JavaScript Monitoring Tools: A Developer's Guide to Choosing the Right One

JavaScript runs on nearly every website you'll ever build or maintain. It powers 98.9% of all sites on the internet, which means JavaScript errors and performance problems are the most common source of frontend issues your team will deal with. They're also some of the hardest to reproduce. A user hits a broken button on a specific browser, a specific screen size, and a specific network condition, and by the time you open the console, the error is gone.

This guide is for developers and DevOps teams evaluating JavaScript monitoring tools. We'll look at what separates a basic error tracker from a tool that gives you real context, how to evaluate that difference for your own stack, and how to run a proof of concept (POC) before you commit.

Key takeaways: JavaScript monitoring tools

• JavaScript monitoring tools range from lightweight error trackers to full performance and observability platforms, and the right fit depends on how deep you need visibility to go.
• Source map support and stack trace accuracy determine whether an error report is actually usable or just a wall of minified code.
• Core Web Vitals and performance monitoring matter as much as error tracking—a page that never crashes but loads slowly still loses users.
• Standalone JavaScript error trackers answer "what broke," and JavaScript monitoring connected to APM, traces, and infrastructure data answers "why it broke and what it cost." New Relic delivers both without adding a separate tool to your stack.

The best JavaScript monitoring tools

Some tools focus on error tracking alone. Others add performance monitoring, and a smaller group connects frontend data to backend traces so you can trace a browser error straight to the service that caused it — the distinction that matters most as your app scales.

New Relic

New Relic Browser Monitoring captures JavaScript errors, AJAX calls, and Core Web Vitals from real user sessions, then connects that data to the same APM and distributed tracing New Relic uses for your backend. A frontend error and the API call behind it show up in the same view, not two different tools.

This matters most during an actual incident. Say a checkout page throws a JavaScript error for a subset of users. A standalone error tracker gives you the stack trace and stops there. In New Relic, that same error links directly to the API call, trace, and infrastructure metrics behind it, so you go from "users are seeing an error" to "the payment service is timing out under load" without switching tools.

New Relic also treats JavaScript monitoring as one part of a single data platform, not a separate product with its own pricing tier. Errors, traces, logs, and infrastructure metrics all live in the same account, with nothing to reconcile across vendors.

Key features:

• Browser Monitoring with automatic JavaScript error capture
• Errors Inbox for triaging errors across frontend and backend in one place
• AJAX request monitoring, including failed and slow calls
• Core Web Vitals tracking with real user data
• Native integration with APM and distributed tracing, no separate login or tool

Best for: Teams that want error tracking and performance monitoring correlated with backend traces, without running a second platform.

Considerations: Teams that only need lightweight, standalone error tracking for a small frontend project may find New Relic's full platform more than they need at first, though the free tier makes it accessible for smaller teams too.

Sentry

Sentry is widely used for JavaScript error tracking. It captures unhandled exceptions and promise rejections automatically, with stack traces, source map support, and breadcrumbs that log the user actions leading up to an error.

Key features:

• Automatic exception and promise rejection capture
• Breadcrumbs showing clicks, navigation, and console output before an error
• Release tracking tied to specific deploys
• Performance monitoring and Web Vitals on paid plans
• Distributed tracing that links a frontend span to a backend span

Best for: Developer teams that want strong error tracking with a large SDK ecosystem across languages and frameworks.

Considerations: Performance monitoring and tracing are add-ons, not core features, and pricing scales with event volume. This can also spike hard during a bad release.

Raygun

Raygun combines crash reporting with real user monitoring in one platform, with a focus on connecting errors to the specific release that introduced them.

Key features:

• Automatic error and crash detection
• Real user monitoring with page load timing
• Deployment tracking that flags regressions by release
• User-level segmentation of performance data
• Source map support for readable stack traces

Best for: Teams with frequent release cycles who want fast visibility into whether a new deploy introduced errors or slower load times.

Considerations: Backend correlation is limited compared to platforms built around distributed tracing, so tracing a frontend error back to a specific service call usually takes extra tooling.

LogRocket

LogRocket pairs performance and error monitoring with full session replay, so you can watch what a user actually did leading up to a bug.

