Correlation & RCA

Correlation That Never Sleeps

Selector continuously ingests different types of operational data such as logs, metrics, and events and correlates them continuously using AI. No rule writing or static thresholds required.

Temporal and contextual correlation across telemetry

Real-time recommender and causality models

Full-stack correlation from device health to application latency

Go From Symptoms to Solutions, Instantly

Understand not just what happened, but why. Selector enriches raw operational telemetry with topology, configuration, and behavioral data to reveal root causes in plain language.

Correlation across metrics, config, topology, logs, and events

Contextual insights across device, service, infrastructure, and application domains

Config drift detection and historical pattern awareness

Turn Down the Noise, Turn Up the Insights

Say goodbye to alert storms. Selector filters, deduplicates, and correlates alerts to reduce noise, highlight what matters, and focus teams on the true root cause.

Identify and suppress secondary alerts tied to downstream effects – for example, surface the root link-down event behind packet drops and consolidate it into a single RCA ticket

Suppress alerts during maintenance windows to avoid false noise and distractions

Deduplicate repeated alerts using pattern recognition and surface results across the UI, API, and chat integrations

Topology That Tells The Full Story

Easy visualization to investigate issues across your entire environment with intelligent, topology-based visualizations that show ripple effects and upstream/downstream relationships.

Visual correlation across devices, locations, and services

Service-layer topology views with contextual event overlay

Works across hybrid, WAN, and wireless environments

Ask Your Network Anything

Use Selector Copilot to ask questions like “What caused the service degradation in Chicago?” and receive an AI-generated root cause answer with visual evidence.

Natural language RCA summaries and chat integration (Slack, MS Teams)

Interactive queries for RCA, alert history, and remediation steps

Built-in summarization and deep dive explainability

What Makes Selector Different? Here’s the Shortlist

Capability	Traditional Tools	Selector
Correlation	Rule-based or manual	AI-driven, continuous recommender + association models
Root Cause Analysis	Fragmented across tools	Unified, enriched, and contextual RCA engine
Alert Management	Manual tuning	Built-in deduplication and suppression
Topology	Static Maps	Dynamic, cross-domain topology awareness
Usability	Technical, complex UIs	Conversational, explainable Copilot interface
Stack Coverage	Siloed Data	Full-stack visibility from layer 1 to layer 7