Creating custom monitors

To create a custom monitor, from Alerts and Diagnostics > Manage alerts in the navigation panel:

1. Click on the New monitor button in the top-right corner of the page to open the monitor configuration.

2. Fill in the fields under the General tab.

3. Define the NQL Query and conditions tab.

   • Including Trigger condition and Scheduling frequency.

4. Configure Notifications via email or webhooks for proactive alert management.

Configuring General monitor settings

Instead of creating a monitor from scratch, Nexthink recommends customizing built-in monitors, as they offer a wider range of features compared to custom monitors.

From the New monitor configuration page, fill in the following fields under the General tab.

Events trigger and Global detection are only available for built-in monitors (system monitors or installed from Nexthink Library).

• Trigger: Custom monitors offer the Schedule trigger method used for periodic checks. Set specific intervals in the scheduling frequency section in the Query and conditions tab.

• Type: Custom monitors offer the following Types of detection modes:

Metric threshold

Metric threshold triggers an alert when the value of one or more metrics reaches a user-defined threshold.

Metric change

Metric change triggers when the current metric value differs from the rolling 7-day global average beyond the configured threshold.

Metric Seasonal Change

Metric seasonal change triggers an alert when the current metric value falls outside its time-of-day baseline from the last 7 days, based on the configured standard deviation band.

You can configure up to 5 custom monitors in total using either Metric change or Metric seasonal change.

You can create up to 50 monitors.

• Name: Provide a meaningful name for the monitor. The system uses this name to send notifications and visualize monitors on the Alerts overview page.

• NQL ID: The system automatically generates a unique identifier from the monitor Name. Use the NQL ID to query this monitor within Nexthink.

  • You can only edit the NQL ID during the monitor creation, using the following characters a-z, 0-9, _.

  • You cannot create a monitor with an NQL ID that was used by a deleted monitor until there are no events in the system still associated with the deleted monitor (30 days max).

• Priority: Set the priority level. The default level is medium.

• Tags: Create custom tags for monitors. This enables you to filter alerts in the Alerts overview and in Webhook integrations. Currently, you can define up to ten tags per monitor.

Defining NQL Query and conditions for a custom monitor

From the monitor configuration page, fill in the following fields under the Query and conditions tab.

If needed, click the Show in Investigations button to view the query investigation results.

1. Write the NQL query to define the metrics to monitor. With NQL, you can:

   • Select one or multiple metrics.

   • Specify the scope using a where clause.

   • Define alert granularity with time aggregation and the by keyword for grouping.

The system displays an error message for NQL queries computing more than 10,000 result contexts/groups. In these cases, reduce granularity—simplify the by clause or add filters—as each group requires its own baseline.

NQL rules and limitations for monitor queries

The NQL query must follow several rules to support monitors:

1. The NQL query for monitors must include a computed or aggregated metric, which means every query requires a compute or summarize clause to be compatible with a monitor.

devices
| with device_performance.system_crashes during past 7d 
| compute 
  total_number_of_system_crashes = number_of_system_crashes.sum()

execution.crashes during past 24h
| summarize total_number_of_crashes = count()

1. Optionally, include more than one computed or aggregated metric in your query to set multiple conditions for triggering the alert.

execution.crashes during past 24h
| summarize 
  total_number_of_crashes = count(), 
  devices_with_crashes = device.count()

1. Use at least one metric to set a threshold for monitoring conditions. Create an additional metric if your original query does not include one.

Not compatible with monitors:

devices
| with antiviruses
| where is_up_to_date == no

Compatible with monitors:

devices
| with antiviruses
| where is_up_to_date == no
| compute device_count = count()

1. Do not add conditions to evaluated metrics at the NQL level. Instead, use the Trigger condition section to define the condition.

Incorrect monitor NQL query:

execution.crashes during past 24h
| summarize total_number_of_crashes = count()
| where total_number_of_crashes >= 10

Correct monitor NQL query with conditions:

execution.crashes during past 24h
| summarize total_number_of_crashes = count()

1. Use the where clause to narrow the scope of your monitor to specific locations, applications and other categories.

execution.crashes during past 24h
| where binary.name == "excel.exe"
| summarize total_number_of_crashes = count()

1. Use summarize... by to define the right granularity for the alert context. In the following example, a single alert will be triggered per binary name.

execution.crashes during past 24h
| summarize total_number_of_crashes = count() by binary.name

Refer to the Detecting issues impacting multiple devices and Detecting issues impacting a single device or user documentation to learn more about defining the NQL query.

1. Define Trigger conditions that activate alerts. Trigger conditions are sensitive to the chosen detection Type for the monitor. Use each metric computed in the NQL query to narrow down the condition.

