Top 8 Real User Monitoring Tools in 2025: Core Web Vitals, Session Replay & Frontend Debugging

In 2025, user experience is a key driver of digital success, where even small delays or poor Core Web Vitals scores affect conversions and search rankings. Real User Monitoring tools (RUM) have become essential, giving teams visibility into real sessions, Core Web Vitals, frontend errors, and backend calls. With features like JavaScript error capture, session replay, and trace correlation, modern RUM helps identify root causes and optimize user journeys across devices and networks.

CubeAPM delivers this with an OTEL-native Real User Monitoring platform that tracks Core Web Vitals (LCP, FID, CLS, INP), captures JavaScript errors with full stack traces, and ties them to session replays for instant debugging. With frontend–backend trace correlation, geo/device breakdowns, and predictable flat-rate pricing, CubeAPM helps organizations scale RUM without runaway costs.

In this article, we’ll compare the top 8 RUM tools in 2025, explore their features, pricing, pros and cons, and highlight the best fit by use case.

Top 8 RUM Tools in 2025

1. CubeAPM
2. Datadog RUM
3. New Relic Browser
4. Dynatrace RUM
5. Sentry
6. SigNoz
7. Raygun
8. Elastic RUM

What is Real User Monitoring?

 

A Real User Monitoring (RUM) tool tracks the performance of applications as experienced by real users in real time. Unlike synthetic monitoring, which simulates visits with pre-defined tests, RUM collects data directly from browsers and devices during live sessions. This provides accurate insight into how users experience page load times, responsiveness, and errors across different conditions.

Modern RUM platforms go beyond simple speed metrics. They measure Core Web Vitals — Largest Contentful Paint (LCP), First Input Delay (FID), and Cumulative Layout Shift (CLS) — along with additional metrics such as Time to First Byte (TTFB), API latency, network errors, and JavaScript crashes. Many also link frontend data with backend traces, giving engineering teams the ability to pinpoint whether an issue originates from the browser, the server, or third-party dependencies.

Advanced RUM tools now include session replay features, which allow teams to watch real user journeys frame by frame. This helps engineers reproduce issues exactly as users encountered them, making debugging faster and more accurate. Device, OS, and geography-level breakdowns also reveal where performance gaps or errors are concentrated, enabling data-driven prioritization of fixes.

How CubeAPM Powers Real User Monitoring at Scale

CubeAPM elevates Real User Monitoring by combining OTEL-native browser instrumentation, session replay, distributed tracing, and infrastructure monitoring into a single platform built for enterprise scale. Here’s how it addresses the unique challenges of frontend performance in modern digital experiences:

1. Core Web Vitals First-Class Support
   CubeAPM continuously tracks Google’s Core Web Vitals (LCP, FID, CLS, INP) for every session. These metrics directly impact SEO rankings and conversions, helping product teams fix regressions before they harm revenue or search visibility.
2. Session Replay with Error Context
   Instead of guessing what went wrong, CubeAPM links JavaScript errors to full session replays. Engineers can see exactly what the user saw — clicks, scrolls, crashes — and replay the journey frame by frame. This drastically reduces debugging time and improves user satisfaction.
3. Geo, Device, and Network Insights
   User experience varies across regions, ISPs, devices, and browsers. CubeAPM provides breakdowns by geography, OS, and device type, allowing teams to detect if performance issues are isolated (e.g., Safari users in APAC) or global.
4. Frontend–Backend Trace Correlation
   A unique strength of CubeAPM is how RUM ties frontend issues directly to backend traces and API calls through distributed tracing. Teams can instantly see if a slow LCP is caused by a delayed React render, a third-party script, or a backend API bottleneck — bringing frontend monitoring into the same workflow as enterprise and infrastructure monitoring.
5. SPA and Mobile App Coverage
   Modern apps don’t reload pages — they rely on single-page frameworks (React, Angular, Vue) and mobile clients. CubeAPM’s RUM captures route changes, long tasks, and API timings for SPAs and mobile apps, giving end-to-end visibility into dynamic user journeys.

Why Teams Choose Different RUM Tools

1. Cost concerns & pricing models

RUM is valuable, but costs often climb faster than expected. Many vendors charge per session, per event, or per GB ingested, which makes bills unpredictable when traffic spikes or seasonal demand hits. For a fast-growing SaaS or eCommerce platform, what starts as a few hundred dollars can quickly escalate into thousands, forcing teams to rethink their vendor choice.

