Application Real-Time Monitoring Service:Static thresholds

Scenarios

• Web & HTML5 application: You can configure static thresholds for web & HTML5 applications to monitor key performance metrics, such as Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS). If these metrics encounter anomalies, alerts are triggered to help you quickly locate and fix the anomalies, and improve user experience.

• iOS and Android apps: You can configure static thresholds for iOS and Android apps to monitor key performance metrics, such as resource loading, API calls, crashes, and janks. Automatic reporting of abnormal stacks and crash logs helps you quickly locate and fix the anomalies and improve user experience.

Example:

After a new version of an app was released, the number of application janks significantly increased. In this case, you can configure a static threshold for the number of janks so that you can identify and fix them promptly, thus preventing more users from being affected.

Prerequisites

The application is monitored in RUM. For more information, see Integrate applications.

Procedure

1. Log on to the ARMS console.

2. In the left-side navigation pane, choose Real User Monitoring > Alert rules. On the page that appears, click Create an alert rule.

3. On the Create an alert rule page, specify an alert rule name and set the Alert Detection Type parameter to Threshold Detection.

4. In the Alert Contact section, specify the application, metric type, and filter condition.

   

   Parameter	Description
   Select Applications	Select the application for which you want to create the alert rule. You can select multiple applications or all applications.
   Automatically apply this alert rule to newly created applications	Specify whether to automatically apply this alert rule to applications that are later added to RUM.
   Metric Type	Select the type of the metric that you want to detect. For more information, see Alert metrics. Note The values of the Alert Condition and Filter Condition parameters vary with the value of the Metric Type parameter.
   Filters	Further filter the metric data to narrow down the monitoring scope. The condition for filtering data related to the dimension. Valid values: Traverse: matches all alerts of the dimension. =/!=: exactly matches or excludes alerts of the dimension based on one or more values. Contain/Do Not Contain: fuzzily matches or excludes alerts of the dimension based on one or more values. Note If you want to display information about a dimension in an alert notification, you must specify the dimension and filter condition. Otherwise, the data is aggregated in the metric query results.

5. In the Alert Rules section, configure the parameters. The following table describes the parameters.

   Parameter	Description
   Alert Triggering Mode	Single Condition: Specify one condition. Multiple Conditions: Set the Alert Triggering Rules parameter to specify multiple conditions. Valid values: Meet All the Following Rules: Alerts are triggered only if all the conditions are met. Meet One of the Following Rules: Alerts are triggered if one of the conditions is met.
   Alert Condition	Configure alert conditions based on the selected metric type. Time Period: Select the time period for triggering alerts. Example: 5. Metric: Select the alert metric. Condition: Select the condition for triggering alerts. Valid values: Greater Than or Equal To, Less Than or Equal To, Month-on-Month Increase %, Month-on-Month Decrease %, Hour-on-Hour Increase %, Hour-on-Hour Decrease %, Day-on-Day Increase %, and Day-on-Day Decrease %. Note In an alert notification, you can evaluate whether the specified static threshold is reasonable and check whether the threshold has recently been triggered. For more information, see the View alert details section.
   Alert Level	The system provides four built-in alert levels. You can configure a notification policy based on the alert level. For example, you can configure phone calls for P1 alerts and DingTalk group notifications for others. P1: critical P2: error P3: warning P4: page
   Enter P4 recommended threshold	You can adjust the threshold based on the metrics shown in the chart preview section. To apply the rule to multiple applications, click the icon next to Application to generate different recommended thresholds for the applications. ARMS uses an intelligent algorithm to generate a recommended threshold based on the historical metric data. For more information, see the Recommended thresholds section.
   Alert Quantity Prediction	View the number of alerts that are expected to be triggered within the time period. Click the number to query the data that is expected to trigger the alerts at the historical points in time. Each time you create or modify an alert rule, we recommend that you use the alert prediction feature. This feature uses an anomaly detection algorithm to analyze historical data and predict the number of alerts within the specified time period. Then, you can adjust a static threshold based on the prediction results. For more information, see the Alert prediction section.

6. Configure the Notification Policy parameter and parameters in the Advanced Alert Settings section.

   Parameter	Description
   Notification Policy	Do Not Specify Notification Policy: If alerts are triggered, no notification is sent. Notifications are sent only when the matching rules of a notification policy is triggered. Specify a notification policy: If you specify a notification policy, ARMS sends notifications by using the notification method specified in the notification policy. You can select an existing notification policy or create a notification policy. For more information, see Create and manage a notification policy.
   Advanced Alert Settings
   No data	This parameter is used to fix data anomalies, such as missing data, abnormal composite metrics, and abnormal period-over-period comparison results. If data anomalies can be fixed, the data is automatically changed to 0 or 1, or the alert is not triggered. For more information, see Terms.

7. Click Save.

View alert details

After you receive an alert notification, you can view the alert details in the ARMS console. In the left-side navigation pane, choose Alert Managament > Alert Event History.

Recommended thresholds

ARMS uses an intelligent algorithm to analyze the historical data and generate recommended static thresholds based on the specified application, interface, and metric. In addition, a chart is generated for preview. You can compare the threshold values and estimated values, and then adjust the threshold values.

Scenarios

• Assume that alerts related to a specific metric are frequently triggered, but the system is running as expected. This may be because the threshold is not properly set, or not suitable for certain applications or interfaces. In this case, you can use the recommended thresholds feature to adjust the thresholds or configure different thresholds for different applications or interfaces.

• Assume that you need to configure different thresholds for a metric of a large number of applications and interfaces. You can use the intelligent algorithm and quickly configure recommended thresholds for the applications and interfaces.

Implementation

After you click Enter P4 recommended threshold, ARMS automatically pulls the metric data of each application and interface in the last three days. Then, ARMS uses the N-sigma algorithm to calculate the average value and variance for each metric. Assume that your business keeps steady and metrics are normally distributed. The probability of three standard deviations is low. In this case, a recommended threshold can be generated based on the average value and fluctuation of the metric within the last three days.

Among the severity levels, P4 has the lowest severity. A recommended P4 threshold indicates that the metric is slightly abnormal. You can take into account the P4 threshold and configure thresholds for other severity levels, including P1, P2, and P3.

Alert quantity prediction

The alert quantity prediction feature uses an algorithm to analyze historical data, display the time when historical alerts occur, and then predicts the number of alerts within a specified period of time. The feature helps you configure static thresholds or improve alert sensitivity for dynamic thresholds.

Implementation

Based on metric data in the last 24 hours, ARMS calculates the number of times that each threshold of a metric is exceeded to predict the quantity of alerts in the future. In addition, ARMS provides the metric details, including the specific time when each threshold is exceeded. You can adjust thresholds based on your business requirements.