Performance insight helps you identify the root causes of database performance issues by analyzing active workloads on your PolarDB for PostgreSQL cluster. When your database experiences high load or latency, Performance insight shows you which SQL statements or session types are driving that load and guides you to the corrective action.
Performance insight is part of the diagnostics feature, which integrates capabilities from Database Autonomy Service (DAS).
How it works
Performance insight collects data based on your instance configuration:
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If
performance_schemais enabled, Performance insight collects and analyzes data fromperformance_schema. -
If
performance_schemais disabled, Performance insight collects and analyzes data from active sessions.
Prerequisites
Before you begin, ensure that you have:
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A PolarDB for PostgreSQL cluster
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Access to the PolarDB console
Enable Performance insight
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Log on to the PolarDB console.
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In the upper-left corner, select the region where your cluster is deployed.
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On the Clusters page, click the ID of the cluster you want to manage.
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In the left-side navigation pane, choose Diagnostics and Optimization > Quick Diagnostics.
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Click the Performance Insight tab.
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Click Enable Performance Insight.
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In the dialog box that appears, click Confirm.
Understand the dashboard
After enabling Performance insight, the dashboard shows two sections:
| Section | What it shows | How to use it |
|---|---|---|
| Performance Insight | Time-series charts for metrics such as CPU utilization | Select a time range to isolate an incident window; click Details in the upper-right corner of any metric to drill into that metric |
| Average Active Session | A trend chart of active sessions broken down by session type | Identify which session type dominated load during the incident window; view database workloads from multiple dimensions to identify root causes |
Metric data is available for the latest seven days only.
Diagnose performance issues
Use the following workflow to move from a symptom to a root cause:
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Identify the incident window. In the Performance Insight section, select a time range and look for spikes or sustained elevation in metrics such as CPU utilization. Click Details on any metric to examine it in more detail.
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Identify the dominant session type. In the Average Active Session section, review the trend chart to find which session type accounts for the most load during the incident window.
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Narrow down the workload. In the Average Active Session section, view database workloads from multiple dimensions to isolate the specific sessions or queries driving the issue.
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Take corrective action. Based on your findings, address the identified session type or workload pattern.
Constraints
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Metric data is available for the latest seven days. Data older than seven days is not accessible in the dashboard.