2. Need for lightweight tools

Not every team needs an enterprise observability suite with dozens of features they won’t use. Startups and smaller engineering teams often prefer lean, developer-friendly RUM solutions that focus on the essentials — Core Web Vitals, error tracking, and a few key dashboards — without the complexity or overhead of enterprise platforms.

3. Avoiding vendor lock-in

Vendor-specific SDKs, pricing, and dashboards make switching painful. Many teams now prefer OpenTelemetry-first or self-hosted tools that let them own their data pipelines and dashboards. This flexibility ensures they aren’t trapped in costly vendor ecosystems and can integrate RUM data into their broader observability workflows.

4. Aggregation & alerting gaps

Simple alerts like “LCP > 2.5s” are helpful, but insufficient for serious operations. Teams expect percentile-based and trend-based alerts, a feature usually seen in advanced observability tools. When a RUM product can’t deliver this, teams are pushed back toward broader enterprise monitoring platforms — even if that means higher costs.

5. Ease of Implementation & Agent Overhead

Teams increasingly demand lightweight SDKs that don’t bloat page load times. OpenTelemetry-native RUM tools are especially attractive because they drop seamlessly into existing observability pipelines and avoid vendor lock-in.

6. Frontend – Backend Correlation

The biggest value of advanced RUM is when it integrates with distributed tracing. By linking frontend slowdowns directly to backend calls or database queries, engineers get end-to-end visibility across the stack. This is especially valuable for SaaS and eCommerce platforms where a single bottleneck can make or break conversions.

7. Data Retention & Query Flexibility

Many vendors limit RUM data retention to 7–14 days unless you pay more, which isn’t enough for tracking regressions over time. Teams in regulated industries like finance or healthcare often require longer retention by default and flexible querying to meet compliance and auditing needs.

8. User Experience Insights vs. Pure Metrics

Different stakeholders want different insights from RUM. Marketing and product teams value session replays, click maps, and funnel analysis, while engineering teams focus on Core Web Vitals, error tracking, and API latency. Tool choice often depends on which department drives the budget..

9. Ecosystem & Integrations

Large enterprises already invested in platforms like Datadog or New Relic often default to those ecosystems for RUM because of bundled pricing and integrations. In contrast, lean startups prefer independent solutions such as CubeAPM or Sentry that integrate flexibly into workflows with Slack, Jira, or GitHub.

Top 8 Real User Monitoring Tools in 2025

1. CubeAPM

Overview

CubeAPM is a full-stack observability platform purpose-built around OpenTelemetry-native ingestion. Its RUM capabilities capture Core Web Vitals, frontend errors, and session replay while tying them directly to backend traces and logs. With flat, predictable pricing and support for both cloud and self-hosted deployments, CubeAPM appeals to organizations that want cost control and compliance flexibility.

RUM-Specific Features

• Core Web Vitals dashboards (LCP, FID, CLS)
• Real session replay tied to errors
• Frontend error capture with trace correlation
• Geo- and device-level performance breakdowns
• SPA (React, Angular, Vue) monitoring and route-change tracking

Key Features

1. Core Web Vitals Monitoring – Tracks LCP, FID, and CLS for UX and SEO.
2. Browser Error Capture – Detects and correlates JS errors with backend traces.
3. Session Replay – Reconstructs full user journeys with error context.
4. OTEL-First Instrumentation – Native OpenTelemetry integration for browsers and SPAs.
5. Self-Hosting Option – Meets compliance needs (HIPAA/GDPR).

Pros

• Cost-effective with transparent pricing.
• Full MELT (metrics, events, logs, traces) support.
• Flexible deployment: cloud or self-hosted.

Cons

• Not suited for teams looking for off-prem solutions
• Strictly an observability platform and does not support cloud security management

Pricing

Pricing: Flat pricing of 0.15/GB

CubeAPM Real User Monitoring(RUM) Pricing At Scale

For a midsized company ingesting 10TB of RUM data per month, CubeAPM’s pricing at $0.15 per GB comes to about $1,500 per month. The simple usage-based model ensures costs scale linearly with traffic, making it easy for teams to predict budgets as their user base grows. Even at higher volumes, pricing remains transparent and manageable, giving organizations the confidence to expand monitoring without unexpected billing surprises.At 10TB/month, CubeAPM typically delivers ~65% lower costs than Datadog or New Relic.

