Track Core Web Vitals from live browser sessions across Vue.js, Angular, React, and Next.js applications, with a direct path from a slow page to its backend trace.
Core Web Vitals are the field metrics that describe how a page actually feels to the people loading it: how quickly the main content appears, how stable the layout stays, and how fast the page responds to interaction. Core Web Vitals monitoring is the practice of capturing those metrics from real visitor sessions instead of a lab or synthetic test, so the numbers reflect the devices, networks, and pages your actual audience uses.
Motadata ObserveOps Real User Monitoring measures Core Web Vitals from inside each visitor's browser. Every session is scored against Largest Contentful Paint, First Contentful Paint, Cumulative Layout Shift, and Interaction to Next Paint, so a slow or unstable page surfaces as a pattern rather than an assumption about how the page performs.
Core Web Vitals monitoring in ObserveOps covers the browser experience only. When a slow page traces back to a backend service, ObserveOps links the session to its application trace, while backend tracing stays with Application Performance Monitoring.
Because the data comes from live sessions, the readings reflect the actual mix of devices, browsers, and network conditions your visitors bring, rather than a single controlled test environment.
Each session is measured for Largest Contentful Paint against a ≤2.5s threshold, so a page that takes too long to render its main content stands out in real traffic.
First Contentful Paint is captured against a ≤1.8s threshold, showing how quickly the first piece of content appears after a page starts loading.
Cumulative Layout Shift is measured against a ≤0.1 threshold, surfacing pages where content moves unexpectedly and disrupts the reading or clicking experience.
Interaction to Next Paint is captured against a ≤200ms threshold as the current responsiveness signal, which replaced First Input Delay in March 2024, showing how fast a page reacts to user input.
Sessions are scored with an Apdex measure using a T=2s target, giving a single satisfaction reading alongside the four individual vitals.
The Flame Chart gives a real-time, severity-based visual read over Largest Contentful Paint and First Contentful Paint, with no extra telemetry configuration required.
The RUM Alert Widget surfaces RUM alerts for a quicker response, and the policy view carries severity color indicators plus Business Service associations on every RUM policy record, so an alert reads with its business context attached.
Custom Reports for RUM support Chart, Grid, Top-N, Counter, and Aggregation formats through the same report-creation workflow as other modules, and Unified Incident Declaration folds RUM policies into a single incident workflow alongside Log, Flow, Trap, and APM policy types.
Saved Views preserve filter combinations, search queries, time ranges, and layout settings in Session Explorer, so a recurring vitals investigation is one click away instead of a rebuilt query.
RUM-APM Trace Correlation uses W3C distributed trace context headers to link a session with poor vitals to its backend application trace. A RUM Performance SLO can be evaluated against multiple metrics at once, though SLO evaluation itself belongs to the Service Level Objectives module, which consumes RUM metrics without collecting backend data of its own.
A browser instrumentation layer collects Core Web Vitals directly from the visitor's browser, alongside sessions, page views, actions, errors, long tasks, and resource timing. Vue.js, Angular, React, and Next.js applications are supported, so the same collection model covers every supported frontend framework.
Every session is checked against the four Core Web Vitals thresholds and an Apdex T=2s satisfaction target. The Flame Chart highlights severity across LCP and FCP, so a drifting page or a noisy segment stands out without extra telemetry configuration.
Session Explorer, session replay, and the Flame Chart present the vitals data, Saved Views keep a recurring investigation one click away, and RUM-APM Trace Correlation joins a frontend session to its backend trace over W3C distributed trace context headers so both halves of a slow request read as one timeline.
Core Web Vitals monitoring instruments Vue.js, Angular, React, and Next.js applications, so teams building on any of these four supported frontend frameworks collect the same Largest Contentful Paint, First Contentful Paint, Cumulative Layout Shift, and Interaction to Next Paint data without switching monitoring tools between projects.
Beyond framework coverage, geographic, device, and network segmentation breaks each metric down by where a session happened and what it ran on, so a team can tell whether a poor Interaction to Next Paint reading traces to a page problem, a device problem, or a network problem before deciding where to focus engineering time.
Field measurements from actual sessions replace assumptions about how fast or stable a page feels outside the lab.
Every metric is checked against its target (LCP ≤2.5s, FCP ≤1.8s, CLS ≤0.1, INP ≤200ms), so a page that drifts out of range stands out immediately.
Segmentation by geography, device, and network shows which visitors experience poor vitals before a team decides what to fix.
RUM-APM Trace Correlation links a session with poor vitals to its backend application trace, so investigation does not stop at the browser.
Saved Views in Session Explorer preserve filters, queries, time ranges, and layout, so a recurring vitals review is one click away.
Unified Incident Declaration brings RUM policies into the same workflow as Log, Flow, Trap, and APM policies, so a poor-vitals alert follows the same incident process as every other signal instead of a separate console.
Full page-experience visibility comes from keeping each layer in its own lane and joining them at the seams. Core Web Vitals monitoring owns the browser experience: sessions, page views, the four vitals, Apdex, and the frontend errors and interactions that make up a visit. When the question is about the backend service behind a slow page, that belongs to Application Performance Monitoring, and when the question is about the host or cluster serving that backend, that belongs to Hybrid Infrastructure Monitoring.
ObserveOps links these views through RUM-APM Trace Correlation, so a poor Largest Contentful Paint reading can be followed to the backend trace and the infrastructure underneath it, without RUM describing backend or host behavior as its own. The result is one connected picture built from modules that each report only on what they actually measure.
Core Web Vitals monitoring in Motadata ObserveOps turns raw browser signals into a clear view of how real users experience each page. By measuring Largest Contentful Paint, First Contentful Paint, Cumulative Layout Shift, and Interaction to Next Paint from live sessions across Vue.js, Angular, React, and Next.js applications, and connecting that data to alerting, reporting, and backend traces across the wider platform, it gives teams a direct path from a slow or unstable page to the fix it actually needs.
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