セルフホスト SQL Server のデータベースモニタリングの設定

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Database Monitoring は、クエリメトリクス、クエリサンプル、実行計画、データベースの状態、フェイルオーバー、イベントを公開することで、Microsoft SQL Server データベースを詳細に可視化します。

データベースで Database Monitoring を有効にするには、以下の手順を実行します。

Agent にアクセスを付与する
Agent をインストールする

はじめに

サポートされている SQL Server バージョン: 2012、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 Datadog 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. If the Agent connects to different hosts while it is running (as in the case of failover, load balancing, and so on), the Agent calculates the difference in statistics between two hosts, producing inaccurate metrics.
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.

Agent にアクセスを付与する

Datadog Agent が統計やクエリを収集するためには、データベースサーバーへの読み取り専用のアクセスが必要となります。

サーバーに接続するために読み取り専用ログインを作成し、必要な権限を付与します。

CREATE LOGIN datadog WITH PASSWORD = '<PASSWORD>';
CREATE USER datadog FOR LOGIN datadog;
GRANT CONNECT ANY DATABASE to datadog;
GRANT VIEW SERVER STATE to datadog;
GRANT VIEW ANY DEFINITION to datadog;
-- If not using either of Log Shipping Monitoring (available in Agent v7.50+) or
-- SQL Server Agent Monitoring (available in Agent v7.57+), comment out the next three lines:
USE msdb;
CREATE USER datadog FOR LOGIN datadog;
GRANT SELECT to datadog;

“```SQL CREATE LOGIN datadog WITH PASSWORD = ‘’; CREATE USER datadog FOR LOGIN datadog; GRANT CONNECT ANY DATABASE to datadog; GRANT VIEW SERVER STATE to datadog; GRANT VIEW ANY DEFINITION to datadog; – Log Shipping Monitoring (Agent v7.50+ で利用可能) または – SQL Server Agent Monitoring (Agent v7.57+ で利用可能) のいずれも使用しない場合は、 – 次の 3 行をコメントアウトしてください。 USE msdb; CREATE USER datadog FOR LOGIN datadog; GRANT SELECT to datadog;