Tech Fit

CubeAPM fits well for teams building cloud-native applications, SPAs, and mobile apps that need precise tracking of Core Web Vitals and real-time error correlation. Its OTEL-native design means it works seamlessly across languages and frameworks, while predictable pricing makes it accessible for both startups and large enterprises.

2. Datadog

Overview

Datadog RUM is part of Datadog’s extensive observability suite, designed for large enterprises and cloud-native teams. It provides deep frontend monitoring with session replay, error grouping, and Core Web Vitals dashboards. Its strength lies in tight integration with Datadog’s ecosystem, though this also means pricing can scale unpredictably as features are layered on.

RUM-Specific Features

• Session Replay with Full Context
• Core Web Vitals Visualization & Drill-Down
• Optimization Workflow for INP, LCP, CLS
• Error & Issue Aggregation
• Rich Custom Context & Telemetry Enrichment
• RUM + Synthetic Monitoring Correlation

Key Features

1. CWV Dashboards – Measures LCP, FID, CLS.
2. Replay & Heatmaps – Visualizes user interactions.
3. Correlated Tracing – Connects frontend sessions with backend spans.
4. AI-Powered Alerts – Identifies anomalies automatically.
5. Third-Party Coverage – Captures performance of external scripts.

Pros

• Wide integration ecosystem.
• Mature dashboards and visualization.
• Strong enterprise adoption and support.

Cons

• Expensive at scale.
• Pricing model unpredictable (per session + data).
• Steeper learning curve for small teams.

Pricing

• Infrastructure Monitoring: $23/host/month
• DevSecOps: $34/host/month
• APM: $400/host/month
• Log Ingestion: $0.10/GB ingested or scanned per month
• Standard Log Indexing (15-day retention): $1.70 per million log events per month

Datadog RUM pricing:

• $0.15 per 1,000 full traffic sessions (RUM Measure)
• $3 per 1,000 filtered sessions (RUM Investigate)
• $2.50 per 1,000 sessions, including Session Replay

Datadog Real User Monitoring(RUM) Pricing At Scale

For a midsized SaaS company managing 50 hosts and handling around 10TB of log data each month, Datadog’s pricing quickly stacks up across its product tiers. Infrastructure Monitoring alone comes in at about $1,150 per month (50 × $23), with DevSecOps adding roughly $1,700 per month (50 × $34). Full-stack APM on those same hosts contributes another $2,000 monthly (50 × $40). On top of this, log ingestion fees for 10TB at $0.10/GB add around $1,000, while indexing 1 million events adds a smaller recurring cost. Combined, the monthly bill for this setup lands at roughly $5,852. Adding Real User Monitoring for around 2M monthly sessions ($300) brings the total to about $6,152 per month, with higher traffic or enabling replay driving costs further up.

Tech Fit

Datadog RUM is well-suited for large-scale enterprises running multi-cloud or Kubernetes-heavy stacks. Its strength lies in correlating frontend metrics with the broader Datadog ecosystem, making it ideal for organizations already invested in Datadog for APM, logs, and infra monitoring.

3. New Relic Browser

Overview

New Relic Browser delivers end-to-end visibility of frontend performance, tying real user data directly to backend APM traces. It offers waterfall charts, error analytics, and Core Web Vitals tracking, making it popular with engineering teams in enterprise environments. Its advantage is full-stack context, though costs and user-based pricing can become a challenge at scale.

RUM-Specific Features

• Session Replay
• Browser & Mobile RUM Integration
• Mobile User Journeys with Breadcrumbs & Events
• Full-Stack Context in RUM

Key Features

1. Page Load Waterfalls – Breaks down resources by timing.
2. CWV Tracking – Monitors LCP, FID, CLS.
3. JS Error Analytics – Captures and trends browser errors.
4. Session Traces – Connects frontend actions with backend spans.
5. User Journey Mapping – Tracks end-to-end navigation paths.

Pros

• Excellent frontend visualization.
• Enterprise-grade stability and support.
• Strong ecosystem for legacy Java/enterprise stacks.

Cons

• $400/user/month license is very costly.
• Limited flexibility for custom self-hosting.
• Data residency issues for compliance-heavy orgs.

