Configurer Database Monitoring pour MongoDB auto-hébergé

Database Monitoring offre des informations détaillées sur vos bases de données MongoDB en donnant accès à des métriques essentielles, des opérations lentes, des échantillons d’opérations, des plans d’explication et des changements d’état de réplication. Pour tirer parti de Database Monitoring pour MongoDB, assurez-vous que l’Agent Datadog est installé et configuré pour se connecter à vos instances MongoDB. Ce guide décrit les étapes de configuration de Database Monitoring pour MongoDB auto-hébergé.

Avant de commencer

Versions majeures de MongoDB prises en charge
4.4, 5.0, 6.0, 7.0, 8.0
Éditions MongoDB prises en charge
Communauté, Entreprise
Supported Agent versions
7.58.0+
Performance impact
The default Agent configuration for Database Monitoring is conservative, but you can adjust settings such as the collection interval and operation 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.

Connection strings or SRV strings
Although MongoDB connection strings or SRV strings provide many benefits such as automatic failover and load balancing, the Datadog Agent must connect directly to the MongoDB instance being monitored. If the Agent connects to a different MongoDB instance 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.

Configuration

Pour activer Database Monitoring pour votre base de données :

  1. Accorder à l’Agent l’accès à vos instances MongoDB
  2. Installer et configurer l’Agent

Accorder à l’Agent l’accès à vos instances MongoDB

L’Agent Datadog nécessite un accès en lecture seule à l’instance MongoDB pour collecter des statistiques et des requêtes.

    Dans un shell Mongo, authentifiez-vous sur l’instance MongoDB, créez un utilisateur en lecture seule pour l’Agent Datadog dans la base de données admin et accordez les autorisations requises :

    # Authentifiez-vous en tant qu'utilisateur admin.
use admin
db.auth("admin", "<YOUR_MONGODB_ADMIN_PASSWORD>")

# Créez l'utilisateur pour l'Agent Datadog.
db.createUser({
  "user": "datadog",
  "pwd": "<UNIQUE_PASSWORD>",
  "roles": [
    { role: "read", db: "admin" },
    { role: "read", db: "local" },
    { role: "clusterMonitor", db: "admin" }
  ]
})

    Accordez des autorisations supplémentaires à l’utilisateur datadog dans les bases de données que vous souhaitez surveiller :

    db.grantRolesToUser("datadog", [
  { role: "read", db: "mydatabase" },
  { role: "read", db: "myotherdatabase" }
])

    Vous pouvez également accorder le rôle readAnyDatabase à l’utilisateur datadog dans la base de données admin pour surveiller toutes les bases de données :

    db.grantRolesToUser("datadog", [
  { role: "readAnyDatabase", db: "admin" }
])

    Dans un shell Mongo, authentifiez-vous sur le nœud primaire du replica set, créez un utilisateur en lecture seule pour l’Agent Datadog dans la base de données admin et accordez les autorisations requises :

    # Authentifiez-vous en tant qu'utilisateur admin.
use admin
db.auth("admin", "<YOUR_MONGODB_ADMIN_PASSWORD>")

# Créez l'utilisateur pour l'Agent Datadog.
db.createUser({
  "user": "datadog",
  "pwd": "<UNIQUE_PASSWORD>",
  "roles": [
    { role: "read", db: "admin" },
    { role: "read", db: "local" },
    { role: "clusterMonitor", db: "admin" }
  ]
})

    Accordez des autorisations supplémentaires à l’utilisateur datadog dans les bases de données que vous souhaitez surveiller :

    db.grantRolesToUser("datadog", [
  { role: "read", db: "mydatabase" },
  { role: "read", db: "myotherdatabase" }
])

