query execution and resource usage.

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How it Works

SQL Pool Insights introduces a new system view in Query Insights:

SELECT * FROM queryinsights.sql_pool_insights;

This view logs events whenever:

• Pool configuration changes.
• Workspace capacity SKU changes.
• Pressure state changes persist for at least one minute.

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Example Scenarios

Identify Pressure Periods:

SELECT sql_pool_name, timestamp, is_pool_under_pressure
FROM queryinsights.sql_pool_insights
WHERE sql_pool_name = 'SELECT'
AND timestamp >= DATEADD(hour, -24, GETDATE())
AND is_pool_under_pressure = 1
ORDER BY timestamp DESC;

Visualize Pressure Trends:

SELECT sql_pool_name, 
timestamp, 
is_pool_under_pressure, 
LAG(timestamp) OVER (PARTITION BY sql_pool_name ORDER BY timestamp) AS previous_event, 
DATEDIFF(minute, LAG(timestamp) OVER (PARTITION BY sql_pool_name ORDER BY timestamp), timestamp) AS minutes_since_last_event 
FROM queryinsights.sql_pool_insights 
WHERE sql_pool_name = 'SELECT' 
ORDER BY timestamp;

Correlate Pressure Window with Queries using queryinsights.exec_requests_history

WITH Pool_Pressure_Events AS
(
	SELECT	DISTINCT timestamp
	FROM	queryinsights.sql_pool_insights
	WHERE	is_pool_under_pressure = 1
)
SELECT *
FROM	queryinsights.exec_requests_history AS erh
JOIN	Pool_Pressure_Events AS ppe
ON	ppe.timestamp BETWEEN erh.start_time AND erh.end_time

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When to Use SQL Pool Insights

• Investigate performance bottlenecks.
• Validate resource isolation between workloads.
• Plan capacity changes based on historical trends.
• Troubleshoot slow-running queries by correlating pressure events with queryinsights.exec_requests_history.

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Learn More

Explore the full documentation and start using SQL Pool Insights.
Query Insights in Fabric Data Warehousing