Intelligent Root Cause Analysis

Find Root Causes in Seconds,
Not Hours

Aurora's AI-powered root cause analysis automatically investigates incidents across your entire infrastructure, giving you instant answers when things go wrong.

How Aurora Investigates Incidents

Alert Integration
Connect Aurora to your monitoring platforms like PagerDuty, DataDog, New Relic, and Grafana. When an alert fires, Aurora automatically begins investigating the root cause.
Kubernetes Deep Dive
Aurora monitors your K8s clusters in real-time, tracking pod crashes, resource exhaustion, failed deployments, and configuration issues across all your namespaces.
Infrastructure Knowledge Graph
Aurora builds a live graph of your entire cloud infrastructure showing how resources depend on each other. When an incident occurs, Aurora traces the problem through your dependency chain.
Agentic Investigation
Aurora's AI agents work autonomously to investigate incidents. They query logs, check metrics, analyze recent changes, and correlate events to pinpoint the exact root cause.

Automated Investigation Workflow

1
Alert Detection
Aurora receives an alert from your monitoring platform indicating a service degradation or failure
2
Context Gathering
Aurora immediately gathers context: recent deployments, infrastructure changes, resource metrics, and related logs
3
Dependency Analysis
Using the infrastructure knowledge graph, Aurora identifies which upstream or downstream services might be affected
4
Root Cause Identification
Aurora's AI correlates all the data and presents you with the root cause, timeline, and suggested remediation steps

Works With Your Existing Tools

Aurora integrates seamlessly with the monitoring and observability tools you already use

PagerDuty
DataDog
New Relic
Grafana
Prometheus
Splunk
CloudWatch
Azure Monitor

Stop Spending Hours on Root Cause Analysis

Let Aurora's AI agents do the investigation while you focus on fixing the issue

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