Pricing

• Free Tier: 100GB/month data ingested
• Ingestion-based pricing of $0.35/GB + $400/user/month for full access

New Relic Real User Monitoring(RUM) Pricing At Scale

For a midsized company ingesting 10TB of data per month with a team of 10 engineers, New Relic’s pricing breaks down as follows: the free 100GB tier leaves 9,900GB billable, which amounts to $3,465/month in ingestion costs. Adding $4,000/month for 10 full-access user licenses brings the total to $7,465 per month.

Tech Fit

New Relic’s RUM tool integrates best with enterprise Java, .NET, and browser-heavy applications, where teams need full-stack visibility tied to backend traces. It’s also a strong fit for companies that rely on detailed waterfall views and want unified monitoring across mobile, frontend, and server-side.

4. Dynatrace

Overview

Dynatrace RUM provides AI-assisted digital experience monitoring that captures every user journey across web and mobile apps. It integrates session replay, anomaly detection via Davis AI, and detailed performance breakdowns. Known for its enterprise focus, Dynatrace is powerful but often seen as complex and over-engineered for smaller teams.

RUM-Specific Features

• Full visibility across user journeys
• Visually Complete & Waterfall Performance Metrics
• Session Replay
• AI-Powered Anomaly Detection (Davis AI)
• Real-Time Issue Detection & Session Correlation
• RUM Browser Extension for 3rd-Party Apps
• Event-Based Data Enrichment & Long-Term Querying

Key Features

1. Session Replay – Records user behavior and frontend issues.
2. AI-Driven Alerts – Identifies regressions proactively.
3. CWV Monitoring – Full compliance with SEO-critical metrics.
4. Full-Stack Tracing – Correlates frontend with microservices.
5. Hybrid/Cloud Support – Works across multi-cloud deployments.

Pros

• AI-driven root cause analysis.
• Scales globally across enterprises.
• Strong support for hybrid and legacy stacks.

Cons

• Complex to set up and manage.
• Premium-level pricing.
• Overkill for startups or mid-market teams.

Pricing

• Full-Stack Monitoring: $0.08 per hour for an 8 GiB host
• Infrastructure Monitoring: $0.04 per hour per host
• Synthetic Monitoring: $0.001 per request
• Logs: $0.20 per GiB
• Real User Monitoring: $0.00225 per session

Dynatrace Real User Monitoring(RUM) Pricing At Scale

For a midsized company running 50 hosts, ingesting 10TB of logs per month, and executing 100,000 synthetic monitoring requests, Dynatrace’s pricing comes to around $6,420 per month. This includes $2,880 for full-stack monitoring, $1,440 for infrastructure coverage, $2,000 for log ingestion, and $100 for synthetic checks. Adding Real User Monitoring at $0.00225 per session for about 2M monthly sessions (~$4,500) pushes the total closer to $10,920 per month. The modular pricing means costs can grow quickly as additional hosts, log volumes, synthetic traffic, or higher RUM usage are added.

Tech Fit

Dynatrace RUM works best in complex enterprise environments, especially those with large-scale Java, .NET, and microservices applications. With Davis AI, it suits organizations that want automated anomaly detection and replay at scale, though it may feel over-engineered for smaller teams.

5. Sentry

Overview

Sentry started as a developer-first error tracking tool and has grown into a platform that includes RUM and performance monitoring. Its RUM solution captures frontend metrics, errors, and slow transactions with direct links to stack traces. This makes it particularly attractive for teams that want lightweight, developer-centric monitoring without adopting a full enterprise platform.

RUM-Specific Features

• Session Replay
• Trace-linked frontend metrics and slowdowns
• Web Vitals monitoring (LCP, CLS, FCP, TTFB, INP)
• Performance issues grouped by user impact
• Session-to-trace correlation for deep debugging
• Automatic SPA route and long-task capture

Key Features

1. Error Tracking – Detects and triages JS errors.
2. Performance Metrics – Measures slow transactions and frontend bottlenecks.
3. Release Health – Tracks issues tied to specific app versions.
4. Traces Integration – Links frontend errors to backend traces.
5. Source Maps Support – Debugs minified code in production.

Pros

• Affordable entry pricing.
• Strong open-source community.
• Easy to set up and integrate.

