Monitor Network Devices from the Charts Page

The following example configuration describes how you can monitor interface flaps for a single interface.

1. Playbook used: interface-kpis-playbook

2. Example graph configuration:

   

   The example shows a configuration for vMX1 device in a canvas titled Test-canvas3. The query section takes interface flap count (flaps) as field input and computes the mean for flaps in ge-0/0/3 interface. The time series graph in the configuration is captured over 3 hours.

   • In the Query section, the FROM fields show the input for device-group name, device name, and rule, respectively.

   • The SELECT fields contain inputs for a KPI key based on the rule you set earlier. If the rule you selected is interface.statistics/check-interface-flaps, the SELECT field could show options for flap count, flap threshold, and so on.

   • The Aggregation field describes data aggregation computation to be performed on the KPI field data (flap counts in this example) such as mean, median, sum, and so on.

   • The Transformation field (optional) describes computations performed on subsequent values in a single field. For example, rate of change, elapsed time, differences, and so on.

   • The WHERE section allows you to set a condition to filter the field data. You must enter a left operand, a right operand, and a conditional operand such as equal to, matches with, greater than, less than, and so on. The left operand can be either a key or a field name.

     In the example configuration, the condition defined checks if the interface-name is equal to ge-0/0/3.

   • The GROUP BY section allows you to group the filtered data by a time interval you specify and handle output value in cases where no field data is available. You can choose group by time interval from the drop-down list.

     If you set the time interval in GROUP BY field as $_interval, then Grafana sets the time interval for data aggregation based on the number of points received in the time series database (TSDB).

   • In the Visualization section, you can enter the y-axis minimum and maximum values, y-axis label and choose a unit such as bytes, kilobytes, and so on.

     In this example configuration, the Visualization section is not configured.

3. Sample graph panel output:

   

   The graph shows interface flaps for ge/0/0/3 interface in device vMX1.

The following example configuration describes how you can monitor interface flaps for all ’ge’ interfaces on a device in a single graph.

1. Playbook used: interface-kpis-playbook

2. Example graph configuration:

   

   The example shows the configuration for vMX1 device in a canvas titled Test-canvas3. The query section takes interface flap count (flaps) as field input and computes the mean for flaps in all ge interfaces. The time series graph in the configuration is captured over 3 hours.

   • In the Query section, the FROM fields shows the input for device-group name, device name, and rule, respectively.

   • The SELECT fields contain inputs for a KPI key based on the rule that you set earlier. If the rule you selected is interface.statistics/check-interface-flaps, the SELECT field could show options for flap count, flap threshold, and so on.

   • The Aggregation field describes data aggregation computation to be performed on the KPI field data (flap counts in this example) such as mean, median, sum, and so on.

   • The Transformation field (optional) describes computations performed on subsequent values in a single field. For example, rate of change, elapsed time, differences, and so on.

   • The WHERE section allows you to set a condition to filter the field data. You must enter a left operand, a right operand and a conditional operand such as equal to, matches with, greater than, less than, and so on. The left operand can be either a key or a field name.

     In the example configuration, the condition defined checks if the interface-name matches with ge.

   • The GROUP BY section allows you to group the filtered data by a time interval you specify and handle output value in cases where no field data is available. You can choose group by time interval from the drop-down list.

     If you set the time interval in GROUP BY field as $_interval, then Grafana sets the time interval for data aggregation based on the number of points received in TSDB.

   • In the Visualization section, you can enter the y-axis minimum and maximum values, y-axis label and choose unit such as bytes, kilobytes, and so on.

     In this example configuration, the Visualization section is not configured.

3. Sample graph panel output:

   

   The graph shows flap counts of three ge interfaces — ge-0/0/0, ge0/0/1, and ge-0/0/2 in the vMX1 device.

The following example configuration describes how you can monitor system memory usage for all devices in a device group in a single graph.

1. Playbook used: system-kpis-playbook

2. Example graph configuration:

   

   This example configuration shows the query section configured for three devices — vMX1, vMX2, and MX240 — in a single canvas titled Canvas1. The query section takes the routing engine’s system memory buffer (re-memory-buffer) as field input, computes mean for a time interval set by the user or Grafana. The example configuration is set for the time series graph captured over 6 hours.

   • In the Query section, the FROM fields show the input for device-group name, device name, and rule, respectively.

   • The SELECT fields contain inputs for a KPI key based on the rule you set earlier. If the rule you selected is system.memory/check-system-memory, the SELECT field could show options for system memory buffer value, system memory high threshold, system memory low threshold, and so on.

   • The Aggregation field describes data aggregation computation to be performed on the KPI field data (system memory buffer in this example) such as mean, median, sum, and so on.

   • The Transformation field (optional) describes computations performed on subsequent values in a single field. For example, rate of change, elapsed time, differences, and so on.

   • The WHERE section allows you to set a condition to filter the field data. You must enter a left operand, a right operand and a conditional operand such as equal to, matches with, greater than, less than, and so on. The left operand can be either a key or a field name.

