Setting Up Database Monitoring for SQL Server on Amazon RDS

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:

1. Configure the AWS integration
2. Grant the Agent access to the database
3. Install the Agent
4. Install the RDS integration

Before you begin

Supported SQL Server versions

2014, 2016, 2017, 2019, 2022

Supported Agent versions

7.41.0+

Performance impact

The default Agent configuration for Database Monitoring is conservative, but you can adjust settings such as the collection interval and query sampling rate to better suit your needs. For most workloads, the Agent represents less than one percent of query execution time on the database and less than one percent of CPU.

Database Monitoring runs as an integration on top of the base Agent (see benchmarks).

Proxies, load balancers, and connection poolers

The Agent must connect directly to the host being monitored. The Agent should not connect to the database through a proxy, load balancer, or connection pooler. While this can be an anti-pattern for client applications, for Database Monitoring each Agent must have knowledge of the underlying host and should stick to a single host for its lifetime, even in cases of failover. If the Datadog Agent connects to different hosts while it is running, then the metrics will be incorrect.

Data security considerations

Read about how Database Management handles sensitive information for information about what data the Agent collects from your databases and how to ensure it is secure.

Configure the AWS integration

Enable Standard Collection in the Resource Collection section of your Amazon Web Services integration tile.

Grant the Agent access

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.

Install the Agent

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.

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>'

connector: adodbapi
adoprovider: MSOLEDBSQL19  # Replace with MSOLEDBSQL for versions 18 and lower

connector: odbc
driver: '{ODBC Driver 18 for SQL Server}'

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>'

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}

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 'clusterChecksRunner.enabled=true' \
  --set "clusterAgent.confd.sqlserver\.yaml=cluster_check: true
init_config:
instances:
  - dbm: true
    host: <HOSTNAME>\,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

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>

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

Example Agent Configurations

Connecting with DSN using the ODBC driver

1. 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
   

2. Copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.

3. 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'
   

4. Restart the Agent.

Using Always On

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

One Agent connecting to multiple hosts

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: 'example-service-primary.example-host.com,1433'
    username: datadog
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    password: '<PASSWORD>'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
  - dbm: true
    host: 'example-service–replica-1.example-host.com,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: '<PASSWORD>'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
  - dbm: true
    host: 'example-service–replica-2.example-host.com,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: '<PASSWORD>'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
    [...]

Storing passwords securely

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]'

Running custom queries

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'

Working with hosts through a remote proxy

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

Discovering ports automatically

SQL Server Browser Service, Named Instances, and other services can automatically detect port numbers. You can use this instead of hardcoding port numbers in connection strings. To use the Agent with one of these services, set the port field to 0.

For example, a Named Instance config:

init_config:
instances:
  - host: <hostname\instance name>
    port: 0

Install the RDS integration

To collect more comprehensive database metrics and logs from AWS, install the RDS integration.

Further reading

Additional helpful documentation, links, and articles:

Basic SQL Server IntegrationDOCUMENTATION Troubleshoot Common IssuesDOCUMENTATION