Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/sentry-pack/skills/sentry-performance-tuning/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill sentry-performance-tuning. Copyright stays with the author (MIT).

Sentry Performance Tuning

Overview

Optimize Sentry's performance monitoring pipeline to maximize signal quality while minimizing SDK overhead and event volume costs. Covers the v8 SDK API for @sentry/node, @sentry/browser, and sentry-sdk (Python), targeting sentry.io or self-hosted Sentry 24.1+.

Prerequisites

• Sentry SDK v8+ installed (@sentry/node >= 8.0.0 or sentry-sdk >= 2.0.0)
• Sentry.init() called with a valid DSN before any application code runs
• Performance monitoring enabled (tracesSampleRate > 0 or a tracesSampler function)
• Access to the Sentry Performance dashboard to verify changes

Instructions

Step 1 — Replace Static tracesSampleRate with Dynamic tracesSampler

A flat tracesSampleRate: 0.1 samples all routes equally. The tracesSampler callback makes per-transaction decisions based on route, operation type, and upstream trace context.

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

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  // tracesSampler replaces tracesSampleRate — do not set both
  tracesSampler: (samplingContext) => {
    const { name, attributes, parentSampled } = samplingContext;

    // Honor parent sampling for distributed trace consistency
    if (parentSampled !== undefined) return parentSampled ? 1.0 : 0;

    // Drop noise — health probes, static assets
    if (name?.match(/\/(health|ready|alive|ping|metrics)$/)) return 0;
    if (name?.match(/\.(js|css|png|jpg|svg|woff2?|ico)$/)) return 0;

    // Always sample business-critical paths
    if (name?.includes('/checkout') || name?.includes('/payment')) return 1.0;

    // Higher sampling for write operations (mutations are riskier)
    if (name?.startsWith('POST ') || name?.startsWith('PUT ')) return 0.25;

    // Moderate sampling for read APIs
    if (name?.startsWith('GET /api/')) return 0.1;

    // Low sampling for background work
    if (name?.startsWith('job:') || name?.startsWith('queue:')) return 0.05;

    // User-tier sampling (via custom attributes from middleware)
    if (attributes?.['user.plan'] === 'enterprise') return 0.5;

    return 0.05; // Default: 5%
  },
});

Step 2 — Configure Profiling with profilesSampleRate

The profilesSampleRate controls what fraction of traced transactions get profiled. Setting it to 1.0 with a 5% tracesSampler means 5% of traffic is profiled.

import { nodeProfilingIntegration } from '@sentry/profiling-node';

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  integrations: [nodeProfilingIntegration()],
  tracesSampler: (ctx) => { /* ... from Step 1 ... */ },

  // Effective rate = tracesSampler rate * profilesSampleRate
  profilesSampleRate: 1.0,

  // Alternative: Continuous profiling (v8.7.0+) — profiles the entire process
  // profileSessionSampleRate: 0.1,  // 10% of server instances
});

Tuning: Start at profilesSampleRate: 0.1 in production. Profiling adds ~3-5% CPU overhead per profiled transaction. Continuous profiling (profileSessionSampleRate) has lower per-transaction cost but runs on sampled instances continuously.

Step 3 — Fix Transaction Naming (Prevent Cardinality Explosion)

Names with dynamic IDs (/api/users/12345) create thousands of unique entries, degrading dashboard performance and inflating quota. Route templates go in the name, dynamic values go in attributes.

// BAD — creates thousands of unique transaction entries
// GET /api/users/12345, GET /api/users/67890, ...

// GOOD — Sentry auto-parameterizes Express/Koa/Fastify routes
// GET /api/users/:userId

// For custom spans, always parameterize:
Sentry.startSpan(
  {
    name: 'order.process',           // No dynamic IDs in name
    op: 'task',
    attributes: {
      'order.id': orderId,           // Filterable in Discover queries
      'order.total_cents': totalCents,
      'customer.tier': customerTier,
    },
  },
  async (span) => {
    const result = await processOrder(orderId);
    span.setAttribute('order.status', result.status);
    return result;
  }
);

Detect cardinality issues with a Discover query:

SELECT count(), transaction FROM transactions GROUP BY transaction ORDER BY count() DESC

Step 4 — Add Custom Measurements

Custom measurements appear in the Performance dashboard and can be charted, alerted on, and queried in Discover. Unit types: 'millisecond', 'byte', 'none' (count), 'percent'.