    Vous pouvez également accorder le rôle readAnyDatabase à l’utilisateur datadog dans la base de données admin pour surveiller toutes les bases de données :

    db.grantRolesToUser("datadog", [
  { role: "readAnyDatabase", db: "admin" }
])
    1. Pour chaque shard de votre cluster, connectez-vous au nœud primaire du shard, créez un utilisateur en lecture seule pour l’Agent Datadog dans la base de données admin et accordez les autorisations requises :
    # Authentifiez-vous en tant qu'utilisateur admin.
use admin
db.auth("admin", "<YOUR_MONGODB_ADMIN_PASSWORD>")

# Créez l'utilisateur pour l'Agent Datadog.
db.createUser({
  "user": "datadog",
  "pwd": "<UNIQUE_PASSWORD>",
  "roles": [
    { role: "read", db: "admin" },
    { role: "read", db: "local" },
    { role: "clusterMonitor", db: "admin" }
  ]
})

    Accordez des autorisations supplémentaires à l’utilisateur datadog dans les bases de données que vous souhaitez surveiller :

    db.grantRolesToUser("datadog", [
  { role: "read", db: "mydatabase" },
  { role: "read", db: "myotherdatabase" }
])

    Vous pouvez également accorder le rôle readAnyDatabase à l’utilisateur datadog dans la base de données admin pour surveiller toutes les bases de données :

    db.grantRolesToUser("datadog", [
  { role: "readAnyDatabase", db: "admin" }
])
    1. Suivez les mêmes étapes et créez le même utilisateur depuis un proxy mongos. Cette action crée l’utilisateur local dans les serveurs de configuration et permet une connexion directe.

    Stocker votre mot de passe de manière sécurisée

    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.

    Installer et configurer l’Agent

    Datadog recommande d’installer l’Agent directement sur le host MongoDB, car cela lui permet de collecter diverses données de télémétrie système (CPU, mémoire, disque, réseau) en plus des données de télémétrie spécifiques à MongoDB.

    Créer le fichier de configuration

      To configure the Agent to monitor a standalone MongoDB instance, use the following configuration block:

      init_config:
instances:
    ## @param hosts - required
    ## Specify the hostname, IP address, or UNIX domain socket
    ## of the standalone mongod instance. If the port number
    ## is not specified, the default port 27017 is used.
    #
  - hosts:
      - <HOST>:<PORT>

    ## @param username - string - optional
    ## The username to use for authentication.
    #
    username: datadog

    ## @param password - string - optional
    ## The password to use for authentication.
    #
    password: "ENC[datadog_user_database_password]"

    ## @param options - mapping - optional
    ## Connection options. For a complete list, see:
    ## https://docs.mongodb.com/manual/reference/connection-string/#connections-connection-options
    #
    options:
      authSource: admin

    ## @param tls - boolean - optional
    ## Set to true to connect to the MongoDB instance using TLS.
    #
    tls: true

    ## @param dbm - boolean - optional
    ## Set to true to enable Database Monitoring.
    #
    dbm: true

    ## @param cluster_name - string - optional
    ## The unique name of the cluster to which the monitored MongoDB instance belongs.
    ## Used to group MongoDB instances in a MongoDB cluster.
    ## cluster_name should follow Datadog tags naming conventions. See:
    ## https://docs.datadoghq.com/extend/guide/what-best-practices-are-recommended-for-naming-metrics-and-tags/#rules-and-best-practices-for-naming-tags
    ## Required when `dbm` is enabled.
    #
    cluster_name: <MONGO_CLUSTER_NAME>

    ## @param reported_database_hostname - string - optional
    ## Set the reported database hostname for the connected MongoDB instance.
    ## This value overrides the MongoDB hostname detected by the Agent
    ## from the MongoDB admin command serverStatus.host.
    #
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>

    ## @param additional_metrics - list of strings - optional
    ## List of additional metrics to collect. Available options are:
    ## - metrics.commands: Use of database commands
    ## - tcmalloc: TCMalloc memory allocator
    ## - top: Usage statistics for each collection
    ## - collection: Metrics of the specified collections
    #
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]

    ## @param collections_indexes_stats - boolean - optional
    ## Set to true to collect index statistics for the specified collections.
    ## Requires `collections` to be set.
    #
    collections_indexes_stats: true