Key features:

• Session replay with DOM-level playback
• Error tracking with stack traces and source maps
• Network request inspection for client-side API calls
• Performance metrics alongside recorded sessions
• AI-assisted issue triage on higher plans

Best for: Product and engineering teams that want to see the user's exact experience alongside the stack trace.

Considerations: Deeper features like heatmaps and funnels are gated behind higher-priced plans, and backend correlation isn't a core strength.

Datadog Real User Monitoring

Datadog Real User Monitoring is part of Datadog's broader observability platform, tracking real user sessions and correlating them with backend traces, logs, and infrastructure data.

Key features:

• Real user monitoring with Core Web Vitals and custom metrics
• Session replay available as an add-on
• Full-stack correlation across frontend, backend traces, and infrastructure
• Deployment tracking tied to error and performance regressions
• Mobile RUM for iOS, Android, and React Native in the same console

Best for: Teams already standardized on Datadog for infrastructure and backend observability who want frontend data in the same place.

Considerations: Session replay and other add-ons are priced separately from core RUM, and costs can climb quickly on high-traffic sites.

How to evaluate JavaScript monitoring tools

The most common mistake teams make is choosing a tool based on how many errors it catches. Error volume is easy to measure and easy to market, but it's the wrong first question, especially given that JavaScript now runs on nearly every site on the web.

What matters more is whether those errors are connected to the backend traces and infrastructure data that explain why they happened. That connection determines how fast your team moves from issue to solution.

Error capture depth and stack trace quality

A monitoring tool should capture unhandled exceptions and promise rejections automatically, without requiring you to wrap every function in a try/catch block. Check how the tool groups similar errors together. With good grouping, your team sees one issue affecting 500 users instead of 500 separate tickets.

Source map support and minified code handling

Production JavaScript is minified. Without source maps, a stack trace points at a compressed bundle instead of your actual code. Confirm the tool supports automatic source map uploading during your build process, and test it against a real deploy before you commit.

Our guide to manually capturing browser logs is a useful reference if you need to validate what a tool is (and isn't) capturing by default.

Performance monitoring and Core Web Vitals

Core Web Vitals (Largest Contentful Paint, Interaction to Next Paint, and Cumulative Layout Shift) are a confirmed Google ranking factor. A tool that only tracks errors won't tell you why a page feels slow even when nothing is technically broken. 

For a deeper look at how real user monitoring differs from traditional APM, see our breakdown of RUM vs. APM.

Integration with APM and backend traces

Application performance monitoring (APM) and backend trace tool integration is the criterion that separates a standalone error tracker from a true observability tool. Can you click from a frontend error straight into the backend trace, database query, or infrastructure metric that caused it? If the answer is no, your team is stitching together data manually every time an incident happens.

Sampling, data retention, and cost at scale

Most tools sample data at high traffic volumes rather than capturing every session. Ask how sampling works, what gets dropped, and how long data is retained. Pricing models that charge per event or per session can get expensive fast once you scale past a proof of concept (POC).

How to run a JavaScript monitoring tool POC

A feature list only tells you so much. The real test is running the tool against your own code, with your own traffic, before you sign a contract. Give yourself at least two to three weeks, and involve the engineers who'll actually use the tool, not just whoever's leading procurement.

Here's how to structure it so it actually surfaces the differences that matter.

1. Define your error and performance success metrics

Decide up front what you're measuring: error capture rate, time to detect a regression, or how many of your Core Web Vitals pass the "good" threshold. A few concrete examples worth tracking are:

• The percentage of errors that resolve to a readable stack trace on the first try
• Mean time from an error occurring to your team getting an alert
• The share of pages that stay in the "good" range for LCP, INP, and CLS

Write these down before you start testing. Without a defined metric, a POC becomes a feature tour.

2. Instrument a representative set of pages or components

Pick pages that reflect real usage, including at least one high-traffic page and one complex, interactive component. A simple landing page won't tell you much about how the tool handles a JavaScript-heavy dashboard, a checkout flow, or client-side routing in a single-page application.

If your app relies on third-party scripts, ads, or embedded widgets, include a page where those run too. Third-party script errors are a common source of noise, and you want to know now how well the tool separates them from your own code.

3. Validate source map upload and stack trace accuracy

Deploy a minified build and confirm the tool resolves stack traces back to your original source, including correct file names and line numbers, not just a cleaned-up version of the minified bundle. Test this through your actual CI/CD pipeline, not a manual upload, since that's how it will work in production.

This is the fastest way to tell a mature tool from one that'll leave your team reading compressed code mid-incident.

4. Test backend correlation: Trace a browser error to its API call

Trigger a real error that involves a backend call, then see how many clicks it takes to get from the frontend error to the backend trace:

• In a well-integrated tool, this is one click: you land on the exact trace, span, or log line tied to that request.
• In a weaker setup, you're copying an error ID, pasting it into a second tool, and hoping the timestamps line up.

More than one or two clicks, or a tool switch, is friction you'll hit constantly — usually during the incidents where speed matters most.

5. Evaluate alert quality and noise in production

Run the tool against real traffic for at least a week, ideally spanning one full deploy cycle, and pay attention to alert volume. Track how many alerts led to a real fix versus how many got dismissed or ignored. A tool that pages your team for every minor error will get its alerts muted within a month, and a muted alert is worse than no alert, since it creates a false sense of coverage. 

Which JavaScript monitoring tool is right for your team?

There's no single right answer here. It comes down to what your team already runs, where the pain is sharpest today, and how much backend correlation you actually need versus how much you think you need.

Here's how the tools covered above tend to map to the most common team profiles.

Teams focused on JavaScript error tracking and debugging

If knowing when something breaks is the main gap, prioritize breadcrumb trails and release tracking.

Teams that need frontend performance and Core Web Vitals monitoring

Raygun and dedicated RUM tools cover Core Web Vitals well when performance is your primary lens and deep backend correlation isn't critical.

Teams building Node.js or full-stack JavaScript applications

If your JavaScript runs on both client and server, you'll want a tool that monitors both consistently rather than pairing a browser-only tool with a separate agent. Our Node.js monitoring guide covers what to look for server-side.

Teams already using New Relic for APM

New Relic Browser Monitoring adds JavaScript error tracking and performance monitoring to your existing account, without a separate tool, login, or bill to manage. For teams already paying for APM, this is usually the lowest-friction way to close the gap between frontend and backend visibility.

Teams with open-source or self-hosted requirements

Some teams need full control over where error data lives, for compliance or to avoid per-session pricing at scale. Open-source options like Grafana Faro or self-hosted Elastic Observability exist, though you'll operate the backend yourself.

What to prioritize before you commit

The best JavaScript monitoring tool isn't the one that catches the most errors. It's the one that gives your team enough context to fix them fast, from the browser error all the way through to the backend service that caused it. A tool that lives outside the rest of your observability stack will always add friction at the exact moment you can least afford it.

Request a demo and see how New Relic monitors JavaScript across your entire stack. 

FAQs about JavaScript monitoring tools

What do JavaScript monitoring tools do?

JavaScript monitoring tools capture errors, exceptions, and performance data from a user's browser in real time. They track unhandled exceptions, slow page loads, failed API calls, and Core Web Vitals, then surface that data so developers can find and fix issues before they affect more users. Some tools also connect this data to backend traces for full context.

What's the difference between JavaScript error monitoring and browser performance monitoring?

Error monitoring captures exceptions, crashes, and failed requests so you know what broke. Performance monitoring tracks metrics like page load time, responsiveness, and visual stability, including Core Web Vitals, so you know how the experience felt even when nothing technically failed. Most modern tools offer both, but the depth of each varies.

How do JavaScript monitoring tools handle single-page applications (SPAs)?

Most tools instrument route changes in SPAs so they can track virtual page views and errors that occur without a full page reload. This requires framework-specific SDKs or configuration for React, Vue, Angular, and similar frameworks, since a SPA doesn't trigger the same browser events a traditional multi-page site does.

Do JavaScript monitoring tools work with Node.js as well as browser JavaScript?

Many platforms, including New Relic, support both browser-side and Node.js monitoring, letting you track a request from the frontend through to the server using the same tool. Standalone browser-only tools typically require a separate product or SDK for server-side Node.js monitoring, which adds a second dashboard to check.