Understanding Results
How to interpret Risk Events and RCA Reports
Kosmos analyzes your incident data to surface patterns and prevent recurring issues. Here's how to interpret what you see.
Key Concepts
Risk Events
A Risk Event is a pattern or anomaly Kosmos has detected that may indicate a systemic problem. Think of these as early warnings—signals that something in your delivery process needs attention.
Risk Events are surfaced automatically when Kosmos identifies:
Recurring incident patterns
Correlation between deployments and issues
Unusual spikes or trends in your data
Not every Risk Event requires action. Some may be expected (planned maintenance, known issues). You can dismiss Risk Events that aren't relevant, and Kosmos learns from your feedback.
RCA Reports
When a Risk Event warrants deeper investigation, it can be promoted to an RCA Report (Root Cause Analysis). RCA Reports provide:
Summary: Plain-language explanation of what happened
Correlated Evidence: Linked commits, PRs, tickets, and cases
Timeline: Sequence of events leading to the issue
Recommendations: Suggested preventive actions
Reading the Dashboard
Risk Events View
Status
New, Acknowledged, Dismissed
Severity
High, Medium, Low — based on frequency and impact
Pattern
Description of what Kosmos detected
First Seen
When this pattern first appeared
Occurrences
How many times this pattern has repeated
Actions you can take:
Acknowledge — You're aware and investigating
Promote to RCA — Generate a full root cause analysis
Dismiss — Not relevant; Kosmos will learn from this
RCA Report View
Each RCA Report includes:
1. Executive Summary A 2-3 sentence overview suitable for sharing with leadership.
2. Correlated Evidence Kosmos links related data across your systems:
Jira issues that match the incident pattern
GitHub commits/PRs deployed near the incident time
Salesforce cases from affected customers
3. Root Cause Analysis AI-generated analysis identifying likely causes, including:
What changed before the incident
Which systems or services were affected
Contributing factors (deployment timing, code changes, config updates)
4. Recommendations Actionable next steps to prevent recurrence.
The Correlation Engine
Kosmos's key differentiator is correlation—connecting data points across systems that humans typically analyze in silos.
Example:
A customer reports an issue in Salesforce. Kosmos correlates this with a Jira bug logged the same day and a GitHub deployment 2 hours prior. The RCA shows the deployment introduced a regression affecting that customer's use case.
This cross-system visibility is what enables prevention, not just faster response.
What "Preventative Intelligence" Means
Traditional tools help you respond faster (reduce MTTR). Kosmos helps you prevent incidents from recurring by:
Detecting patterns before they become outages
Correlating deployments with downstream issues
Surfacing systemic risks across your toolchain
The goal: fewer incidents, not just faster fixes.
Questions About Your Results?
Your Kosmos team will walk you through your initial Look Back findings. If you have questions between scheduled calls, reach out to your dedicated contact or email [email protected].
Questions? Contact [email protected] | app.kosmoslabs.ai
© 2026 Kosmos AI Labs, Inc.
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