Database Monitoring provides deep visibility into your Microsoft SQL Server databases by exposing query metrics, query samples, explain plans, database states, failovers, and events.
Do the following steps to enable Database Monitoring with your database:
The Datadog Agent requires read-only access to the database server to collect statistics and queries.
Create a read-only login to connect to your server and grant the required permissions:
USE [master];
CREATE LOGIN datadog WITH PASSWORD = '<PASSWORD>';
GO
--Set context to msdb database and create datadog user
USE [msdb];
CREATE USER datadog FOR LOGIN datadog;
GO
--Switch back to master and grant datadog user server permissions
USE [master];
GRANT VIEW SERVER STATE to datadog;
GRANT VIEW ANY DEFINITION to datadog;
GO
Create the datadog user in each additional application database:
USE [database_name];
CREATE USER datadog FOR LOGIN datadog;
This is required because RDS does not permit granting CONNECT ANY DATABASE. The Datadog Agent needs to connect to each database to collect database-specific file I/O statistics.
Since AWS does not grant direct host access, the Datadog Agent must be installed on a separate host where it is able to talk to the SQL Server host. There are several options for installing and running the Agent.
For AlwaysOn users, the Agent must be installed on a separate server and connected to the cluster through the listener endpoint, as information about Availability Group (AG) secondary replicas is collected from the primary replica. Additionally, installing the Agent in this way helps keep it up and running in the event of a failover.
To start collecting SQL Server telemetry, first install the Datadog Agent.
Create the SQL Server Agent conf file C:\ProgramData\Datadog\conf.d\sqlserver.d\conf.yaml. See the sample conf file for all available configuration options.
init_config:
instances:
- dbm: true
host: '<HOSTNAME>,<SQL_PORT>'
username: datadog
password: '<PASSWORD>'
connector: adodbapi
adoprovider: MSOLEDBSQL
include_ao_metrics: true # Optional: For AlwaysOn users
tags: # Optional
- 'service:<CUSTOM_SERVICE>'
- 'env:<CUSTOM_ENV>'
To use Windows Authentication, set connection_string: "Trusted_Connection=yes" and omit the username and password fields.
Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.
The recommended ADO provider is Microsoft OLE DB Driver. Ensure the driver is installed on the host where the agent is running.
connector: adodbapi
adoprovider: MSOLEDBSQL
The other two providers, SQLOLEDB and SQLNCLI, are considered deprecated by Microsoft and should no longer be used.
The recommended ODBC driver is Microsoft ODBC Driver. Ensure the driver is installed on the host where the Agent is running.
connector: odbc
driver: '{ODBC Driver 18 for SQL Server}'
Once all Agent configuration is complete, restart the Datadog Agent.
Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.
To start collecting SQL Server telemetry, first install the Datadog Agent.
On Linux, the Datadog Agent additionally requires an ODBC SQL Server driver to be installed—for example, the Microsoft ODBC driver. Once an ODBC SQL Server is installed, copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.
Use the odbc connector and specify the proper driver as indicated in the odbcinst.ini file.
Create the SQL Server Agent conf file /etc/datadog-agent/conf.d/sqlserver.d/conf.yaml. See the sample conf file for all available configuration options.
init_config:
instances:
- dbm: true
host: '<HOSTNAME>,<SQL_PORT>'
username: datadog
password: '<PASSWORD>'
connector: odbc
driver: '<Driver from the `odbcinst.ini` file>'
include_ao_metrics: true # Optional: For AlwaysOn users
tags: # Optional
- 'service:<CUSTOM_SERVICE>'
- 'env:<CUSTOM_ENV>'
Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.
Once all Agent configuration is complete, restart the Datadog Agent.
Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.
To configure the Database Monitoring Agent running in a Docker container, set the Autodiscovery Integration Templates as Docker labels on your Agent container.
Note: The Agent must have read permission on the Docker socket for Autodiscovery of labels to work.
Replace the values to match your account and environment. See the sample conf file for all available configuration options.
export DD_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
export DD_AGENT_VERSION=7.35.0
docker run -e "DD_API_KEY=${DD_API_KEY}" \
-v /var/run/docker.sock:/var/run/docker.sock:ro \
-l com.datadoghq.ad.check_names='["sqlserver"]' \
-l com.datadoghq.ad.init_configs='[{}]' \
-l com.datadoghq.ad.instances='[{
"dbm": true,
"host": "<HOSTNAME>",
"port": <SQL_PORT>,
"connector": "odbc",
"driver": "FreeTDS",
"username": "datadog",
"password": "<PASSWORD>",
"include_ao_metrics": true, # Optional: For AlwaysOn users
"tags": [
"service:<CUSTOM_SERVICE>"
"env:<CUSTOM_ENV>"
]
}]' \
gcr.io/datadoghq/agent:${DD_AGENT_VERSION}
Use the service and env tags to link your database telemetry to other telemetry through a common tagging scheme. See Unified Service Tagging on how these tags are used throughout Datadog.
Run the Agent’s status subcommand and look for sqlserver under the Checks section. Alternatively, navigate to the Databases page in Datadog to get started.
If you have a Kubernetes cluster, use the Datadog Cluster Agent for Database Monitoring.