    ## @param database_autodiscovery - mapping - optional
    ## Enable database autodiscovery to automatically collect metrics from all your MongoDB databases.
    #
    database_autodiscovery:
      ## @param enabled - boolean - required
      ## Enable database autodiscovery.
      #
      enabled: true

      ## @param include - list of strings - optional
      ## List of databases to include in the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to include all databases starting with "mydb", use "^mydb.*".
      ## By default, include is set to ".*" and all databases are included.
      #
      include:
        - "^mydb.*"

      ## @param exclude - list of strings - optional
      ## List of databases to exclude from the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to exclude all databases starting with "mydb", use "^mydb.*".
      ## When the exclude list conflicts with include list, the exclude list takes precedence.
      #
      exclude:
        - "^mydb2.*"
        - "admin$"

      ## @param max_databases - integer - optional
      ## Maximum number of databases to collect metrics from. The default value is 100.
      #
      max_databases: 100

      ## @param refresh_interval - integer - optional
      ## Interval in seconds to refresh the list of databases. The default value is 600 seconds.
      #
      refresh_interval: 600

      To monitor a MongoDB replica set, the Agent needs to connect to all members (including the arbiter) of the replica set.

      Use the following configuration block as an example to configure the Agent to connect to a replica set member:

      init_config:
instances:
    ## @param hosts - required
    ## Specify the hostname, IP address, or UNIX domain socket of
    ## a mongod instance as listed in the replica set configuration.
    ## If the port number is not specified, the default port 27017 is used.
    #
  - hosts:
      - <HOST>:<PORT>

    ## @param username - string - optional
    ## The username to use for authentication.
    #
    username: datadog

    ## @param password - string - optional
    ## The password to use for authentication.
    #
    password: "ENC[datadog_user_database_password]"

    ## @param options - mapping - optional
    ## Connection options. For a complete list, see:
    ## https://docs.mongodb.com/manual/reference/connection-string/#connections-connection-options
    #
    options:
      authSource: admin

    ## @param tls - boolean - optional
    ## Set to true to connect to the MongoDB instance using TLS.
    #
    tls: true

    ## @param dbm - boolean - optional
    ## Set to true to enable Database Monitoring.
    #
    dbm: true

    ## @param cluster_name - string - optional
    ## The unique name of the cluster to which the monitored MongoDB instance belongs.
    ## Used to group MongoDB instances in a MongoDB cluster.
    ## cluster_name should follow Datadog tags naming conventions. See:
    ## https://docs.datadoghq.com/extend/guide/what-best-practices-are-recommended-for-naming-metrics-and-tags/#rules-and-best-practices-for-naming-tags
    ## Required when `dbm` is enabled.
    #
    cluster_name: <MONGO_CLUSTER_NAME>

    ## @param reported_database_hostname - string - optional
    ## Set the reported database hostname for the connected MongoDB instance.
    ## This value overrides the MongoDB hostname detected by the Agent
    ## from the MongoDB admin command serverStatus.host.
    #
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>


    ## @param additional_metrics - list of strings - optional
    ## List of additional metrics to collect. Available options are:
    ## - metrics.commands: Use of database commands
    ## - tcmalloc: TCMalloc memory allocator
    ## - top: Usage statistics for each collection
    ## - collection: Metrics of the specified collections
    #
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]

    ## @param collections_indexes_stats - boolean - optional
    ## Set to true to collect index statistics for the specified collections.
    ## Requires `collections` to be set.
    #
    collections_indexes_stats: true

    ## @param database_autodiscovery - mapping - optional
    ## Enable database autodiscovery to automatically collect metrics from all your MongoDB databases.
    #
    database_autodiscovery:
      ## @param enabled - boolean - required
      ## Enable database autodiscovery.
      #
      enabled: true

      ## @param include - list of strings - optional
      ## List of databases to include in the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to include all databases starting with "mydb", use "^mydb.*".
      ## By default, include is set to ".*" and all databases are included.
      #
      include:
        - "^mydb.*"