追加した各アプリケーションデータベースに `datadog` ユーザーを作成します。
```SQL
USE [database_name];
CREATE USER datadog FOR LOGIN datadog;

パスワードを安全に保管

Store your password using secret management software such as Vault. You can then reference this password as ENC[<SECRET_NAME>] in your Agent configuration files: for example, ENC[datadog_user_database_password]. See Secrets Management for more information.

The examples on this page use datadog_user_database_password to refer to the name of the secret where your password is stored. It is possible to reference your password in plain text, but this is not recommended.

Agent のインストール

Agent を SQL Server ホストに直接インストールすることをお勧めします。そうすることで、SQL Server 固有のテレメトリーに加え、様々なシステムテレメトリー (CPU、メモリ、ディスク、ネットワーク) を収集することができるからです。

注: AlwaysOn ユーザーの場合、Agent は別のサーバーにインストールし、リスナーエンドポイントを介してクラスターに接続する必要があります。これは、Availability Group (AG) のセカンダリレプリカに関する情報がプライマリレプリカから収集されるためです。さらに、この方法で Agent をインストールすると、フェイルオーバー時にも Agent を稼働させ続けることができます。 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>,<PORT>'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    # Optional: For additional tags
    tags:  
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>'

To use Windows Authentication, set connection_string: "Trusted_Connection=yes" and omit the username and password fields.

The agent supports SQL Server Browser Service in versions 7.41+. To enable SSBS, provide a port of 0 in the host string: <HOSTNAME>,0.

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.

Supported Drivers

Microsoft ADO

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: MSOLEDBSQL19  # Replace with MSOLEDBSQL for versions 18 and lower

The other two providers, SQLOLEDB and SQLNCLI, are considered deprecated by Microsoft and should no longer be used.

ODBC

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.

Validate

Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.

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>,<PORT>'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: odbc
    driver: '<Driver from the `odbcinst.ini` file>'
    # Optional: For additional tags
    tags:  
      - '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.

Validate

Run the Agent’s status subcommand and look for sqlserver under the Checks section. Navigate to the Databases page in Datadog to get started.

注: AlwaysOn ユーザーの場合、Agent は別のサーバーにインストールし、リスナーエンドポイントを介してクラスターに接続する必要があります。これは、Availability Group (AG) のセカンダリレプリカに関する情報がプライマリレプリカから収集されるためです。さらに、この方法で Agent をインストールすると、フェイルオーバー時にも Agent を稼働させ続けることができます。 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=<AGENT_VERSION>

docker run -e "DD_API_KEY=${DD_API_KEY}" \
  -v /var/run/docker.sock:/var/run/docker.sock:ro \
  -l com.datadoghq.ad.check_names='["sqlserver"]' \
  -l com.datadoghq.ad.init_configs='[{}]' \
  -l com.datadoghq.ad.instances='[{
    "dbm": true,
    "host": "<HOSTNAME>,<PORT>",
    "connector": "odbc",
    "driver": "ODBC Driver 18 for SQL Server",
    "username": "datadog",
    "password": "<PASSWORD>",
    "tags": [
      "service:<CUSTOM_SERVICE>"
      "env:<CUSTOM_ENV>"
    ]
  }]' \
  gcr.io/datadoghq/agent:${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.

Validate

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.

注: AlwaysOn ユーザーの場合、Agent は別のサーバーにインストールし、リスナーエンドポイントを介してクラスターに接続する必要があります。これは、Availability Group (AG) のセカンダリレプリカに関する情報がプライマリレプリカから収集されるためです。さらに、この方法で Agent をインストールすると、フェイルオーバー時にも Agent を稼働させ続けることができます。 If you’re running a Kubernetes cluster, use the Datadog Cluster Agent to enable Database Monitoring. If cluster checks aren’t already enabled, follow these instructions to enable them before proceeding.

Operator

Follow the steps below to set up the SQL Server integration, using the Operator instructions in Kubernetes and Integrations as a reference.

Create or update the datadog-agent.yaml file with the following configuration:

apiVersion: datadoghq.com/v2alpha1
kind: DatadogAgent
metadata:
  name: datadog
spec:
  global:
    clusterName: <CLUSTER_NAME>
    site: <DD_SITE>
    credentials:
      apiSecret:
        secretName: datadog-agent-secret
        keyName: api-key

  features:
    clusterChecks:
      enabled: true

  override:
    nodeAgent:
      image:
        name: agent
        tag: <AGENT_VERSION>

    clusterAgent:
      extraConfd:
        configDataMap:
          sqlserver.yaml: |-
            cluster_check: true # Required for cluster checks
            init_config:
            instances:
            - host: <HOSTNAME>,<PORT>
              username: datadog
              password: 'ENC[datadog_user_database_password]'
              connector: 'odbc'
              driver: 'ODBC Driver 18 for SQL Server'
              dbm: true
              # Optional: For additional tags
              tags:  
                - 'service:<CUSTOM_SERVICE>'
                - 'env:<CUSTOM_ENV>'

Apply the changes to the Datadog Operator using the following command:
```
kubectl apply -f datadog-agent.yaml
```

Helm

Complete the following steps to install the Datadog Cluster Agent on your Kubernetes cluster. Replace the values to match your account and environment.

Complete the Datadog Agent installation instructions for Helm.

Update your YAML configuration file (datadog-values.yaml in the Cluster Agent installation instructions) to include the following:

clusterAgent:
  confd:
    sqlserver.yaml: |-
      cluster_check: true # Required for cluster checks
      init_config:
      instances:
      - dbm: true
        host: <HOSTNAME>,<PORT>
        username: datadog
        password: 'ENC[datadog_user_database_password]'
        connector: 'odbc'
        driver: 'ODBC Driver 18 for SQL Server'
        # Optional: For additional tags
        tags: 
          - 'service:<CUSTOM_SERVICE>'
          - 'env:<CUSTOM_ENV>'      

  clusterChecksRunner:
    enabled: true

Deploy the Agent with the above configuration file from the command line:
```
helm install datadog-agent -f datadog-values.yaml datadog/datadog
```

For Windows, append --set targetSystem=windows to the helm install command.

Configure with mounted files

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>
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: 'odbc'
    driver: 'ODBC Driver 18 for SQL Server'
    # Optional: For additional tags  
    tags: 
      - 'service:<CUSTOM_SERVICE>'
      - 'env:<CUSTOM_ENV>'

Configure with Kubernetes service annotations

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>",
          "username": "datadog",
          "password": "ENC[datadog_user_database_password]",
          "connector": "odbc",
          "driver": "ODBC Driver 18 for SQL Server",
          "tags": ["service:<CUSTOM_SERVICE>", "env:<CUSTOM_ENV>"]  
        }
      ]      
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.

Agent の構成例

Connecting with DSN using the ODBC driver on Linux

Locate the odbc.ini and odbcinst.ini files. By default, these are placed in the /etc directory when installing ODBC.
Copy the odbc.ini and odbcinst.ini files into the /opt/datadog-agent/embedded/etc folder.

Configure your DSN settings as follows:

odbcinst.ini must provide at least one section header and ODBC driver location.

Example:

[ODBC Driver 18 for SQL Server]
Description=Microsoft ODBC Driver 18 for SQL Server
Driver=/opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18.3.so.2.1
UsageCount=1

odbc.ini must provide a section header and a Driver path that matches odbcinst.ini.

Example:

[datadog]
Driver=/opt/microsoft/msodbcsql18/lib64/libmsodbcsql-18.3.so.2.1

Update the /etc/datadog-agent/conf.d/sqlserver.d/conf.yaml file with your DSN information.

Example:

instances:
  - dbm: true
    host: 'localhost,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: 'odbc'
    driver: 'ODBC Driver 18 for SQL Server' # This is the section header of odbcinst.ini
    dsn: 'datadog' # This is the section header of odbc.ini

Restart the Agent.

Using AlwaysOn

For AlwaysOn users, the Agent should be installed on each replica server and connected directly to each replica. The full set of AlwaysOn telemetry is collected from each individual replica, in addition to host-based telemetry (CPU, disk, memory, and so on) for each server.

instances:
  - dbm: true
    host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    database_metrics:
      # If Availability Groups is enabled
      ao_metrics:
        enabled: true
      # If Failover Clustering is enabled
      fci_metrics:
        enabled: true

Monitoring SQL Server Agent Jobs

To enable monitoring of SQL Server Agent jobs, the Datadog Agent must have access to the [msdb] database.

SQL Server Agent Jobs monitoring is not available for Azure SQL Database.

Monitoring of SQL Server Agent jobs is supported on SQL Server versions 2016 and newer. Starting from Agent v7.57, the Datadog Agent can collect SQL Server Agent job metrics and histories. To enable this feature, set enabled to true in the agent_jobs section of the SQL Server integration configuration file. The collection_interval and history_row_limit fields are optional.

instances:
  - dbm: true
    host: 'shopist-prod,1433'
    username: datadog
    password: '<PASSWORD>'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    agent_jobs:
      enabled: true
      collection_interval: 15
      history_row_limit: 10000

Collecting schemas

Starting from Agent v7.56, the Datadog Agent can collect schema information from SQLServer databases running SQLServer 2017 or higher. To enable this feature, use the schemas_collection option. Schemas are collected on databases for which the Agent has CONNECT access.

To collect schema information from RDS instances, you must grant the datadog user explicit CONNECT access to each database on the instance. For more information, see Grant the Agent access.

Use the database_autodiscovery option to avoid specifying each logical database. See the sample sqlserver.d/conf.yaml for more details.

init_config:
instances:
 # This instance detects every logical database automatically
  - dbm: true
        host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    database_autodiscovery: true
    schemas_collection:
      enabled: true
    database_metrics:
      # Optional: enable metric collection for indexes
      index_usage_metrics:
        enabled: true
# This instance only collects schemas and index metrics from the `users` database
  - dbm: true
        host: 'shopist-prod,1433'
    username: datadog
    password: 'ENC[datadog_user_database_password]'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    database: users
    schemas_collection:
      enabled: true
    database_metrics:
      # Optional: enable metric collection for indexes
      index_usage_metrics:
        enabled: true

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: 'ENC[datadog_user_database_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: 'ENC[datadog_user_database_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: 'ENC[datadog_user_database_password]'
    tags:
      - 'env:prod'
      - 'team:team-discovery'
      - 'service:example-service'
    [...]

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: 'ENC[datadog_user_database_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: 'ENC[datadog_user_database_password]'
    reported_hostname: products-primary
  - dbm: true
    host: 'localhost,1433'
    connector: adodbapi
    adoprovider: MSOLEDBSQL
    username: datadog
    password: 'ENC[datadog_user_database_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

参考資料

お役に立つドキュメント、リンクや記事:

基本的な SQL Server インテグレーションドキュメント

よくある問題のトラブルシューティングドキュメント

デッドロックモニタリングの構成ドキュメント

Datadog で SQL ワークロードの Azure 移行を戦略化するブログ

Datadog Database Monitoring で AlwaysOn のアベイラビリティグループを監視するブログ