If cluster checks are not already enabled in your Kubernetes cluster, follow the instructions to enable cluster checks. You can configure the Cluster Agent either with static files mounted in the Cluster Agent container, or by using Kubernetes service annotations:
Execute the following Helm command to install the Datadog Cluster Agent on your Kubernetes cluster. Replace the values to match your account and environment:
helm repo add datadog https://helm.datadoghq.com
helm repo update
helm install <RELEASE_NAME> \
--set 'datadog.apiKey=<DATADOG_API_KEY>' \
--set 'clusterAgent.enabled=true' \
--set "clusterAgent.confd.sqlserver\.yaml=cluster_check: true
init_config:
instances:
- dbm: true
host: <HOSTNAME>
port: 1433
username: datadog
password: '<PASSWORD>'
connector: 'odbc'
driver: 'FreeTDS'
include_ao_metrics: true # Optional: For AlwaysOn users
tags: # Optional
- 'service:<CUSTOM_SERVICE>'
- 'env:<CUSTOM_ENV>'\
datadog/datadog"
To configure a cluster check with a mounted configuration file, mount the configuration file in the Cluster Agent container on the path: /conf.d/sqlserver.yaml:
cluster_check: true # Make sure to include this flag
init_config:
instances:
- dbm: true
host: '<HOSTNAME>'
port: <SQL_PORT>
username: datadog
password: '<PASSWORD>'
connector: 'odbc'
driver: 'FreeTDS'
include_ao_metrics: true # Optional: For AlwaysOn users
tags: # Optional
- 'service:<CUSTOM_SERVICE>'
- 'env:<CUSTOM_ENV>
Rather than mounting a file, you can declare the instance configuration as a Kubernetes Service. To configure this check for an Agent running on Kubernetes, create a Service in the same namespace as the Datadog Cluster Agent:
apiVersion: v1
kind: Service
metadata:
name: sqlserver-datadog-check-instances
annotations:
ad.datadoghq.com/service.check_names: '["sqlserver"]'
ad.datadoghq.com/service.init_configs: '[{}]'
ad.datadoghq.com/service.instances: |
[
{
"dbm": true,
"host": "<HOSTNAME>",
"port": "<SQL_PORT>",
"username": "datadog",
"password": "<PASSWORD>",
"connector": "odbc",
"driver": "FreeTDS",
"include_ao_metrics": true, # Optional: For AlwaysOn users
"tags": ["service:<CUSTOM_SERVICE>", "env:<CUSTOM_ENV>"] # Optional
}
]
spec:
ports:
- port: 1433
protocol: TCP
targetPort: 1433
name: sqlserver
The Cluster Agent automatically registers this configuration and begins running the SQL Server check.
To avoid exposing the datadog user’s password in plain text, use the Agent’s secret management package and declare the password using the ENC[] syntax.
Configure the odbc.ini file based on your DSN settings.
Example:
[DATADOG]
Driver=/opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18.1.so.1.1
Server=127.0.0.1
Port=1433
User=datadog
Password=Password
Copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.
Configure the SQL Server integration config to include the DSN.
Example:
instances:
- dbm: true
host: 'localhost,1433'
username: datadog
password: '<PASSWORD>'
connector: 'odbc'
driver: '{ODBC Driver 18 for SQL Server}'
dsn: 'DATADOG'
Restart the agent.
When monitoring Always On clusters, the Agent must be installed on a separate server from the SQL Servers and connect to the cluster through the listener endpoint.
instances:
- dbm: true
host: 'shopist-prod,1433'
username: datadog
password: '<PASSWORD>'
connector: adodbapi
adoprovider: MSOLEDBSQL
include_ao_metrics: true # If Availability Groups is enabled
include_fci_metrics: true # If Failover Clustering is enabled
It is common to configure a single Agent host to connect to multiple remote database instances (see Agent installation architectures for DBM). To connect to multiple hosts, create an entry for each host in the SQL Server integration config. In these cases, Datadog recommends limiting the number of instances per Agent to a maximum of 10 database instances to guarantee reliable performance.
init_config:
instances:
- dbm: true
host: 'products-primary.123456789012.us-east-1.rds.amazonaws.com,1433'
username: datadog
connector: adodbapi
adoprovider: MSOLEDBSQL
password: '<PASSWORD>'
tags:
- 'env:prod'
- 'team:team-discovery'
- 'service:product-recommendation'
- dbm: true
host: 'products–replica-1.us-east-1.rds.amazonaws.com,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: '<PASSWORD>'
tags:
- 'env:prod'
- 'team:team-discovery'
- 'service:product-recommendation'
- dbm: true
host: 'products–replica-2.us-east-1.rds.amazonaws.com,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: '<PASSWORD>'
tags:
- 'env:prod'
- 'team:team-discovery'
- 'service:product-recommendation'
[...]
While it is possible to declare passwords directly in the Agent configuration files, it is a more secure practice to encrypt and store database credentials elsewhere using secret management software such as Vault. The Agent is able to read these credentials using the ENC[] syntax. Review the secrets management documentation for the required setup to store these credentials. The following example shows how to declare and use those credentials:
init_config:
instances:
- dbm: true
host: 'localhost,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: 'ENC[datadog_user_database_password]'
To collect custom metrics, use the custom_queries option. See the sample sqlserver.d/conf.yaml for more details.
init_config:
instances:
- dbm: true
host: 'localhost,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: '<PASSWORD>'
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'
If the Agent must connect to a database host through a remote proxy, all telemetry is tagged with the hostname of the proxy rather than the database instance. Use the reported_hostname option to set a custom override of the hostname detected by the Agent.
init_config:
instances:
- dbm: true
host: 'localhost,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: '<PASSWORD>'
reported_hostname: products-primary
- dbm: true
host: 'localhost,1433'
connector: adodbapi
adoprovider: MSOLEDBSQL
username: datadog
password: '<PASSWORD>'
reported_hostname: products-replica-1
To collect more comprehensive database metrics and logs from AWS, install the RDS integration.
Additional helpful documentation, links, and articles:
