Frontend Observability Deep Dive: Bugsnag vs LogRocket vs Sentry

When your React app crashes in production, a stack trace alone rarely tells the whole story. Was the user scrolling? What API calls failed beforehand? Did a race condition corrupt state? bugsnag, logrocket, and sentry all aim to answer these questions — but they approach observability from different angles. Let’s compare how they handle real-world debugging scenarios.

🛠️ Core Philosophy: What Each Tool Optimizes For

bugsnag treats errors as stable, actionable incidents. It focuses on accurate grouping, release correlation, and minimizing noise. You get clean dashboards showing which errors regressed after a deploy — ideal for engineering teams prioritizing reliability.

logrocket treats errors as symptoms of broken user journeys. Instead of just logging exceptions, it records everything: mouse movements, DOM mutations, console logs, and network requests. Perfect for product engineers who need to see what went wrong.

sentry treats errors as part of a larger observability graph. It connects frontend crashes to backend traces, performance metrics, and custom business events. Built for teams that want one system to monitor code health across the entire stack.

🧪 Error Capture & Reporting: How Exceptions Are Handled

All three auto-capture unhandled promise rejections and global errors, but differ in customization.

bugsnag: Explicit metadata attachment

Bugsnag encourages adding structured context via addMetadata() and leaveBreadcrumb(). Errors are enriched with user state without bloating payloads.

// bugsnag-js
import Bugsnag from '@bugsnag/js';

Bugsnag.start({ apiKey: 'YOUR_KEY' });

// Attach user info
Bugsnag.setUser('123', 'alice@example.com');

// Add custom tab in dashboard
Bugsnag.addMetadata('account', {
  plan: 'premium',
  trialEndsAt: '2023-12-01'
});

// Manual report
try {
  riskyOperation();
} catch (err) {
  Bugsnag.notify(err);
}

logrocket: Automatic session linkage

LogRocket doesn’t emphasize manual error reporting. Instead, every console.error or uncaught exception is automatically tied to a session replay URL.

// logrocket
import LogRocket from 'logrocket';

LogRocket.init('your-app-id');

// No explicit notify() needed
// Errors appear in dashboard linked to replays
window.addEventListener('error', (event) => {
  // Already captured automatically
});

// Optional: tag sessions
LogRocket.identify('user-123', {
  email: 'alice@example.com'
});

sentry: Unified event ingestion

Sentry uses a single captureException() method that works for errors, messages, or custom events — all flowing into the same issue stream.

// @sentry/react
import * as Sentry from '@sentry/react';

Sentry.init({ dsn: 'YOUR_DSN' });

// Report error with extra context
Sentry.captureException(new Error('Oops'), {
  tags: { section: 'checkout' },
  user: { id: '123' }
});

// Also captures unhandled rejections automatically

👁️ Session Replay & Context: Beyond the Stack Trace

This is where LogRocket diverges sharply.

logrocket: Full-fidelity replay

LogRocket records DOM changes, input events, and network activity by default. When an error occurs, you can watch exactly what the user saw.

// logrocket — replay is automatic
// In dashboard: click error → watch 30s before/after

// Optional: exclude sensitive fields
LogRocket.init('your-app-id', {
  network: {
    requestSanitizer: (request) => {
      if (request.url.includes('/auth')) {
        request.body = null;
      }
      return request;
    }
  }
});

sentry: Optional replay with sampling

Sentry offers session replay as an add-on feature (via @sentry/replay), but it’s opt-in and sampled to control costs.

// @sentry/react + @sentry/replay
import * as Sentry from '@sentry/react';
import { Replay } from '@sentry/replay';

Sentry.init({
  dsn: 'YOUR_DSN',
  integrations: [new Replay()],
  replaysSessionSampleRate: 0.1, // 10% of sessions
  replaysOnErrorSampleRate: 1.0  // 100% of error sessions
});

bugsnag: No session replay

Bugsnag does not offer DOM or video replay. It relies on breadcrumbs (e.g., "clicked button X", "navigated to /checkout") and metadata tabs for context.