     In this example, no conditions are set in the WHERE section.

   • The GROUP BY section allows you to group the filtered data by a time interval you specify and handle output value in cases where no field data is available. You can choose group by time interval from the drop-down list.

     If you set the time interval in GROUP BY field as $_interval, then Grafana sets the time interval for data aggregation based on the number of points received in TSDB.

     In this example configuration, the group by interval is set at 1 minute for vMX1 and vMX2 devices whereas, Grafana would decide the time interval to group by aggregated data for MX240 device.

   • In the Visualization section, you can enter the y-axis minimum and maximum values, y-axis label and choose unit such as bytes, kilobytes, and so on.

     In this example configuration, the Visualization section is not configured.

3. Sample graph panel output:

   

   The graph shows mean system memory buffer values aggregated per minute for vMX1 and vMX2, and for an unknown time interval for MX240 device.

The following example configuration describes how you can monitor RE CPU usage for multiple devices in a single graph.

1. Playbook used: system-kpis-playbook

2. Example graph configuration:

   

   This example configuration shows the query section and visualization section configured for three devices — vMX1, vMX2, and MX240 — in a single canvas titled Canvas1. The query section takes the routing engine’s CPU utilization (re-cpu-utilization) as field input, computes the mean every minute for the three devices, and visualizes the mean CPU utilization per minute as percentage. The example configuration is set for the time series graph captured over 6 hours.

   • In the Query section, the FROM fields shows the input for device-group name, device name, and rule, respectively.

   • The SELECT fields contain inputs for a KPI key based on the rule that you set earlier. If the rule you selected is system.cpu/check-system-cpu, the SELECT field could show options for CPU utilization value, CPU utilization high threshold, CPU utilization low threshold, and so on.

   • The Aggregation field describes data aggregation computation to be performed on the KPI field data (CPU utilization in this example) such as mean, median, sum, and so on.

   • The Transformation field (optional) describes computations performed on subsequent values in a single field. For example, rate of change, elapsed time, differences, and so on.

   • The WHERE section allows you to set a condition to filter the field data. You must enter a left operand, a right operand and a conditional operand such as equal to, matches with, greater than, less than, and so on. The left operand can be either a key or a field name.

     In this example, no conditions are set in the WHERE section.

   • The GROUP BY section allows you to group the filtered data by a time interval you specify and handle output value in cases where no field data is available. You can choose group by time interval from the drop-down list.

     If you set the time interval in GROUP BY field as $_interval, then Grafana sets the time interval for data aggregation based on the number of points received in TSDB.

     In this example configuration, the group by interval is set at 1 minute for vMX1, vMX2, and MX240 devices.

   • In the Visualization section, you can enter the y-axis minimum and maximum values, y-axis label and choose unit such as bytes, kilobytes, and so on.

     In this example configuration, the y-axis range for mean CPU utilization per minute is set on a scale of 0 to 100 percentage.

3. Sample graph panel output:

   

   The graph displays mean CPU utilization in percentage for vMX1, vMX2, and MX240 devices.

The following example configuration describes how you can monitor RE CPU usage for multiple devices side-by-side.

1. Playbook used: system-kpis-playbook

2. Example graph configurations:

   
   

   This example shows separate configurations for two devices — vMX1 and MX240 — in a single canvas titled Canvas1. The query section takes routing engine’s CPU utilization (re-cpu-utilization) as field input, computes the mean every minute for the three devices. These example configurations are set for the time series graph captured over 6 hours.

   • In the Query section, the FROM fields shows the input for device-group name, device name, and rule, respectively.

   • The SELECT fields contain inputs for a KPI key based on the rule that you set earlier. If the rule you selected is system.cpu/check-system-cpu, the SELECT field could show options for CPU utilization value, CPU utilization high threshold, CPU utilization low threshold, and so on.

   • The Aggregation field describes data aggregation computation to be performed on the KPI field data (CPU utilization in this example) such as mean, median, sum, and so on.

   • The Transformation field (optional) describes computations performed on subsequent values in a single field. For example, rate of change, elapsed time, differences, and so on.

   • The WHERE section allows you to set a condition to filter the field data. You must enter a left operand, a right operand and a conditional operand such as equal to, matches with, greater than, less than, and so on. The left operand can be either a key or a field name.

     In this example, no conditions are set in the WHERE section.

   • The GROUP BY section allows you to group the filtered data by a time interval you specify and handle output value in cases where no field data is available. You can choose group by time interval from the drop-down list.

     If you set the time interval in GROUP BY field as $_interval, then Grafana sets the time interval for data aggregation based on the number of points received in TSDB.

   • In the Visualization section, you can enter the y-axis minimum and maximum values, y-axis label and choose unit such as bytes, kilobytes, and so on.

     In these example configurations, the Visualization section is not configured.

3. Sample graph panel output for two configurations:

   

   The canvas titled Canvas1 has two graphs (because of two separate configurations) for the vMX1 and MX240 devices side-by-side.