Share data in the Splunk App for Anomaly Detection
What data is collected
The Splunk App for Anomaly Detection collects the following basic usage information:
Component | Description | Example |
---|---|---|
app.session.schedule_clicked
|
Information entered in the "Schedule" modal in the Job Dashboard. |
|
app.session.manage_alert_clicked
|
When a user clicks "Manage alert" in Anomaly app. |
|
app.session.app_go_to_tab
|
The tab ("Job Dashboard" or "Create a New Job") to which the user changed. |
|
app.session.field_selected
|
The name of the field in the user's data that was selected for anomaly detection. |
|
app.session.alert_trigger_saved
|
The information that evaluates the detected anomalies against the alerting conditions to determine whether or not an email should be sent. |
|
app.session.new_job_go_to_tab
|
The tab ("Job Dashboard" or "Create a New Job") to which the user changed. |
|
app.session.schedule_saved
|
The scheduling details that the user entered for the Job execution. |
|
app.session.new_job_saved
|
Saving of a new job in the app. |
|
app.session.delete_job_clicked
|
User deleted a job. |
|
app.session.detect_anomalies_clicked
|
User clicked on the "Detect Anomalies" button to initiate anomaly detection. |
|
app.session.sensitivity_saved
|
The sensitivity value (low, medium, or high) selected by the user upon operationalization of the AD search. |
|
app.session.create_job_open_in_search_clicked
|
User clicked on the button to open the SPL query in search from within the "Create Job" dialog. |
|
app.session.view_spl_clicked
|
User clicked on the button to open the SPL query in search from the main AD workflow UI. |
|
app.session.delete_job_successful
|
Deleting a job was successful. |
|
app.session.delete_model_artifact_successful
|
Deleting model artifacts associated with a job that was deleted was successful. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
The data health check result. For example, if data contains missing values, or timestamps are unevenly spaced. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
The number of anomalies/ anomalous intervals detected in the data. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
The length of the seasonal/periodic component (if one is found) in the data. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
Whether the user is running the app with Splunk preinstalled dataset or with their own data. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
The top and bottom 5 anomaly confidence scores found in the data. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
How long our custom algorithm took to run. Encompasses all backend computation other than the SPL query execution time. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
The data resolution. The spacing between timestamps, in number of seconds. |
|
app.Splunk_App_for_Anomaly_Detection.anomalyapp
|
Range of the data values. Number of orders of magnitude between highest and lowest value. |
|