      ## @param exclude - list of strings - optional
      ## List of databases to exclude from the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to exclude all databases starting with "mydb", use "^mydb.*".
      ## When the exclude list conflicts with include list, the exclude list takes precedence.
      #
      exclude:
        - "^mydb2.*"
        - "admin$"

      ## @param max_databases - integer - optional
      ## Maximum number of databases to collect metrics from. The default value is 100.
      #
      max_databases: 100

      ## @param refresh_interval - integer - optional
      ## Interval in seconds to refresh the list of databases. The default value is 600 seconds.
      #
      refresh_interval: 600

      An example configuration for a replica set with 1 primary and 2 secondaries is as follows:

      init_config:
instances:
  - hosts:
      - <HOST_REPLICA_1>:<PORT>  # Primary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_REPLICA_2>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_REPLICA_3>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true

      To monitor a MongoDB sharded cluster, the Agent needs to connect to the mongos router(s) and all members of the shards. If you have multiple mongos routers, you can configure the Agent to connect to them for load balancing.

      Use the following configuration block as an example to configure the Agent to connect to a Mongos router:

      init_config:
instances:
    ## @param hosts - required
    ## For a sharded cluster, you need one check instance for each mongod instance in
    ## each shard (including the configsvr shard) as well as one additional check instance
    ## that connects to at least one mongos node.

    ## Specify the hostname, IP address, or UNIX domain socket of the mongod or mongos instance.

    ## If the port number is not specified, the default port 27017 is used.
  - hosts:
      - <HOST>:<PORT>

    ## @param username - string - optional
    ## The username to use for authentication.
    #
    username: datadog

    ## @param password - string - optional
    ## The password to use for authentication.
    #
    password: "ENC[datadog_user_database_password]"

    ## @param options - mapping - optional
    ## Connection options. For a complete list, see:
    ## https://docs.mongodb.com/manual/reference/connection-string/#connections-connection-options
    #
    options:
      authSource: admin

    ## @param tls - boolean - optional
    ## Set to true to connect to the MongoDB instance using TLS.
    #
    tls: true

    ## @param dbm - boolean - optional
    ## Set to true to enable Database Monitoring.
    #
    dbm: true

    ## @param cluster_name - string - optional
    ## The unique name of the cluster to which the monitored MongoDB instance belongs.
    ## Used to group MongoDB instances in a MongoDB cluster.
    ## cluster_name should follow Datadog tags naming conventions. See:
    ## https://docs.datadoghq.com/extend/guide/what-best-practices-are-recommended-for-naming-metrics-and-tags/#rules-and-best-practices-for-naming-tags
    ## Required when `dbm` is enabled.
    #
    cluster_name: <MONGO_CLUSTER_NAME>

    ## @param reported_database_hostname - string - optional
    ## Set the reported database hostname for the connected MongoDB instance.
    ## This value overrides the MongoDB hostname detected by
    ## the Agent from the MongoDB admin command serverStatus.host.
    #
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>

    ## @param additional_metrics - list of strings - optional
    ## List of additional metrics to collect. Available options are:
    ## - metrics.commands: Use of database commands
    ## - tcmalloc: TCMalloc memory allocator
    ## - top: Usage statistics for each collection
    ## - collection: Metrics of the specified collections
    ## - jumbo_chunks: Count and percentage of jumbo chunks. Ignored on mongod instances.
    ## - sharded_data_distribution: Distribution of data in sharded collections.
    #
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection", "jumbo_chunks", "sharded_data_distribution"]

    ## @param collections_indexes_stats - boolean - optional
    ## Set to true to collect index statistics for the specified collections.
    ## Requires `collections` to be set.
    #
    collections_indexes_stats: true

    ## @param database_autodiscovery - mapping - optional
    ## Enable database autodiscovery to automatically collect metrics from all your MongoDB databases.
    #
    database_autodiscovery:
      ## @param enabled - boolean - required
      ## Enable database autodiscovery.
      #
      enabled: true