Cons

• Limited enterprise-scale features.
• Session replay less mature than rivals.
• Lacks advanced CWV dashboards.

Pricing

• Base Plan: $26/month, Covers standard access
• Business: 80/month, covers 1 replay, 1 uptime monitor, nd 1 cron monitor
• Enterprise: Custom Pricing

Sentry Real User Monitoring(RUM) Pricing At Scale

For a midsized SaaS business running 50 hosts, Sentry’s costs scale quickly once monitoring volumes grow. The base plan starts at $26/month, but with around 5 million error events (~$3.50), 200 million spans ($150), 30K session replays ($1,500), 300 monitors ($234), 200 uptime alerts ($200), and continuous profiling across 50 hosts ($1,134), the monthly bill lands at about $3,248.

Tech Fit

Sentry RUM is designed for developer-first teams building SPAs, Node.js backends, or mobile apps. It’s particularly strong where fast debugging of JavaScript errors and trace-linked session replay are priorities, making it popular among product and engineering teams who want rapid, code-level insights.

6. SigNoz

Overview

SigNoz is an open-source, self-hosted observability platform that provides RUM as part of its OTEL-native monitoring stack. It enables teams to track Core Web Vitals, frontend errors, and session performance while retaining full control over their telemetry data. Its community-driven model and flexibility make it a favorite for compliance-heavy industries and cost-sensitive teams.

RUM-Specific Features

• Native OpenTelemetry support for frontend instrumentation
• Unified dashboards combining logs, metrics, and traces for end-to-end RUM insights
• Distributed tracing with flamegraphs and Gantt chart visualization
• Flexible dashboards and custom queries (PromQL-like or DIY) for RUM analysis

Key Features

1. OTEL Native – Works seamlessly with OpenTelemetry browser SDKs.
2. Session Metrics – Captures page load and navigation timings.
3. CWV Tracking – Dashboards for LCP, FID, CLS.
4. Error Logging – JS error capture with context.
5. Custom Dashboards – Build tailored frontend reports.

Pros

• Open-source and free to self-host.
• Full OTEL support.
• Good for compliance-heavy teams.

Cons

• Smaller community than Grafana.
• Limited commercial support.
• Setup requires infra expertise.

Pricing

• Free tier + base fee of $49/month. Charges beyond the base fee are based on data ingested:
• Traces: $0.30/GB.
• Logs: $0.30/GB.
• Metrics: $0.10/million samples.

SigNoz Real User Monitoring(RUM) Pricing At Scale

For a midsized company running 50 hosts and ingesting 10 TB of telemetry each month, SigNoz charges a $49 base fee plus usage-based costs. Assuming 5 TB of traces (5,120 GB × $0.30 = $1,536) and 5 TB of logs (5,120 GB × $0.30 = $1,536), total ingestion comes to $3,072. Metrics are billed at $0.10 per million samples, so with 500M samples monthly that adds another $50. Adding the base fee, the total monthly spend comes to $3,171.

Tech Fit

SigNoz is a strong choice for teams that need self-hosted or compliance-driven deployments while still monitoring frontend performance. It fits well for companies with engineering teams who prefer open-source, OTEL-native solutions, and want to avoid vendor lock-in while retaining control of their telemetry data.

7. Raygun

Overview

Raygun specializes in real user monitoring and crash reporting, built with developers in mind. It provides detailed session-level insights, Core Web Vitals tracking, and crash diagnostics across browsers and devices. With an emphasis on fast debugging and performance optimization, Raygun fits well for SaaS products and customer-facing applications.

RUM-Specific Features

• Session replay inside Crash Reporting
• Core Web Vitals support (including INP)
• Performance breakdowns by browser, version, geolocation, URL, device, and tags
• Detailed waterfall views and histograms with session-level timings

Key Features

1. Session Traces – Records every page view and action.
2. Crash Reporting – Error monitoring for JS, mobile, and backend.
3. Core Web Vitals Dashboards – Built-in UX metrics.
4. Geo Performance – Regional latency and availability maps.
5. Custom Dashboards – Flexible visualization options.

Pros

• Strong focus on frontend and UX.
• Easy to deploy with SDKs.
• Affordable for SMBs.

Cons

• Lacks deep backend observability.
• Pricing grows with traffic.
• Smaller ecosystem compared to Datadog/New Relic.

