Passer au contenu
Pour commencer
Blog

Synthetic Monitoring vs Real User Monitoring (RUM): the complete guide (2025)

lucaslabrousse@uplix.fr |

Synthetic runs scripted checks from controlled locations and browsers to catch regressions and ensure uptime 24/7. The best real user monitoring tools captures what real users actually experience on real devices, networks, and geographies, ideal for prioritizing work that moves Core Web Vitals (INP/LCP/CLS) and revenue. The best practice is to combine both: synthetics for proactive reliability, RUM for field truth and business impact.

Synthetic Monitoring

Active • Controlled

Scripted tests (browser/API) from chosen regions and devices.

  • Best for pre-prod, uptime/SLA, regression checks
  • Works even with low traffic or off-hours
  • Stable baselines, proactive alerts on journeys

Real User Monitoring (RUM)

Passive • Field Data

Measures real users on real devices, networks, and geographies.

  • Best for prioritizing by impact (conversions, UX)
  • Tracks Core Web Vitals at p75: INP, LCP, CLS
  • Finds outliers (country, ISP, page, device)

Use Both (Recommended)

Coverage • Confidence

Pair proactive reliability with real-world experience.

  • Synthetics guardrails critical paths 24/7
  • RUM proves real impact and guides prioritization
  • Align metrics & alerts; correlate to APM/logs
See the comparison table How to combine both

Updated: October 22, 2025 • INP replaced FID as the responsiveness vital (use RUM to track field performance).

Synthetic Monitoring vs Real User Monitoring (RUM) — Comparison at a glance

Skim this side-by-side to see where each shines. On mobile, scroll the table horizontally.

Dimension Synthetic Monitoring Real User Monitoring (RUM)
Nature Active, scripted tests run from chosen regions/browsers/devices. Passive, field data from real users on real devices & networks.
Environment Great in pre-prod/staging and production canaries. Best in production (actual traffic & behavior).
Traffic dependency Works with zero traffic. Needs real traffic (sampling helps at scale).
Best for Uptime/SLA, regression detection, 24/7 journey checks. Prioritizing by business impact, trends, UX reality.
Core Web Vitals Lab baselines; good for change control & guardrails. Field CWV at p75: INP, LCP, CLS.
Uptime / SLA Primary use case (HTTP/API + browser flows). Indirect (errors & availability as experienced by users).
Transactions Deterministic scripted journeys (login, checkout). Observes real funnels; reveals drop-offs & variance.
Alerting Threshold/availability & step failures (proactive). Distribution shifts (p75) & outlier segments (geo/ISP/device).
Debug depth Repeatable filmstrips, HAR, controlled repro. Real-world session context, errors, optional replay.
Outlier detection Limited (unless you simulate many geos/ISPs). Strong (actual geos, ISPs, devices, pages).
Privacy & governance Lower risk (robots). Data mostly synthetic/logs. Needs PII masking, consent (CMP), RBAC, EU hosting options.
Cost model By number of checks/locations/frequency. By sessions/pageviews; sampling controls spend.
Limitations May miss real-world variance & human behavior. Needs traffic; less deterministic for exact repro.
When it shines Before launch; at night; SLAs; catching regressions early. After launch; proving impact; SEO/CWV; market/geo insights.
Best together Use both: synthetics for guardrails & early alerts, RUM for field truth, prioritization, and Core Web Vitals outcomes.

Tip: align metric names across both (e.g., route names, journey IDs) and correlate to APM/logs for faster root-cause.

Definitions — Synthetic Monitoring & Real User Monitoring (RUM)


What is Synthetic Monitoring?

Scripted checks that simulate user actions from chosen regions, browsers, and devices.

  • Runs on schedule (cron) — works with zero traffic, day or night.
  • Validates uptime, API responses, and transaction flows (login, checkout).
  • Ideal for pre-prod/staging and guarding critical paths in production.
  • Produces stable baselines and proactive alerts on step failures.
Best for
Regression catching • SLA/uptime • Canary checks
Data
Deterministic timings, filmstrips, HAR, HTTP assertions

What is Real User Monitoring (RUM)?

Real user monitoring measures what real users experience on real devices, networks, geographies, and pages.

  • Tracks Core Web Vitals at p75: INP, LCP, CLS (field reality).
  • Finds outliers by country, ISP, device, or page template.
  • Correlates UX with conversions, errors, and backend traces.
  • Optional session replay (with PII masking & consent) speeds diagnosis.
Best for
Prioritizing by impact • Trend tracking • SEO/CWV
Data
Field distributions, JS errors, resource timings, segments

When to use each — a practical decision framework

Pick the right tool for the moment. Each scenario card recommends Synthetic, RUM, or Both, with a short “why” and a concrete next step.

