RMM alerts arrive continuously and require manual triage to decide which ones become tickets. Staff spend hours reading alert details, assessing severity, and manually creating tickets, with inconsistent decisions and frequent duplicates.
Automation reads each alert, applies consistent rules to determine actionability, checks for duplicates, and creates tickets with pre-filled fields. The team focuses only on edge cases that need human judgment.
The full workflow, from trigger to completion.
The automation platform receives an incoming alert from the RMM system via webhook or API polling.
The automation extracts alert fields: endpoint name, severity, alert type, timestamp, and error message.
The automation applies rules to determine if the alert should create a ticket, is a known false positive, or can be auto-resolved. Low-confidence cases are flagged for human review.
The automation queries the ticketing system to see if a ticket for the same endpoint and alert type exists within the last 24 hours.
If no duplicate exists and the alert is actionable, the automation creates a ticket with category, priority, description, and affected endpoint pre-filled.
The automation records the alert ID, ticket ID, timestamp, and severity audit log for compliance and reporting.
The automation sends a summary message to the IT team channel with the ticket link and alert summary.
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