Atatus monitors SQL Server hosted on Azure Virtual Machines by capturing query metrics, execution plans, and database events. This guide provides the steps needed to enable monitoring and configure your environment for complete observability of your SQL Server instances running on Azure VMs.

1. Grant the Agent Access

For SQL Server running on Azure VM, follow the instructions in the Setting Up Database Monitoring for Self-hosted SQL server documentation to grant the necessary access for monitoring on the Server host VM.

2. Configure the Atatus Agent

Step 1: Configure the SQL Server Integration

Edit the conf.d/sqlserver.d/sqlserver.yml configuration file in your Atatus Agent installation directory:

metrics:
  - hosts:
      - "<MSSQL_SERVER_HOST>"
    port: 1433
    username: <DB_USERNAME>
    password: <DB_PASSWORD>
    dbm: true

Step 2: Restart the Atatus Infra Agent

sudo service atatus-infra-agent restart

Enable Schema Collection for SQL Server 2017+ (Optional)

Atatus Agent can collect schema information from SQL Server 2017 and above.

Requirements

  • Agent v3.4.0 or higher
  • collect_database_info: true
  • collect_settings: true
  • Use auto_discovery: true to auto-detect all databases

Configuration Examples

  • Collect schemas from all logical databases
metrics:
  - hosts:
      - "<MSSQL_SERVER_HOST>"
    port: 1433
    username: <DB_USERNAME>
    password: <DB_PASSWORD>
    dbm: true
    dbm_mssqlserver_options:
      collect_settings:
        enabled: true
      collect_database_info:
        enabled: true
        auto_discovery: true
        # include:
        #   - db_name1
        #   - db_name2
        # exclude:
        #   - db_name1
        #   - db_name2

Collect Metrics Using Custom Queries (Optional)

You can collect custom metrics from SQL Server using the custom_queries option in your configuration.

Configuration Example

metrics:
  - hosts:
      - "<MSSQL_SERVER_HOST>"
    port: 1433
    username: <DB_USERNAME>
    password: <DB_PASSWORD>
    dbm: true
    dbm_mssqlserver_options:
      additional_metrics_options:
# The following is an example of a custom query configuration.                
        custom_queries:
          - query: SELECT age, salary, hours_worked, name FROM hr.employees;
            columns:
              - name: custom.employee_age
                type: gauge
              - name: custom.employee_salary
                type: gauge
              - name: custom.employee_hours
                type: count
              - name: name
                type: tag
            tags:
              - 'table:employees'
        max_custom_queries: 20