Synthetic RUM Both

Pre-launch & staging checks

Synthetic

You need repeatable, controlled tests to catch regressions before production.

  • Script journeys (login, add-to-cart, checkout)
  • Run hourly from 2–3 key regions & browsers
  • Block release on failures (CI/CD hook)

Low traffic or off-hours coverage

Synthetic

RUM can’t alert without users; synthetics give 24/7 availability and baselines.

  • Set frequency (5–15 min) for critical flows
  • Add API checks for dependencies
  • Alert on step failures & latency thresholds

SEO & Core Web Vitals outcomes

RUM

Only field data reflects real user experience at p75 for INP, LCP, CLS.

  • Instrument RUM on key templates & routes (SPA)
  • Alert on p75 shifts for INP/LCP/CLS
  • Segment by geo/ISP/device to find outliers

“It’s slow in country X / ISP Y”

RUM

Real traffic exposes variance by geography, ISP, and device mix.

  • Drill field metrics by geo & network
  • Correlate with errors & third-party tags
  • Backtest fixes with A/B or time windows

Checkout reliability (24/7)

Both

Guard rails + real impact: synthetics catch outages; RUM shows actual drop-offs.

  • Synthetics: scripted checkout from 3 regions
  • RUM: monitor conversion + CWV on steps
  • Correlate to APM/logs for root-cause

Intermittent JS errors & long tasks

Both

RUM finds real sessions & INP outliers; synthetics reproduces with control.

  • RUM: upload source maps & track INP attribution
  • Replay (masked) sessions to see patterns
  • Reproduce via synthetic scripted steps

Measure impact of an optimization

RUM

Only field distributions capture perceived gains across devices & networks.

  • Compare p75 before/after (same cohorts)
  • Slice by device/geo; watch INP/LCP deltas
  • Validate no regression via synthetics

Compliance, privacy & data residency

Both

Synthetics minimizes privacy risk; RUM requires strict masking & governance.

  • Enable PII masking & CMP hooks (RUM)
  • Choose EU hosting / sovereignty options
  • Limit capture scope; define retention
Open the 6-step playbook Back to comparison

How to combine Synthetic Monitoring and RUM — a 6-step playbook

Use this lightweight sequence to pair proactive guardrails (synthetics) with field truth (RUM). It’s vendor-neutral and works for web apps, SPAs, and APIs.

  1. Map critical journeys & top traffic pages

    List the business-critical flows (login, search, add-to-cart, checkout) and the highest-traffic templates/routes. These will anchor both synthetic checks and RUM dashboards.

  2. Instrument RUM for field metrics (INP/LCP/CLS)

    Add the browser tag/SDK, enable SPA navigation tracking, and surface p75 distributions for INP, LCP, CLS. Upload source maps to make JS errors readable.

    • Segment by geo/ISP/device to catch outliers
    • Set baselines per route/template

  3. Align naming & sampling across tools

    Use the same route names / journey IDs in both RUM and synthetics. Configure sampling and environments (prod/stage) to control cost and noise.

    • Tag builds with release / app.version
    • Exclude bots / admin traffic from RUM

  4. Build synthetic guardrails (browser + API)

    Script journeys for the flows from step 1 and add API checks for dependencies. Run every 5–15 min from 2–3 regions and at least 2 browsers/devices.

    • Fail the build on journey errors (CI/CD)
    • Store HAR/filmstrips for repro

  5. Correlate and reproduce fast

    When RUM flags a regression (e.g., INP spike in country X), jump to session context (and optional replay), then reproduce with a targeted synthetic scenario. Link to APM/logs for root-cause.

    • Trace IDs / error IDs clickable from RUM
    • Create a synthetic “hotfix” runbook

  6. Governance, alerts & continuous review

    Enforce PII masking, CMP consent, RBAC, and EU hosting options. Set alerts on synthetic availability/latency and on RUM p75 shifts (INP/LCP/CLS). Review weekly.

