Agent v6 and v7 are composed of a main process responsible for collecting infrastructure metrics, logs, and receiving DogStatsD metrics. The main components to this process are:
Two optional processes are spawned by the Agent if enabled in the
datadog.yaml configuration file:
On Windows the services are listed as:
|datadog-trace-agent||“Datadog Trace Agent”|
|datadog-process-agent||“Datadog Process Agent”|
By default the Agent binds 3 ports on Linux and 4 on Windows and OSX:
|5000||Exposes runtime metrics about the Agent.|
|5001||Used by the Agent CLI and GUI to send commands and pull information from the running Agent.|
|5002||Serves the GUI server on Windows and OSX.|
|8125||Used for the DogStatsD server to receive external metrics.|
The collector gathers all standard metrics every 15 seconds. Agent v6 embeds a Python 2.7 interpreter to run integrations and custom checks.
The Agent forwarder send metrics over HTTPS to Datadog. Buffering prevents network splits from affecting metric reporting. Metrics are buffered in memory until a limit in size or number of outstanding send requests are reached. Afterwards, the oldest metrics are discarded to keep the forwarder’s memory footprint manageable. Logs are sent over an SSL-encrypted TCP connection to Datadog.
In v6, DogStatsD is a Golang implementation of Etsy’s StatsD metric aggregation daemon. It is used to receive and roll up arbitrary metrics over UDP or Unix socket, thus allowing custom code to be instrumented without adding latency. Learn more about DogStatsD.
Agent v5 is composed of four major components, each written in Python running as a separate process:
agent.py): The collector runs checks on the current machine for configured integrations, and captures system metrics, such as memory and CPU.
dogstatsd.py): This is a StatsD-compatible backend server that you can send custom metrics to from your applications.
ddagent.py): The forwarder retrieves data from both DogStatsD and the collector, queues it up, and then sends it to Datadog.
Note: For Windows users, all four Agent processes appear as instances of
ddagent.exe with the description
DevOps’ best friend.
A SupervisorD master process runs as the
dd-agent user, and all forked subprocesses run as the same user. This also applies to any system call (
netstat) initiated by the Datadog Agent. The Agent configuration resides at
/etc/dd-agent/conf.d. All configuration must be readable by
dd-agent. The recommended permissions are 0600 since configuration files contain your API key and other credentials needed to access metrics.
The following ports are open for operations:
|tcp/17123||The forwarder for normal operations|
|tcp/17124||The forwarder for graphite support|
All listening processes are bound by default to
::1 on v3.4.1+ of the Agent. In earlier versions, they were bound to
0.0.0.0 (all interfaces). For information on running the Agent through a proxy see Agent proxy configuration. For information on IP ranges to allow, see Network Traffic.
The recommended number of open file descriptors is 1024. You can see this value with the command
ulimit -a. If you have a hard limitation below the recommended value, for example Shell Fork Bomb Protection, one solution is to add the following in
[supervisord] minfds = 100 # Your hard limit
You can configure the port on which the GUI runs in the
datadog.yaml file. To disable the GUI, set the port’s value to
-1. For Windows and macOS, the GUI is enabled by default and runs on port
5002. For Linux, the GUI is disabled by default.
When the Agent is running, use the
datadog-agent launch-gui command to open the GUI in your default web browser.
Note: The Agent GUI isn’t supported on 32-bit Windows platforms.
Cookies must be enabled in your browser. The GUI generates and saves a token in your browser which is used for authenticating all communications with the GUI server.
To start the GUI, the user must have the required permissions. If you are able to open
datadog.yaml, you are able to use the GUI.
For security reasons, the GUI can only be accessed from the local network interface (
127.0.0.1), therefore you must be on the same host that the Agent is running. That is, you can’t run the Agent on a VM or a container and access it from the host machine.
|Amazon Linux||Amazon Linux 2|
|Debian with systemd||Debian 7 (wheezy)+|
|Debian with SysVinit||Debian 7 (wheezy)+ in Agent 6.6.0+|
|SUSE Enterprise Linux with systemd||SUSE 11 SP4+|
|SUSE Enterprise Linux with SysVinit||SUSE 11 SP4 in Agent 7.16.0+|
|Windows Server||Windows Server 2008 R2+ and Server Core (not Nano Server)|
|Windows Azure Stack HCI OS||All Versions|
|Amazon Linux||Amazon Linux 2|
|Debian||Debian 7 (wheezy)+|
|Kubernetes||Version 1.3 to 1.8|
|SUSE Enterprise Linux||SUSE 11 SP4+|
|Windows Server||Windows Server 2008r2+|
|AIX||AIX 6.1 TL9 SP6, 7.1 TL5 SP3, 7.2 TL3 SP0|
With Agent v6+, the command line interface is based on subcommands. To run a subcommand, first invoke the Agent binary:
<AGENT_BIN_PATH> <SUB_COMMAND> <OPTIONS>
|Run the specified check.|
|Print all configurations loaded & resolved of a running Agent.|
|Execute connectivity diagnosis on your system.|
|Collect a flare and send it to Datadog.|
|Print the current Agent health.|
|Help about any command.|
|Print the hostname used by the Agent.|
|Import and convert configuration files from previous versions of the Agent.|
|Install the Agent within the service control manager.|
|Start the Datadog Agent GUI.|
|Import the registry settings into |
|Remove the Agent from the service control manager.|
|Restart the Agent.|
|Restart the Agent within the service control manager.|
|Start the Agent.|
|Start the Agent within the service control manager.|
|Print the current Agent status.|
|Stop the Agent.|
|Stop the Agent within the service control manager.|
|Print version info.|
Note: Some options have their own set of flags and options detailed in a help message. For example, to see how to use the
check subcommand, run:
<AGENT_BIN_PATH> check --help
An example of the Datadog Agent resource consumption is below. Tests were made on an AWS EC2 machine
c5.xlarge instance (4 VCPU/ 8GB RAM). The vanilla
datadog-agent was running with a process check to monitor the Agent itself. Enabling more integrations may increase Agent resource consumption.
Enabling JMX Checks forces the Agent to use more memory depending on the number of beans exposed by the monitored JVMs. Enabling the trace and process Agents increases the resource consumption as well.
Note: Since v5.15 of the container Agent, it is recommended to set container resources to at least 256MB due to an added memory cache – upping the limit is not to account for baseline usage but rather to accommodate temporary spikes. Agent 6 has a much more limited memory footprint.
The results below are obtained from a collection of 110KB of logs per seconds from a file with the HTTP forwarder enabled. It shows the evolution of resource usage for the different compression levels available.
To manually update the Datadog Agent core between two minor versions on a given host, run the corresponding install command for your platform.
Note: If you want to manually update one specific Agent integration refer to the Integration Management guide.
Edit the Agent’s main configuration file,
datadog.yaml, to set the
site parameter (defaults to