Trigger conditions for Metric threshold

In trigger conditions for monitors with a Metric threshold detection, the monitor triggers alerts based on relational operators—greater than or equal to, less than or equal to—against the value you set.

The system triggers the alert when all trigger conditions are met.

Trigger conditions for Metric change

In trigger conditions for monitors with Metric change detection:

• The first trigger condition represents the deviation rule—higher or lower—that proportionally compares the current metric to the baseline (7-day global average).

• Additional trigger conditions activate the alert based on relational operators—greater than or equal to, less than or equal to—against the defined threshold.

The system triggers the alert when all trigger conditions are met.

In the example below, the first trigger condition activates an alert when the CPU Usage value doubles the metric average over the last 7 days.

These trigger conditions apply to both Schedule and Events-trigger monitors.

Trigger conditions for Metric seasonal change

In trigger conditions for monitors with Metric seasonal change detection:

• The first trigger condition sets the sensitivity band or range computed the from time-of-day baseline from the last 7 days. The monitor triggers an alert when the current metric value falls outside the selected standard deviation range for that time slot:

  • slightly = one standard deviation (±1σ)

  • moderately = two times the standard deviation (±2σ)

  • highly = three times the standard deviation (±3σ)

• Additional trigger conditions activate the alert based on relational operators—greater than or equal to, less than or equal to—against the defined threshold.

The system triggers the alert when all trigger conditions are met.

In the example below, the first trigger condition activates an alert when the Percentage of failed connections is outside the band two standard deviations (±2σ) from the baseline.

1. Set the Scheduling frequency of the monitor to determine how often the system evaluates the trigger condition.

   • The possible timeframes are 15 min, 1 hour, 3 hours, 6 hours, 12 hours, 24 hours, 48 hours and 7 days. These timeframes depend on the monitor NQL query ( during past clause) and the configured detection method:

     • For Metric change, the scheduling frequency ranges from 15 minutes to several days.

     • For Metric seasonal change, the maximum scheduling frequency is 24 hours, as more than 1-day frequency does not contribute to computing the mean for the same slot across the last 7 days.

Setting an alert Scheduling frequency, for example to 7 days, means the monitor evaluates the alert every 7 days, starting on the 1st of each month.

This may cause the system to trigger alerts sooner than expected, such as one alert on the 28th of a specific month, but triggered again on the 1st of the month after.

How does the NQL query affect the available scheduling timeframes?

The availability of Scheduling frequency timeframes depends on the during past clause and the events defined in the monitor NQL query.

See the following examples to understand how setting monitor query determines the available scheduling frequency:

Monitored events with during past	Minimum frequency	Maximum frequency
device_performance.boots during past 24h	15 min	7 days
device_performance.boots during past 7d	24 h	7 days
session.events during past 1h	15 min	7 days
session.events during past 24h	12h	7 days
execution.events during past 1h	15 min	7 days
execution.events during past 24h	12h	7 days
execution.events during past 7d	7 days	7 days
session.vdi_events during past 1h	15 min	7 days
session.vdi_events during past 7d	24 h	7 days

1. Choose an alert auto-recovery option. In many alert scenarios, the monitor does not need to extend the recovery period by 72 hours, as the Trigger condition is normalized:

   • In these cases, recover alerts immediately after the monitor's first evaluation returns no data due to inactivity.

   • On the contrary, you may decide to wait 72 hours to, for example, account for a weekend break and keep the alert open during this inactivity period—instead of closing and opening a new alert.

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Creating custom monitors for virtual desktops (VDI)

Using built-in Nexthink Library VDI monitors for Alerts requires Nexthink VDI experience.

While built-in monitors for virtual desktops (VDI) provide out-of-the-box functionality with partial customization, you can create custom VDI monitors for specific organizational needs.

Consider the following when creating custom VDI monitors:

• Only the Schedule trigger, with a minimum granularity of 15 minutes is available for custom VDI monitors.

• Use VDI-related NQL tables and fields in the Query and conditions. For example, the query below calculates the average network latency per desktop pool.

  • If needed, you may add trigger conditions to activate an alert when the average latency in the pool exceeds a threshold value, for example, 50ms.

session.vdi_events during past 15min
| where session.vdi_event.network_rtt != null
| summarize average_network_latency = network_rtt.avg(), 
total_number_of_sessions = vdi_session.count() by vdi_session.desktop_pool

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RELATED TOPICS

• Detecting issues impacting multiple devices

• Detecting issues impacting a single device or user

• Nexthink Library

• Product configuration