Amazon RDS 上の SQL Server のデータベースモニタリングの設定

データベースモニタリングはこのサイトでサポートされていません。

データベースモニタリングは、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。

データベースでデータベースモニタリングを有効にするには、以下の手順を実行します。

  1. Agent にデータベースへのアクセスを付与する
  2. Agent をインストールする
  3. RDS インテグレーション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
2014、2016、2017、2019
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.

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の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。

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

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。

USE [database_name];
CREATE USER datadog FOR LOGIN datadog;

これは、RDS が CONNECT ANY DATABASE の付与を許可していないため、必要です。Datadog Agent は、データベース固有のファイル I/O 統計情報を収集するために、各データベースに接続する必要があります。

Agent のインストール

AWS はホストへの直接アクセスを許可しないため、Datadog Agent は SQL Server ホストと通信可能な別のホストにインストールする必要があります。Agent のインストールと実行には、いくつかのオプションがあります。

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からです。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 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>,<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.

    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: MSOLEDBSQL

    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.

    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.

    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.

    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.

    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.

    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:

    Command line with Helm

    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"

    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: <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>

    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": "<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.

    Agent の構成例

    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: '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'
    [...]

    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

    RDS インテグレーションをインストールする

    AWS からより包括的なデータベースメトリクスとログを収集するには、RDS インテグレーションをインストールします。

    その他の参考資料

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