Pricing

• APM: starts $80/100k/month
• RUM: starts $80/100k/month
• Crash Reporting: starts $40/100k/month
• SAML SSO (add-on): $50/month
• Usage capping (add-on): $40/month

Raygun Real User Monitoring(RUM) Pricing At Scale

For a midsized company processing 2M APM events, 2M RUM events, and 1M crash reports monthly, Raygun costs scale more moderately: APM at $80 × 20 = $1,600, RUM at $1,600, and crash reporting at $40 × 10 = $400. With SAML SSO ($50) and usage capping ($40), the total monthly bill comes to around $3,690–$4,000. Factoring in some headroom for growth and overage, this averages to about $5,000/month at mid-sized scale.

Tech Fit

Raygun’s RUM fits best for frontend-heavy SaaS and mobile apps where developers need granular crash reporting tied to real user sessions. It’s favored by engineering teams that want fast feedback on JavaScript errors, Core Web Vitals, and performance bottlenecks without adopting a full observability suite.

8. Elastic Observability RUM

Overview

Elastic RUM is part of the Elastic Observability suite and ties directly into the Elastic Stack (Elasticsearch, Kibana, Logstash). It captures browser metrics, Core Web Vitals, and performance timings, while allowing users to query and visualize data through Kibana dashboards. Its open-source foundation makes it highly flexible, though setup can be complex for teams not already using Elastic.

RUM-Specific Features

• Real-time tracking of Core Web Vitals (LCP, INP, CLS), TTFB, DOM Interactive, and DOM Complete
• Filtering and analysis by URL, OS, browser, and geographic location
• Integration with Elastic APM to correlate RUM data with backend traces, logs, and metrics
• Out-of-the-box dashboards and visualizations in Kibana for performance insights
• Open-source flexibility with Elastic’s search-driven analytics.

Key Features

1. Browser Agent – Captures CWV and timing metrics.
2. Trace Correlation – Connects frontend sessions to backend services.
3. Error Tracking – Logs JS and API errors.
4. Geo Performance – Latency breakdowns by region.
5. Open-Source Dashboards – Customizable via Kibana.

Pros

• Free and open-source.
• Flexible for custom dashboards.
• Strong ecosystem with Elastic Stack.

Cons

• No session replay.
• Requires Elastic infra expertise.
• Less turnkey than SaaS competitors.

Pricing

• Pricing varies for Elastic Cloud usage. Hosted: resource-based, ranges $99-184/month
•  Serverless: usage-based, $0.15/GB of data ingested,
• Synthetic monitoring: $0.0123 per test run

Elastic Observability Real User Monitoring(RUM) Pricing At Scale

Elastic Observability has a free tier, but at scale, costs grow based on data ingestion and retention. For a midsized SaaS team ingesting 10TB of logs and traces monthly (10,240GB × $0.23/GB = $2,355) plus APM/metrics storage of about $500, the data side alone reaches $2,855/month. Adding infrastructure monitoring for 50 hosts at $16/host ($800) and synthetic monitoring at around $200, the total bill comes to roughly $3,800/month. With longer retention (30+ days) and enterprise features like machine learning anomaly detection, real-world bills typically approach $4,500–$5,000/month.

Tech Fit

Elastic RUM works well for teams already using the Elastic Stack for logging and search. It’s especially suitable for organizations that want open-source flexibility, customizable dashboards in Kibana, and correlation of RUM data with logs and metrics in a single ecosystem.

Conclusion

In 2025, Real User Monitoring (RUM) is central to delivering seamless user experiences. The best tools don’t just track uptime — they capture Core Web Vitals, JavaScript errors, API latency, and session replays to show exactly how users experience applications in the real world. Advanced platforms also provide waterfall views, SPA navigation tracking, and frontend-to-backend trace correlation, turning raw browser events into actionable insights.

Our review of the top RUM tools shows there is no one-size-fits-all solution. CubeAPM stands out with its OTEL-native browser instrumentation, Core Web Vitals dashboards, error-to-trace correlation, session replay, and geo/device-level performance insights — all delivered with predictable pricing. This makes it a strong fit for teams seeking scalable RUM without runaway costs.

The right RUM tool ultimately depends on scale, use case, and budget — but the goal is universal: turning real user data into faster, smoother digital experiences.