await Sentry.startSpan(
  { name: 'search.execute', op: 'function' },
  async (span) => {
    const start = performance.now();
    const results = await searchService.query(term);

    Sentry.setMeasurement('search.latency', performance.now() - start, 'millisecond');
    Sentry.setMeasurement('search.result_count', results.length, 'none');
    Sentry.setMeasurement('search.memory_delta',
      process.memoryUsage().heapUsed - memBefore, 'byte');

    span.setAttribute('search.cache_hit', results.fromCache);
    return results;
  }
);

Step 5 — Reduce SDK Overhead

For high-throughput services (>1000 req/s), every integration and breadcrumb counts.

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  maxBreadcrumbs: 20,           // Default: 100. Each ~0.5-2KB.
  maxValueLength: 500,          // Truncate long string values
  maxAttachmentSize: 5_242_880, // 5MB (default: 20MB)

  // Remove noisy integrations
  integrations: (defaults) => defaults.filter(
    (i) => i.name !== 'Console'
  ),

  // Trim oversized stack traces
  beforeSend: (event) => {
    if (event.exception?.values) {
      for (const exc of event.exception.values) {
        if (exc.stacktrace?.frames && exc.stacktrace.frames.length > 30) {
          exc.stacktrace.frames = [
            ...exc.stacktrace.frames.slice(0, 10),
            ...exc.stacktrace.frames.slice(-20),
          ];
        }
      }
    }
    return event;
  },

  // Drop internal/noise spans
  beforeSendSpan: (span) => {
    if (span.description?.startsWith('internal.')) return null;
    return span;
  },
});

Browser SDK lazy loading (saves ~30KB gzipped from critical path):

async function initSentry() {
  const Sentry = await import('@sentry/browser');
  Sentry.init({
    dsn: process.env.SENTRY_DSN,
    integrations: [Sentry.browserTracingIntegration()],
    tracesSampleRate: 0.1,
  });
}
window.addEventListener('load', initSentry, { once: true });

Step 6 — Span Best Practices (Avoid Span Explosion)

Only wrap operations with measurable latency (>1ms). Never span synchronous lookups or individual loop iterations.

// BAD — sub-microsecond config read; span overhead exceeds operation cost
function getConfig(key: string) {
  return Sentry.startSpan({ name: 'config.get', op: 'function' }, () => config[key]);
}

// BAD — N spans per request from loop iterations
for (const item of items) {
  await Sentry.startSpan({ name: 'process.item', op: 'function' }, () => processItem(item));
}

// GOOD — span the batch, count in attributes
await Sentry.startSpan(
  { name: 'process.batch', op: 'function', attributes: { 'batch.size': items.length } },
  async () => Promise.all(items.map(processItem))
);

// GOOD — span external I/O with real latency
async function fetchUserProfile(userId: string) {
  return Sentry.startSpan(
    { name: 'user.fetch_profile', op: 'http.client', attributes: { 'user.id': userId } },
    async () => fetch(`${USER_SERVICE_URL}/users/${userId}`).then(r => r.json())
  );
}

Step 7 — Web Vitals Monitoring

The Browser SDK auto-captures Core Web Vitals. Filter span creation to avoid noise from third-party scripts.

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  integrations: [
    Sentry.browserTracingIntegration({
      shouldCreateSpanForRequest: (url) =>
        !url.includes('googleapis.com') && !url.includes('analytics'),
    }),
  ],
  tracesSampleRate: 0.1,
});

Alert thresholds: LCP p75 > 2.5s (5 min), INP p75 > 200ms (5 min), CLS p75 > 0.1 (15 min).

Step 8 — Dashboard Queries for Performance Trends

-- Slowest transactions (p95)
SELECT transaction, p95(transaction.duration), count()
FROM transactions WHERE transaction.duration:>1000
ORDER BY p95(transaction.duration) DESC

-- Regression detection (20%+ slower vs last week)
SELECT transaction, p75(transaction.duration),
       compare(p75(transaction.duration), -7d) as vs_last_week
FROM transactions GROUP BY transaction
HAVING compare(p75(transaction.duration), -7d) > 1.2

-- Span breakdown for a route
SELECT span.op, span.description, p75(span.duration), count()
FROM spans WHERE transaction:/api/checkout
ORDER BY p75(span.duration) DESC

Output

• Dynamic sampling active — health checks at 0%, payments at 100%, defaults at 5%
• Profiling enabled with profilesSampleRate or continuous profileSessionSampleRate
• Transaction names parameterized — cardinality under 500 unique names
• Custom measurements tracking business KPIs alongside latency
• SDK overhead reduced — fewer breadcrumbs, filtered integrations, trimmed payloads
• Web Vitals monitored with alerts at Google's recommended thresholds

Verify at Sentry Stats (Settings > Stats) — volume should drop while data quality improves.

