The Alert Management Training File is a CSV (Comma-Separated Values) file used to train the OpsRamp platform’s machine learning engine to recognize alert patterns and automate alert processing. It enhances alert processing in OpsRamp by enabling machine learning-based automation. It provides a structured way to define how alerts should be correlated, suppressed, snoozed, or escalated based on historical patterns
This file enables intelligent handling of alerts by improving:
- First Response – Automatically suppressing or snoozing alerts based on defined patterns.
- Alert Escalation – Routing alerts to the appropriate support teams by matching alert conditions with escalation policies.
The training file serves as input to predictive models and plays a crucial role in improving incident response accuracy, reducing alert fatigue, and increasing operational efficiency.
The file is structured as a simple table, where each row represents a pattern based on specific alert attributes (such as metric name, resource type, or custom tags). When a new alert is triggered, the system compares it against these patterns to determine the appropriate action.
Note: The Resource Type can be referenced as either:
- Resource Type on the Alert Details page, or
- Resource Type Name on the Resource Details page.
Purpose of the Training File
The training file enables consistent and automated responses to recurring alert patterns. It reduces manual effort and human error by teaching the system how to respond to specific alert scenarios.
The training file can be used in:
- Correlating alerts that follow a known sequence.
- Suppressing or snoozing non-critical alerts.
- Escalating alerts to the appropriate support team based on predefined conditions.
- Minimizing alert noise and improving signal-to-noise ratio.
The file is a CSV that contains rows of alert and resource attribute combinations along with the desired outcomes. When a new alert is generated, the system evaluates it against the training file to determine the most appropriate handling method.
The system applies the row with the most exact attribute matches. If multiple rows match, the system selects the first matching row in the file.
Impact on Incident Management
By leveraging the training file:
- Alerts are processed more intelligently and consistently.
- Incident response times are reduced.
- Operational workflows are streamlined.
- Resources are focused on high-impact alerts rather than routine noise.
The training file plays a central role in configuring both First Response and Alert Escalation policies, contributing to a scalable and resilient alert management strategy.