- はじめに
- エージェント
- インテグレーション
- Watchdog
- イベント
- ダッシュボード
- モバイルアプリケーション
- インフラストラクチャー
- サーバーレス
- メトリクス
- ノートブック
- アラート設定
- APM & Continuous Profiler
- CI Visibility
- RUM & セッションリプレイ
- データベース モニタリング
- ログ管理
- セキュリティプラットフォーム
- Synthetic モニタリング
- ネットワークモニタリング
- 開発者
- API
- アカウントの管理
- データセキュリティ
- ヘルプ
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。
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。
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;
CREATE LOGIN datadog WITH PASSWORD = '<PASSWORD>';
CREATE USER datadog FOR LOGIN datadog;
GRANT VIEW SERVER STATE to datadog;
GRANT VIEW ANY DEFINITION 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。
USE [database_name];
CREATE USER datadog FOR LOGIN datadog;
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。
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
provider: MSOLEDBSQL
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
provider: 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 17 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>'
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=${DD_API_KEY}" \
-v /var/run/docker.sock:/var/run/docker.sock:ro \
-l com.datadoghq.ad.check_names='["sqlserver"]' \
-l com.datadoghq.ad.init_configs='[{}]' \
-l com.datadoghq.ad.instances='[{
"dbm": true,
"host": "<HOSTNAME>",
"port": <SQL_PORT>,
"connector": "odbc",
"driver": "FreeTDS",
"username": "datadog",
"password": "<PASSWORD>",
"tags": [
"service:<CUSTOM_SERVICE>"
"env:<CUSTOM_ENV>"
]
}]' \
datadoghq/agent:${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'\
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"
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"
}
]
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.
お役に立つドキュメント、リンクや記事: