Connect MongoDB to Datadog in order to:

• Visualize key MongoDB metrics.
• Correlate MongoDB performance with the rest of your applications.

You can also create your own metrics using custom find, count and aggregate queries.

Note: MongoDB v2.6+ is required for this integration.

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

Follow the instructions below to configure this check for an Agent running on a host. For containerized environments, see the Containerized section.

In a Mongo shell, create a read-only user for the Datadog Agent in the admin database:

# Authenticate as the admin user.
use admin
db.auth("admin", "<YOUR_MONGODB_ADMIN_PASSWORD>")

# On MongoDB 2.x, use the addUser command.
db.addUser("datadog", "<UNIQUEPASSWORD>", true)

# On MongoDB 3.x or higher, use the createUser command.
db.createUser({
  "user":"datadog",
  "pwd": "<UNIQUEPASSWORD>",
  "roles" : [
    {role: 'read', db: 'admin' },
    {role: 'clusterMonitor', db: 'admin'},
    {role: 'read', db: 'local' }
  ]
})

1. Edit the mongo.d/conf.yaml file in the conf.d folder at the root of your Agent's configuration directory. See the sample mongo.d/conf.yaml for all available configuration options.

   init_config:
   instances:
     ## @param server - string - required
     ## Specify the MongoDB URI, with database to use for reporting (defaults to "admin")
     ## E.g. mongodb://datadog:LnCbkX4uhpuLHSUrcayEoAZA@localhost:27016/admin
     #
     - server: "mongodb://datadog:<UNIQUEPASSWORD>@<HOST>:<PORT>/<DB_NAME>"
   
       ## @param replica_check - boolean - required - default: true
       ## Whether or not to read from available replicas.
       ## Disable this if any replicas are inaccessible to the agent.
       #
       replica_check: true
   
       ## @param additional_metrics - list of strings - optional
       ## By default, the check collects a sample of metrics from MongoDB.
       ## This  parameter instructs the check to collect additional metrics on specific topics.
       ## 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

2. Restart the Agent.

Available for Agent versions >6.0

1. Collecting logs is disabled by default in the Datadog Agent, enable it in your datadog.yaml file:

   logs_enabled: true

2. Add this configuration block to your mongo.d/conf.yaml file to start collecting your MongoDB logs:

   logs:
     - type: file
       path: /var/log/mongodb/mongodb.log
       service: mongo
       source: mongodb

   Change the service and path parameter values and configure them for your environment. See the sample mongo.yaml for all available configuration options

3. Restart the Agent.

For containerized environments, see the Autodiscovery Integration Templates for guidance on applying the parameters below.

Available for Agent versions >6.0

Collecting logs is disabled by default in the Datadog Agent. To enable it, see Docker log collection.

Run the Agent's status subcommand and look for mongo under the Checks section.

See metadata.csv for a list of metrics provided by this check.

See the MongoDB 3.0 Manual for more detailed descriptions of some of these metrics.

NOTE: The following metrics are NOT collected by default, use the additional_metrics parameter in your mongo.d/conf.yaml file to collect them:

Replication state changes:
This check emits an event each time a Mongo node has a change in its replication state.

mongodb.can_connect:
Returns CRITICAL if the Agent cannot connect to MongoDB to collect metrics, otherwise returns OK.

Need help? Contact Datadog support.

Read our series of blog posts about collecting metrics from MongoDB with Datadog:

• Monitoring MongoDB performance metrics (WiredTiger)
• Monitoring MongoDB performance metrics (MMAP)