Performance Monitoring

Sentry goes beyond tracking page load metrics. By enabling Tracing, Sentry automatically instruments the frameworks and libraries you use — capturing detailed performance data for every request across your entire application stack.

Getting Set Up

Enable tracing in your SDK by setting tracesSampleRate. For most frameworks (Next.js, Laravel, Rails, Django, Express, and others), Sentry auto-instruments common operations like HTTP requests, database queries, and template rendering out of the box.

For applications with both frontend and backend services, set up distributed tracing to follow requests across service boundaries. Learn more about trace propagation for your platform.

Ways to Monitor Performance

Pre-built Dashboards

After turning on tracing, you'll automatically see Sentry Dashboards that give you a high-level view of performance data for each layer of your stack:

• Frontend — Core Web Vitals, transaction duration, error rates
• Backend — database queries, API calls, caches, queues, crons
• Mobile — cold/warm app starts, TTID & TTFD, screen load times
• AI — LLM call latency, token usage, tool execution performance

Automated Performance Issues

Sentry automatically detects common performance problems and groups them into performance issues:

• N+1 queries and API calls
• Consecutive DB queries or HTTP requests that could be batched
• Database or file I/O on the main thread (blocking UI)
• And more

These appear alongside error issues in your Issues feed, so you can triage and resolve them the same way.

Trace Explorer

The Trace Explorer lets you query all your span data by any attribute. Find the p95 duration of a specific endpoint, identify which user segments are experiencing slowdowns, or compare a time window against your baseline to isolate regressions.

You can also calculate span metrics — custom aggregations like p50, p95, and p99 durations grouped by any attribute — and use them to build dashboards and alerts.

Connected Context

Performance data in Sentry isn't siloed. Every trace connects to:

• Logs — see what your application logged during a slow request
• Session Replay — watch the user experience during a performance issue
• Profiling — drill from a slow span into the exact functions consuming CPU time
• Seer — get AI-powered root cause analysis for performance regressions

How It Works Under the Hood

Instead of capturing predefined metrics at fixed intervals, Sentry instruments the libraries you rely on, providing detailed telemetry for Web Vitals, file I/O, network requests, and more. Performance data is sent as spans — the smallest unit of work in a trace. Traces are assembled server-side and power all of Sentry's performance tools, so every high-level metric is backed by the raw tracing data you can drill into.

Next Steps

• Querying Traces guide — practical queries for finding slow pages and bottlenecks
• Adding Custom Spans guide — instrument your own code for visibility beyond auto-instrumentation
• Distributed Tracing tutorial — follow along with a sample React + Express app