// bugsnag — breadcrumbs only
Bugsnag.leaveBreadcrumb('Clicked checkout button', {
  page: window.location.pathname
});
// No visual replay capability

⚙️ Framework Integration: React-Specific Handling

All three provide React error boundary wrappers, but implementation differs.

bugsnag: Boundary as HOC

// bugsnag-react
import Bugsnag from '@bugsnag/js';
import BugsnagPluginReact from '@bugsnag/plugin-react';

Bugsnag.loadPlugin(BugsnagPluginReact);
const ErrorBoundary = Bugsnag.getPlugin('react').createErrorBoundary(React);

function App() {
  return (
    <ErrorBoundary>
      <CheckoutForm />
    </ErrorBoundary>
  );
}

logrocket: No special boundary needed

LogRocket captures React errors via global handlers. You don’t wrap components unless you want custom session tagging.

// logrocket — no boundary required
// Errors caught automatically

// But you can still use React's built-in error boundaries
// for UI recovery

sentry: Boundary as component

// @sentry/react
import * as Sentry from '@sentry/react';

function App() {
  return (
    <Sentry.ErrorBoundary fallback={<p>An error occurred</p>}>
      <CheckoutForm />
    </Sentry.ErrorBoundary>
  );
}

🔍 Performance Impact & Data Control

Network Payloads

• bugsnag: Sends minimal JSON payloads (~2–5KB per error). Breadcrumbs are capped at 20 items by default.
• logrocket: Records continuous session data (can be 100KB+ per minute). Offers aggressive scrubbing and sampling controls.
• sentry: Configurable payload size. Replay adds significant bandwidth; non-replay errors stay lean (~3KB).

Privacy & Compliance

All three support:

• IP address anonymization
• GDPR-compliant data deletion
• Custom PII scrubbing

But LogRocket requires more proactive sanitization since it records DOM/network data by default. Sentry and Bugsnag start with conservative data collection.

🔄 Release Tracking & Regression Detection

bugsnag: Release-based stability scores

Bugsnag calculates a "stability score" (% of sessions without errors) per release. Regressions are flagged when new errors appear post-deploy.

// bugsnag — set release stage
Bugsnag.addMetadata('app', { releaseStage: 'production' });
// Dashboard shows: "Release v2.1 caused 12 new errors"

sentry: Release health + commits

Sentry links errors to Git commits and deploys. You can mark releases as "healthy" based on error rates.

// sentry-cli or SDK
Sentry.init({
  dsn: '...'
  release: 'my-app@1.2.3',
  dist: 'prod-us-east'
});
// Dashboard shows: "Commit abc123 introduced this error"

logrocket: No release-centric views

LogRocket groups errors by message/stack, but doesn’t tie them to deploys or calculate stability metrics. You’d need to tag sessions manually with version info.

// logrocket — manual version tagging
LogRocket.getSessionURL(sessionURL => {
  fetch('/log-error', {
    method: 'POST',
    body: JSON.stringify({ sessionURL, appVersion: '1.2.3' })
  });
});

🧩 Extensibility & Ecosystem

• sentry wins for ecosystem depth: supports 50+ languages, has Prometheus exporters, Slack/Discord alerts, and a public API for custom tooling.
• bugsnag offers solid mobile SDKs (iOS/Android) with shared dashboard — useful for cross-platform apps.
• logrocket integrates tightly with support tools (Intercom, Zendesk) so agents can view replays directly from tickets.

📊 When to Use Which: Decision Guide

💡 Final Recommendation

• Start with sentry if you want one observability platform for errors, performance, and traces — especially in full-stack apps.
• Choose logrocket if your biggest pain point is reproducing UI bugs that don’t throw errors (e.g., layout shifts, missing buttons).
• Pick bugsnag if your priority is clean, release-correlated error triage with minimal configuration and no need for visual replay.

Pro Tip: Many teams actually use Sentry + LogRocket together — Sentry for alerting on crashes, LogRocket for deep-dive replay on critical user flows. Bugsnag tends to be chosen when organizations prefer a simpler, error-only focus.

All three are actively maintained, production-ready, and avoid deprecated APIs. None should be ruled out for technical obsolescence — the choice hinges on your team’s debugging workflow and data philosophy.