Full-stack application monitoring platforms

Which brands AI mentions

Best when you want an issue-centric workflow: identify the error, inspect the trace, and determine which release introduced it.

Official site ·Tracing documentation

2. New Relic

(Strongest documented unified error workflow)

Its Errors Inbox combines browser, APM, mobile, and other errors into grouped issues. An error's details can include distributed traces, logs, stack traces, and occurrences by version. Deployment markers can help correlate regressions with releases.docs.newrelic.com+2

Best when you want frontend errors, backend diagnostics, and deployment tracking together in one triage interface.

Official site ·Errors Inbox documentation

3. Datadog

A strong candidate for connecting browser monitoring, backend APM, distributed traces, and deployment/change telemetry. Particularly attractive if your team already uses Datadog for infrastructure and service monitoring.

Best when you need broad full-stack observability and correlation across multiple services. Verify that the specific issue view surfaces all the release and trace context you need.

Official site ·Error Tracking

4. Elastic Observability

Combines application performance monitoring, distributed tracing, logs, and error analysis. A good option for teams that want flexible querying and OpenTelemetry-based instrumentation.

Best for teams that prioritize an integrated telemetry platform and customizable investigation workflows. Confirm how closely its issue grouping and release attribution match your desired experience.

Official site

Comparison against your exact requirements

Datadog's official documentation confirms that its Error Tracking groups similar errors and correlates frontend and backend error data with relevant logs, traces, and RUM events. www.datadoghq.comdocs.datadoghq.comdocs.datadoghq.com New Relic explicitly documents version-aware error groups and deployment markers.docs.newrelic.com+2

My recommendation

• Choose Sentry if the primary unit of work is a developer-facing issue with a stack trace, release regression, and linked request trace.
• Choose Datadog if you want full-stack issue correlation across frontend, backend, logs, traces, and existing infrastructure telemetry.
• Choose New Relic if a centralized error inbox with explicit deployment/version tracking is the most important requirement.

One important qualification: none of these integrations automatically guarantees that every frontend error will map to a backend trace. Trace propagation, sampling, SDK instrumentation, and consistent release/version metadata matter.

For a proof of concept, test one real production-like failure and check whether a single issue shows the frontend stack trace, the corresponding backend distributed trace, and the deployment version that introduced the regression. That will distinguish genuine end-to-end issue correlation from simply having several monitoring tools in one dashboard.