Incident Recognition


Managing and handling incidents is the pillar of ITOps functions that directly affects system availability, user satisfaction, and business productivity. Let AI become a part of your DevOps team and use its Incident Recognition capability to zero down on meaningful alerts and cut down on the duration of service downtime.



Incident Recognition

Incident Recognition has become more challenging in Modern IT Operations. Faster development cycles and complex modern deployments have made service reliability challenging for DevOps and SRE teams. Due to the flood of alerts, IT Operations teams are hard put to narrow down on issues and enable quick resolution. With AIOps in the picture, they have access to powerful tools that enable event correlation and automated AI model design for recognition, empowering them to resolve issues faster.

Benefits of Incident Recognition

Automated Root Cause Analysis

Changes in performance metrics alone don't mean much. They have to be understood in the context of dependencies, usage, and topology to be meaningful. That is why AI-based Root Cause Analysis and Incident Recognition combines analysis of KPIs, logs, and traces in the context of topology to create the most meaningful incident reports. AI does the manual leg work on behalf of the ITOps team and saves them hours in detection time, directly impacting their efficiency and service uptime.

Automated Root cause analysis

Better Decision-Making

Understanding incident priority and assignment is as important as recognizing the problem. AI can triage and prioritize incidents faster and choose the right team and person to handle issues. By assigning weightages in the AI algorithm, AI can create confidence levels in its prediction. It uses this to auto-assign the right category of incident and even determine event severity. This leaves only the most unknown, complex issues for humans while automated triage handles all other incidents.

Decision Making

Single Point of Diagnosis

With growing multi-cloud deployments and hybrid cloud architectures, there is a labyrinth of interaction and dependency between all service components in modern enterprise IT. Telemetry data collected from multiple sources often requires multiple tools for analysis. AIOps enables a single point of collection, diagnosis and repair of incidents by correlating information across different observation points. This means your ITOps teams can manage daily operations from a single tool - cutting down on training time and complexity.

Single point of diagnosis
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