Monitoring Azure Database for MySQL

Effective monitoring is crucial for ensuring the health, performance, and availability of your Azure Database for MySQL instances. Azure provides a comprehensive suite of tools and features to help you gain insights into your database's operations.

Key Monitoring Tools and Features

Azure Monitor

Azure Monitor is the foundational service for collecting, analyzing, and acting on telemetry from your Azure and on-premises environments. For Azure Database for MySQL, it provides:

  • Metrics: Real-time numerical values that describe some aspect of your database at a particular time. Common metrics include CPU utilization, memory usage, storage I/O, network traffic, and connection counts.
  • Logs: Diagnostic logs capture events and performance data that can be stored, queried, and analyzed. You can configure logging for server parameters, slow query logs, and general query logs.
  • Alerts: Set up rules to trigger notifications or automated actions when specific metric thresholds are met or log events occur. This is vital for proactive issue detection.
  • Autoscale: Configure rules to automatically adjust the compute resources allocated to your database based on predefined metrics, ensuring optimal performance and cost-efficiency.

Query Performance Insight

Query Performance Insight helps you identify the top database queries by CPU, duration, execution count, or failure count. It provides a detailed view of your query execution, enabling you to pinpoint performance bottlenecks.

Intelligent Insights

Intelligent Insights automatically detects performance anomalies and provides insights and recommendations to help you diagnose and resolve potential database issues.

Configuring Monitoring

Enabling Diagnostic Logs

To leverage log-based analysis, you need to enable diagnostic settings for your Azure Database for MySQL server. This allows you to send logs to:

  • Azure Log Analytics workspace for complex querying and analysis.
  • Azure Storage for long-term archiving.
  • Azure Event Hubs for streaming data to external monitoring solutions.

You can configure this through the Azure portal under the server's "Diagnostic settings" blade.

Setting Up Alerts

Navigate to the "Alerts" section of your Azure Database for MySQL server in the Azure portal. You can create alert rules based on various metrics, such as:

  • CPU Percentage > 90%
  • Memory Percentage > 85%
  • Storage Used Percentage > 90%
  • Connections > 500

Configure action groups to receive notifications via email, SMS, or webhook.

Azure Monitor Dashboard Example
Example of a typical Azure Monitor dashboard for Azure Database for MySQL.

Best Practices for Monitoring

  • Define Key Performance Indicators (KPIs): Identify the most critical metrics for your application's performance and user experience.
  • Establish Baselines: Understand your database's normal performance patterns to easily spot deviations.
  • Configure Meaningful Alerts: Avoid alert fatigue by setting alerts for critical conditions that require immediate attention.
  • Regularly Review Logs: Periodically analyze query logs and slow query logs to identify and optimize inefficient queries.
  • Utilize Query Performance Insight: Make it a habit to check Query Performance Insight, especially after deploying new features or experiencing performance degradation.
  • Monitor Storage Usage: Proactively monitor storage to prevent unexpected service interruptions due to full disks.
Note: Ensure you understand the different pricing tiers for Azure Monitor, especially if you plan to ingest large volumes of logs into Log Analytics.
Tip: Consider using Azure Workbooks to create rich, interactive visual reports for your database monitoring data.

Example: Querying Slow Queries in Log Analytics

You can use Kusto Query Language (KQL) in Azure Log Analytics to analyze slow query logs. Assuming your slow query logs are ingested into a table named AzureDiagnostics and the resource provider is MYSQLSERVERS:

AzureDiagnostics
| where ResourceProvider == "MICROSOFT.DBFORMYSQL" and Category == "MySqlSlowQuery"
| project TimeGenerated, ServerName, DatabaseName, QueryTime, DurationMs, Query
| order by DurationMs desc
| limit 50