Error Handling

Examples

TypeScript — Express Production Setup

import * as Sentry from '@sentry/node';
import { nodeProfilingIntegration } from '@sentry/profiling-node';
import express from 'express';

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  environment: process.env.NODE_ENV,
  release: process.env.SENTRY_RELEASE,
  integrations: [nodeProfilingIntegration()],
  tracesSampler: (ctx) => {
    const { name, parentSampled } = ctx;
    if (parentSampled !== undefined) return parentSampled ? 1.0 : 0;
    if (name?.match(/\/(health|ready|ping)$/)) return 0;
    if (name?.includes('/checkout')) return 1.0;
    if (name?.startsWith('POST ')) return 0.25;
    if (name?.startsWith('GET /api/')) return 0.1;
    return 0.05;
  },
  profilesSampleRate: 1.0,
  maxBreadcrumbs: 20,
  beforeSendSpan: (span) =>
    span.description?.includes('health') ? null : span,
});

const app = express();
Sentry.setupExpressErrorHandler(app);

app.get('/api/search', async (req, res) => {
  const results = await Sentry.startSpan(
    { name: 'search.execute', op: 'function' },
    async () => {
      const data = await searchService.query(req.query.q as string);
      Sentry.setMeasurement('search.result_count', data.length, 'none');
      return data;
    }
  );
  res.json(results);
});

Python — FastAPI Production Setup

import os, re, sentry_sdk
from fastapi import FastAPI

def traces_sampler(ctx: dict) -> float:
    tx = ctx.get("transaction_context", {})
    name = tx.get("name", "")
    parent = ctx.get("parent_sampled")
    if parent is not None:
        return 1.0 if parent else 0.0
    if re.search(r"/(health|ready|ping)$", name):
        return 0.0
    if "/checkout" in name or "/payment" in name:
        return 1.0
    if name.startswith(("POST ", "PUT ")):
        return 0.25
    if name.startswith("GET /api/"):
        return 0.1
    if tx.get("op") == "task":
        return 0.05
    return 0.05

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    environment=os.environ.get("ENVIRONMENT", "development"),
    release=os.environ.get("SENTRY_RELEASE"),
    traces_sampler=traces_sampler,
    profiles_sample_rate=1.0,
    max_breadcrumbs=20,
    before_send_transaction=lambda event, hint: (
        None if event.get("transaction", "").endswith("/health") else event
    ),
)

app = FastAPI()

@app.get("/api/search")
async def search(q: str):
    with sentry_sdk.start_span(op="function", name="search.execute") as span:
        results = await search_service.query(q)
        sentry_sdk.set_measurement("search.result_count", len(results), "none")
        span.set_data("search.query_length", len(q))
        return {"results": results}

Resources

• Performance Monitoring — Dashboard overview and configuration
• Sampling Configuration — tracesSampler deep dive
• Profiling (Node.js) — Setup and tuning
• Profiling (Python) — sentry-sdk[profiling] setup
• Web Vitals — LCP, INP, CLS dashboards
• Custom Instrumentation — setMeasurement() API
• Discover Queries — SQL-like query builder
• Span Operations — Naming conventions for op field

Next Steps

1. Validate sampling — Check Sentry Stats (Settings > Stats) to confirm volume dropped while critical route coverage is maintained
2. Set up alerts — Create metric alerts for LCP p75 > 2.5s and INP p75 > 200ms
3. Review flamegraphs — Navigate to a sampled transaction and examine the Profile tab for CPU hotspots
4. Audit cardinality — Run the Discover query from Step 3 to find remaining high-cardinality names
5. Add business measurements — Identify 3-5 KPIs (cart value, search latency) and add setMeasurement() calls
6. Server-side sampling — Use Sentry's Dynamic Sampling UI (Settings > Performance) for rules without code deploys