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User Metrics

Metrics help you to monitor applications. rapyuta.io platform can now collect custom metrics based on user requirement. rapyuta.io also provides Grafana with its custom data source to visualize such metrics.

Suppose a user application requires monitoring, additional metrics apart from the existing system metrics can now be collected to monitor their application.

Device User Metrics

Device user metrics are custom metrics collected from devices to monitor your applications.
For example, a robot.battery_charge metric provides information on the amount of charge present in the battery of the robot and a robot.distance_traveled metric provides information on the distance traveled across the warehouse. Suppose the application fails to send the robot to the charging station in case of low battery, additional information will not be present as the robot might shut itself down. In such a situation you can view the metric robot.battery_charge to conclude the reason for failure.

Rapyuta IO Metrics Collector

For collecting user metrics, the Rapyuta IO Metrics Collector is enabled by default for all ROS device deployments. /io_metrics_collector ROS node will try to contact ROS master, and expose /io_metrics topic. Messages are sent from this ROS topic to the metrics pipeline, which is stored in the cloud. The metrics can be visualized using the Grafana data source. For more information on /io_metrics topic, see /io_metrics ROS topic

Cloud User Metrics

Cloud user metrics are custom metrics collected from Cloud Deployments. They help you analyze your applications that are running on the Cloud.
For example, an HTTP server application uses the request_duration metric to collect information about the number of requests and the request duration. The Deployment ID and Name are automatically added as tags to these metrics. This helps you distinguish metrics of different deployments.

ROS Endpoint

ROS deployments can use the /io_metrics ROS topic for publishing metrics. For more information, see /io_metrics ROS topic.

UDP Endpoint

Use UDP endpoint in applications where speed is more critical and when no connection needs to be established between the source and destination before you transmit data. UDP provides low overhead data transport.
You can send UDP messages to host $IO_METRICS_HOST at port $IO_METRICS_UDP_PORT, where the $IO_METRICS_HOST and $IO_METRICS_UDP_PORT are environment variables that are automatically available for your Deployment Executables.

Following is a sample UDP request using netcat:

echo -n '{"name": "http_duration", "tags": {"method": "GET", "path": "/api/v0"}, "fields": {"seconds": 1.2}}' | netcat -u  $IO_METRICS_HOST $IO_METRICS_UDP_PORT

You can view a complete sample Python application here.

HTTP Endpoint

Use HTTP endpoint for reliable data transfer.
You can send HTTP request to host $IO_METRICS_HOST at port $IO_METRICS_HTTP_PORT, where the $IO_METRICS_HOST and $IO_METRICS_HTTP_PORT are environment variables that are automatically available for your Deployment Executables.

Following is a sample HTTP request using curl:

curl -XPOST $IO_METRICS_HOST:$IO_METRICS_HTTP_PORT/io_metrics --data '{"name": "http_duration", "tags": {"method": "GET", "path": "/api/v0"}, "fields": {"seconds": 1.2}}'

You can view a complete sample Python application here.

rapyuta.io now supports django middleware. It collects the duration metrics for an HTTP request. For more information see, django-riometrics-middleware

/io_metrics ROS topic

ROS Message Types

The ROS message type for /io_metrics uses the ros_monitoring_msgs package, which also has binary Ubuntu packages.
To use them in your ROS applications, add <depend>ros_monitoring_msgs</depend> to the package.xml file as shown in this sample application.
Alternatively, you can manually install it using the following commands.

. /opt/ros/<distro>/setup.bash
sudo apt-get update
sudo apt-get install -y ros-$ROS_DISTRO-ros-monitoring-msgs

Message Fields

Following is a sample python code that defines a metric. You can view a complete sample ROS package here.

MetricList([
    MetricData(
        metric_name='robot.battery_charge',
        unit=MetricData.UNIT_PERCENTAGE,
        value=42,
        dimensions=[
            MetricDimension(name='cycle', value='cycle1'),
        ],
    )
])

The following table describes the message format:

Field Description
metric_name Defines the subsystem/group and the metric field that is being collected.
Format: <group>.<field>
Example: robot.battery_charge, robot.distance_travelled etc.
unit Measurement unit of the metric field.
It can be any string or a predefined unit.
For a list of predefined units, see Commonly used units.
value Float value of the metric. For example, the value for the metric robot.battery_charge can be 10,20,100 etc.
time_stamp It is automatically set using device’s time before sending it to the cloud.
dimensions Key-value pairs to augment metric with relevant data. For example, charge cycle can be set for the metric robot.battery_charge.

These metrics can be visualized using the Grafana data source. For more information, see

Install packaged Grafana data source

To install the packaged Grafana data source:

  1. Execute the following commands to fetch the packaged data source:
    sudo mkdir -p /var/lib/grafana-plugins
    sudo chown $USER:$USER /var/lib/grafana-plugins
    wget -P /tmp https://grafanadatasource.blob.core.windows.net/grafanadatasource/rr-io-datasource-v0.1.0.zip
    unzip /tmp/rr-io-datasource-v0.1.0.zip -d /var/lib/grafana-plugins
    
  2. Add the following to grafana-server’s config. For more information, see Config file locations.
    [paths]
    plugins = /var/lib/grafana-plugins
    [plugins]
    allow_loading_unsigned_plugins = rr-io-datasource
    
  3. Restart Grafana.