      ## @param include - list of strings - optional
      ## List of databases to include in the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to include all databases starting with "mydb", use "^mydb.*".
      ## By default, include is set to ".*" and all databases are included.
      #
      include:
        - "^mydb.*"

      ## @param exclude - list of strings - optional
      ## List of databases to exclude from the autodiscovery. Use regular expressions to match multiple databases.
      ## For example, to exclude all databases starting with "mydb", use "^mydb.*".
      ## When the exclude list conflicts with include list, the exclude list takes precedence.
      #
      exclude:
        - "^mydb2.*"
        - "admin$"

      ## @param max_databases - integer - optional
      ## Maximum number of databases to collect metrics from. The default value is 100.
      #
      max_databases: 100

      ## @param refresh_interval - integer - optional
      ## Interval in seconds to refresh the list of databases. The default value is 600 seconds.
      #
      refresh_interval: 600

      Refer to the Replica Set configuration for an example configuration for connecting to members in each shard and the config server.

      An example configuration for a sharded cluster with 1 mongos router and 2 shards is as follows:

      init_config:
instances:
  ## mongos router
  - hosts:
      - <HOST_MONGOS>:<PORT>
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection", "jumbo_chunks", "sharded_data_distribution"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  ## Shard1
  - hosts:
      - <HOST_SHARD1_1>:<PORT>  # Primary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_SHARD1_2>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_SHARD1_3>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  ## Shard 2
  - hosts:
      - <HOST_SHARD2_1>:<PORT>  # Primary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_SHARD2_2>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  - hosts:
      - <HOST_SHARD2_3>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true
    database_autodiscovery:
      enabled: true
  ## Config server
  - hosts:
      - <HOST_CONFIG_1>:<PORT>  # Primary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    database: config
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
  - hosts:
      - <HOST_CONFIG_2>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    database: config
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
  - hosts:
      - <HOST_CONFIG_3>:<PORT>  # Secondary node
    username: datadog
    password: "ENC[datadog_user_database_password]"
    database: config
    options:
      authSource: admin
    tls: true
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>

      Configurer l’Agent

        Place the MongoDB Agent configuration file created in the previous step in /etc/datadog-agent/conf.d/mongo.d/conf.yaml. See the sample conf file for all available configuration options.

        Once all Agent configuration is complete, restart the Datadog Agent.

        Validate

        Run the Agent’s status subcommand and look for mongo under the Checks section. Navigate to the Database Monitoring for MongoDB 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.

        The MongoDB check is included in the Datadog Agent. No additional installation is necessary.

        Note: The Agent must have read permission on the Docker socket for autodiscovery of labels to work.

        Add the configuration details for the MongoDB check from the previous step in the com.datadoghq.ad.checks label. See the sample conf file for all available configuration options.

        export DD_API_KEY=<DD_API_KEY>
export DD_AGENT_VERSION=7.58.0

docker run -e "DD_API_KEY=${DD_API_KEY}" \
  -v /var/run/docker.sock:/var/run/docker.sock:ro \
  -l com.datadoghq.ad.checks='{
    "mongo": {
      "init_config": {},
      "instances": [{
        "hosts": ["<HOST>:<PORT>"],
        "username": "datadog",
        "password": "<UNIQUE_PASSWORD>",
        "options": {
          "authSource": "admin"
        },
        "dbm": true,
        "cluster_name": "<MONGO_CLUSTER_NAME>",
        "reported_database_hostname": "<DATABASE_HOSTNAME_OVERRIDE>",
        "additional_metrics": ["metrics.commands", "tcmalloc", "top", "collection"],
        "collections_indexes_stats": true,
        "database_autodiscovery": {
          "enabled": true
        }
      }]
    }
  }' \
  datadog/agent:${DD_AGENT_VERSION}

