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API Reference

MongoDB Metrics with InstrumentalD

The best way to get MongoDB metrics into Instrumental is with InstrumentalD, the fast and reliable server agent created by the Instrumental team. By using InstrumentalD to collect MongoDB metrics, you'll get premade MongoDB graphs and unlock the full power of our Query Language.

Quick Start
Configuring InstrumentalD
MongoDB Metrics Collected
How many metrics can I expect from InstrumentalD?
Dashboard

Quick Start

Check out our Installation Instructions for more details. Otherwise, here's the bare minimum to get up and running.

brew install instrumental/instrumentald/instrumentald
echo 'mongodb = ["localhost:27017"]' >> instrumentald.toml
instrumentald -c instrumentald.toml -k PROJECT_TOKEN

curl https://packagecloud.io/install/repositories/expectedbehavior/instrumental/script.deb.sh | sudo bash
sudo apt-get install instrumentald
sudo echo 'project_token = "PROJECT_TOKEN"' > /etc/instrumentald.toml
sudo echo 'mongodb = ["localhost:27017"]' >> /opt/instrumentald.toml
sudo systemctl start instrumentald

curl https://packagecloud.io/install/repositories/expectedbehavior/instrumental/script.rpm.sh | sudo bash
sudo yum install instrumentald
sudo echo 'project_token = "PROJECT_TOKEN"' > /etc/instrumentald.toml
sudo echo 'mongodb = ["localhost:27017"]' >> /opt/instrumentald.toml
sudo service instrumentald restart

Configuring InstrumentalD

InstrumentalD will collect the metrics below from as many MongoDB servers as configured. Here's a basic example of the MongoDB config:

mongodb = ["mongodb://localhost:27017"]

Everything you need to know about configuring InstrumentalD, including more information about MongoDB config, can be found in the InstrumentalD Configuration docs.

Metrics Collected

All MongoDB metrics collected by InstrumentalD follow this pattern:

mongodb.<mongo server hostname>.<metric>

The following metrics are collected:

Database Thread/Worker Activity Metrics

`active_reads`	Number of threads currently reading
`active_writes`	Number of threads currently writing
`queued_reads`	Number of waiting read operations
`queued_writes`	Number of waiting write operations
`ttl_deletes_per_sec`	Number individual ttl-index deletes, on average, per second
`ttl_passes_per_sec`	Number of scans for ttl-index deletes, on average, per second

Database Operations ("opcounters")

`commands_per_sec`	Number of general commands, on average, per second
`deletes_per_sec`	Number of documents deleted, on average, per second
`flushes_per_sec`	Number of calls to fsync, on average, per second
`getmores_per_sec`	Number of getmore commands against cursors, on average, per second
`inserts_per_sec`	Number of documents inserted, on average, per second
`queries_per_sec`	Number of find commands, on average, per second
`updates_per_sec`	Number of update commands, on average, per second

Network Activity

`net_in_bytes`	Number of bytes of network input
`net_out_bytes`	Number of bytes of network output
`open_connections`	Number of average open connections during the period

Shard Balancing Stats

`jumbo_chunks`	Number of open chunks detected (mongos/mongo config only)

Server Capacity (mmapv1 storage engine)

`mapped_megabytes`	Number of megabytes mapped to files
`non-mapped_megabytes`	Number of megabytes not mapped to files
`page_faults_per_sec`	Number of page faults, on average, per second
`resident_megabytes`	Amount of memory being used by mongodb
`vsize_megabytes`	Virtual size of mapped database - approximately total database size

Server Capacity (wiredTiger storage engine)

`percent_cache_dirty`	Percentage of wiredTiger cache waiting to be written
`percent_cache_used`	Percentage of wiredTiger cache currently in use
`resident_megabytes`	Amount of memory being used by mongodb
`vsize_megabytes`	Virtual size of database - this will be larger than the actual size on disk

Replica Set Monitoring

`repl_commands_per_second`	Commands per second from replset primary
`repl_deletes_per_sec`	Deletes per second from replset primary
`repl_getmores_per_second`	Getmores per second from replset primary
`repl_inserts_per_second`	Inserts per second from replset primary
`repl_queries_per_second`	Queries per second from replset primary
`repl_updates_per_second`	Updates per second from replset primary
`repl_lag`	How far (seconds) this server is behind the replset primary

How many metrics can I expect from InstrumentalD?

InstrumentalD will collect between 22 and 30 unique metrics per MongoDB server configured.

Dashboard

Here are the graphs included in our MongoDB Dashboard. It's a great way to get started visualizing these metrics.