    • RUM: alert on p75 INP > 200 ms, LCP > 2.5 s, CLS > 0.1
    • Synthetics: alert on 2-step failure or > SLAs

Quick configuration checklist

  • RUM tag/SDK live on key routes (prod only)
  • SPA navigation detection enabled
  • Source maps uploaded per release
  • Synthetic journeys scripted for login/checkout
  • API checks for auth, catalog, payment
  • Shared route/journey naming across tools
  • RBAC + PII masking + CMP hooks

Alert policy templates

  • RUM (field) — INP p75 ↑ 20% (15 min), LCP p75 > 2.5s, CLS p75 > 0.1
  • Synthetic (browser) — Step failure (2 of 3), journey > baseline +25%
  • Synthetic (API) — 5xx rate > 1%, latency > 95p +30%
  • Budget guardrail — RUM sampling cap by env/app

Privacy & data residency (EU)

Default to masking, restrict replay fields, log access, and prefer EU hosting with sovereignty guarantees when required.

Back to comparison Next: metrics that matter

Metrics that matter — and where they’re best measured

Use this vendor-neutral matrix to decide whether a metric is best tracked with RUM, Synthetic, or Both. On mobile, scroll horizontally.

RUM Synthetic Both
Metric Best measured in Why / when Typical alert / target
INP (Interaction to Next Paint) RUM Represents real responsiveness across the whole visit; needs field data and real interactions. p75 INP ≤ 200 ms (good), > 200–500 (needs), > 500 (poor).
LCP (Largest Contentful Paint) Both RUM for impact by geo/device; Synthetic for controlled baselines and regression tests. p75 LCP ≤ 2.5 s (good), > 2.5–4.0 (needs), > 4.0 (poor).
CLS (Cumulative Layout Shift) RUM Layout shifts are driven by real content/ads/user behavior; field data tells the truth. p75 CLS ≤ 0.1 (good), > 0.1–0.25 (needs), > 0.25 (poor).
TTFB Both RUM reveals real networks/CDNs; Synthetic isolates server/regression with fixed nodes. Watch p75; common guardrail around 0.8–1.8 s depending on stack & region.
Uptime / Availability Synthetic Deterministic, round-the-clock checks independent of traffic; ideal for SLAs. Availability ≥ 99.9% monthly; fail on 2 of 3 probe errors.
API latency & 5xx rate Synthetic Scripted API assertions and multi-region probes to de-risk dependencies. 95p latency < baseline +30%; 5xx rate < 1%.
Transaction (login/checkout) duration Both Synthetic = guardrails; RUM = real drop-offs by segment and device mix. Synth: duration +25% vs baseline; RUM: p75 step times increasing > 20%.
JS error rate / stack traces RUM Field stacks + source maps locate real crashes; Synthetic can reproduce once identified. Error rate > baseline +X% or new top error appears.
Long tasks / main-thread blocking RUM Often device/CPU dependent; field data surfaces segments causing INP regressions. Time blocked > threshold on target routes; INP p75 ↑ 20%.
3rd-party / tag impact Both Synthetic for clean before/after baselines; RUM for real impact on users & conversions. Alert when tag adds > X ms to LCP/INP or increases JS errors.
DNS / Connect / TLS Synthetic Best isolated in lab from multiple nodes to detect provider or routing issues early. p95 connect/TLS spikes vs baseline +30%.
Experience availability (as felt) RUM Captures real-world outages or blockers users hit despite green synthetics. Drop in successful sessions or conversion beyond normal seasonality.

Tip: align route/journey names across tools and correlate to APM/logs. Reminder: INP replaced FID in 2024 — track INP in the field.

Pre-production → Production — the handoff that prevents regressions

Use a two-lane workflow: synthetics to block regressions before release, then RUM to validate real-world impact after go-live. This section shows who does what — and when — so nothing slips through.

Pre-production • Synthetic

Before release

  1. Script critical journeys

    Login, add-to-cart, checkout, account — with assertions on text, status, and timings.

  2. Add API checks

    Auth, catalog, payments. Validate 95p latency and error rates against SLAs.

  3. Run from 2–3 regions & browsers

    Create stable baselines and catch geo/device-specific regressions early.

  4. CI/CD block on failures

    Fail the pipeline when steps break or exceed thresholds; store HAR/filmstrips.

Production • RUM

After release

  1. Validate with field metrics

    Track INP/LCP/CLS at p75 by route/template and cohort (geo/ISP/device).

  2. Correlate to errors & traces

    Use JS errors (with source maps) and APM/logs to find and explain outliers.

  3. Alert on distribution shifts

    Raise alerts when p75 worsens (e.g., INP ↑ +20%) or conversion drops on a step.

  4. Feedback to synthetics

    Turn new RUM findings into targeted synthetic scenarios to reproduce and prevent.