        Validate

        Run the Agent’s status subcommand and look for mongo under the Checks section. Navigate to the Database Monitoring for MongoDB 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 'clusterChecksRunner.enabled=true' \
  --set 'clusterAgent.confd.mongo\.yaml=cluster_check: true
init_config:
instances:
  - hosts:
      - <HOST>:<PORT>
    username: datadog
    password: <UNIQUE_PASSWORD>
    options:
      authSource: admin
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    database_autodiscovery:
      enabled: true
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true' \
  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/mongo.yaml:

        cluster_check: true  # Make sure to include this flag
init_config:
instances:
  - hosts:
      - <HOST>:<PORT>
    username: datadog
    password: "ENC[datadog_user_database_password]"
    options:
      authSource: admin
    dbm: true
    cluster_name: <MONGO_CLUSTER_NAME>
    reported_database_hostname: <DATABASE_HOSTNAME_OVERRIDE>
    database_autodiscovery:
      enabled: true
    additional_metrics: ["metrics.commands", "tcmalloc", "top", "collection"]
    collections_indexes_stats: true

        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: mongodb-datadog-check-instances
  annotations:
    ad.datadoghq.com/service.checks: |
    {
      "mongo": {
        "init_config": {},
        "instances": [{
          "hosts": ["<HOST>:<PORT>"],
          "username": "datadog",
          "password": "ENC[datadog_user_database_password]",
          "options": {
            "authSource": "admin"
          },
          "dbm": true,
          "cluster_name": "<MONGO_CLUSTER_NAME>",
          "reported_database_hostname": "<DATABASE_HOSTNAME_OVERRIDE>",
          "additional_metrics": ["metrics.commands", "tcmalloc", "top", "collection"],
          "collections_indexes_stats": true,
          "database_autodiscovery": {
            "enabled": true
          }
        }]
      }
    }
spec:
  ports:
  - port: 27017
    protocol: TCP
    targetPort: 27017
    name: mongodb

        The Cluster Agent automatically registers this configuration and begins running the MongoDB integration.

        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.

        Validate

        Run the Agent’s status subcommand and look for mongo under the Checks section. Navigate to the Database Monitoring for MongoDB page in Datadog to get started.

        Données collectées

        Métriques

        Consultez la documentation sur l’intégration MongoDB pour obtenir la liste complète des métriques collectées par l’intégration MongoDB.

        Slow operations

        Database Monitoring for MongoDB captures slow operations from either MongoDB slow query logs or the system.profile collection. Slow operations are defined as those taking longer than the slowms threshold set in your MongoDB configuration.

        • With Database Profiling Enabled: When profiling is enabled at levels 1 or 2, Database Monitoring collects slow operations from the system.profile collection.
        • With Database Profiling Disabled: If profiling is disabled, Database Monitoring relies on MongoDB getLog command to gather slow operations from slow query logs.

        Note: The getLog command retrieves the most recent 1024 mongod events. In busy databases with a high volume of slow queries or when the slow query collection interval is set to a higher interval (resulting in less frequent collection), some slow queries may not be captured.

        Operation samples and explain plans

        Database Monitoring for MongoDB gathers operation samples using the currentOp command. This command provides information about operations that are currently being executed on the MongoDB instance. Additionally, Database Monitoring collects explain plans for the read operation samples using the explain command, offering detailed insights into the query execution plans.

        Replication state changes

        Database Monitoring for MongoDB generates an event each time there is a change in the replication state within the MongoDB instance. This ensures that any changes in replication are promptly detected and reported.

        Collection of schemas and indexes

        Database Monitoring for MongoDB collects inferred schemas and indexes of MongoDB collections. This information is used to provide insights into the structure and organization of your collections.

        When analyzing MongoDB collections, Datadog collects inferred schema information by sampling documents using the $sample aggregation stage. From this analysis, only metadata about the schema is gathered and sent to Datadog, including field names, field prevalence (how often each field appears), and their respective data types. Datadog does not collect or transmit the actual content of documents or any customer business data. This ensures that sensitive data remains protected while still providing valuable insights into the structure and organization of your collections.