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