See metrics that matter Back to the 6-step playbook

Tooling landscape — vendor-neutral overview

RUM and Synthetic live across a few clear categories. Skim these neutral cards to understand what type of platform fits your context. Open a card to see common examples and typical strengths.

Unified DEM suites (RUM + Synthetic + APM)

Full-stack

All-in-one observability with RUM, browser/API synthetics, traces & logs, and alerting in one UI.

  • Enterprises wanting cross-signal correlation
  • Governance, RBAC, compliance & auditability
  • One contract, one data platform
Examples: Datadog • Dynatrace • New Relic • Splunk

Frontend performance specialists (CWV focus)

CWV/INP

Deep diagnostics for INP/LCP/CLS, visual comparisons, and developer-friendly insights.

  • Teams optimizing Core Web Vitals as KPIs
  • Visual diffs, filmstrips, asset-level timing
  • Clear guidance for engineers
Examples: SpeedCurve • DebugBear

Uptime / Status platforms with RUM add-ons

Guardrails

Straightforward synthetic uptime & transactions with optional RUM overlay for websites/APIs.

  • Fast setup for incident visibility
  • SLAs/SLOs and public status pages
  • Basic RUM to complement synthetics
Examples: Pingdom • Better Uptime (w/ integrations)

API-first synthetic platforms

APIs/Backends

Programmable probes and assertions for HTTP(s), auth flows, third-party dependencies, and SLAs.

  • Microservices & partner integrations
  • Contract tests in CI/CD
  • Multi-region latency & 5xx budgets
Examples: Checkly • Sematext (API) • Assertible

EU-focused platforms (hybrid / self-host options)

EU governance

RUM + Synthetics with options for EU hosting, sovereignty controls, and on-prem/hybrid deployments.

  • Regulated sectors & data residency demands
  • Granular privacy/PII masking & access logs
  • Flexible deployment (cloud, hybrid, on-prem)
Examples: Ekara by IP-Label • (others vary by region/policy)

Open-source / self-hosted stacks

DIY

Own the pipeline with community agents; shift cost to infrastructure & operations.

  • Teams with strong DevOps/SRE capabilities
  • Customization & data ownership
  • Cost control at very high scale
Examples: Elastic RUM • Grafana Faro • k6 (synthetics)
See the 6-step playbook Open decision framework

Note: Examples are illustrative and vendor-neutral. Replace/expand based on your ecosystem and compliance needs.

FAQ — Synthetic Monitoring vs Real User Monitoring (RUM)


What’s the difference between Synthetic Monitoring and RUM?

Synthetic runs scripted tests from controlled locations, browsers, and devices — great for uptime, SLAs, and preventing regressions. RUM measures what real users experience in production — ideal for prioritizing work that improves Core Web Vitals (INP/LCP/CLS) and conversions.

Which is better: RUM or Synthetic?

Neither is “better” in all cases. Use Synthetic when you need repeatable guardrails and 24/7 coverage; use RUM when you need field truth and business impact. Most teams get the best results by combining both.

Do I need both, or can one replace the other?

They are complementary. Synthetic catches issues before users do; RUM confirms how users are affected. Replacing one with the other usually leaves blind spots (either no field reality or no proactive guardrails).

Pre-production vs production — which tool fits where?
  • Pre-prod/staging: Synthetic journeys and API checks in CI/CD to block regressions.
  • Production: RUM for field metrics at p75, outliers by geo/ISP/device, and real funnels.
  • After release: Validate impact with RUM, then reproduce via targeted Synthetic tests.
Does RUM affect SEO and Core Web Vitals?

Yes — RUM provides field measurements for INP, LCP, CLS at the 75th percentile. Improving these for real users strengthens page experience signals and often correlates with better business outcomes.

What changed with INP replacing FID?

INP (Interaction to Next Paint) replaced FID as the responsiveness vital in 2024. INP looks at all interactions across a visit, so you should track it in RUM and add Synthetic guardrails for critical user actions.

How often should I run Synthetic checks?

Common baselines are every 5–15 minutes for critical browser journeys and 1–5 minutes for key API endpoints. Use multiple regions and at least two browsers/devices for coverage.

How do privacy and data residency apply?

RUM: enable PII masking by default, integrate your CMP, apply RBAC, and choose EU hosting when required. Synthetic: lower privacy risk (robots), but still treat credentials and test data securely.

Updated: October 22, 2025

Partager ce post

Poursuivre la lecture