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sentry-performance-tracing

Configures Sentry for performance tracking and distributed tracing to identify bottlenecks.

Install

mkdir -p .claude/skills/sentry-performance-tracing && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7719" && unzip -o skill.zip -d .claude/skills/sentry-performance-tracing && rm skill.zip

Installs to .claude/skills/sentry-performance-tracing

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Set up performance monitoring and distributed tracing with Sentry.
66 charsno explicit “when” trigger
Advanced

Key capabilities

  • Configure distributed tracing and profiling
  • Create custom spans for business-critical operations
  • Implement dynamic sampling for specific endpoints
  • Link performance data to error tracking

How it works

The SDK uses a span-based API to capture latency and request data across services. It supports auto-instrumentation for standard operations and manual span creation for custom business logic.

Inputs & outputs

You give it
Sentry DSN and sampling configuration
You get back
Distributed traces and function-level flamegraphs

When to use sentry-performance-tracing

  • Enable distributed tracing across services
  • Configure profiling to find slow functions
  • Set up performance monitoring for HTTP routes
  • Debug latency bottlenecks in production

About this skill

Sentry Performance Tracing

Overview

Sentry performance monitoring captures distributed traces across your application stack, measuring latency, identifying bottlenecks, and tracking Web Vitals. The v8 SDK uses a span-based API where Sentry.startSpan() replaces the deprecated startTransaction(). Auto-instrumentation covers HTTP, database queries, and framework routes out of the box. Manual spans let you measure business-critical operations. Combined with profiling (profilesSampleRate), you get function-level flamegraphs attached to traces.

Prerequisites

  • Sentry SDK v8+ installed (@sentry/node >= 8.0.0 or sentry-sdk >= 2.0.0)
  • tracesSampleRate > 0 set in Sentry.init() — performance data is not collected at zero
  • Performance monitoring enabled in your Sentry project settings (Settings > Performance)
  • For distributed tracing: all participating services must have Sentry SDK initialized

Instructions

Step 1 — Configure Tracing and Profiling in SDK Init

Set tracesSampleRate to control what percentage of requests generate traces. Use tracesSampler for dynamic, per-endpoint sampling. Add profilesSampleRate to attach function-level flamegraphs to sampled transactions.

TypeScript (@sentry/node):

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

Sentry.init({
  dsn: process.env.SENTRY_DSN,
  tracesSampleRate: 0.2, // 20% of transactions in production

  // Profiling — profiles 10% of sampled transactions
  profilesSampleRate: 0.1,

  // Dynamic sampling overrides tracesSampleRate when defined
  tracesSampler: (samplingContext) => {
    const { name, attributes } = samplingContext;

    // Drop health checks entirely — no trace data
    if (name === 'GET /health') return 0;

    // Always trace payment flows
    if (name?.includes('/api/payment')) return 1.0;

    // Higher sampling for API routes
    if (name?.startsWith('GET /api/') || name?.startsWith('POST /api/')) return 0.2;

    // Default: 5% for everything else
    return 0.05;
  },
});

Python (sentry-sdk):

import os
import sentry_sdk

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    traces_sample_rate=0.2,       # 20% of transactions
    profiles_sample_rate=0.1,     # 10% of sampled transactions get profiled

    # Dynamic sampling via traces_sampler (overrides traces_sample_rate)
    traces_sampler=lambda ctx: (
        0.0 if ctx.get("transaction_context", {}).get("name") == "GET /health"
        else 1.0 if "/api/payment" in ctx.get("transaction_context", {}).get("name", "")
        else 0.2
    ),
)

Key decisions:

  • Start at tracesSampleRate: 0.2 and adjust based on volume and budget
  • tracesSampler takes priority when defined — tracesSampleRate becomes the fallback
  • profilesSampleRate is relative to sampled transactions (0.1 means 10% of the 20% that are sampled)
  • Return 0 from tracesSampler to explicitly drop a transaction, not false

Step 2 — Create Custom Spans for Business Logic

Auto-instrumentation covers HTTP and database calls, but business-critical operations need manual spans. The v8 API provides three span creation methods for different use cases.

Sentry.startSpan() — auto-ending spans (most common):

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

const result = await Sentry.startSpan(
  {
    name: 'order.process',
    op: 'task',
    attributes: {
      'order.id': orderId,
      'order.items': items.length,
    },
  },
  async (span) => {
    // Nested spans automatically become children of the parent
    const validated = await Sentry.startSpan(
      { name: 'order.validate', op: 'validation' },
      async () => validateOrder(order)
    );

    const charged = await Sentry.startSpan(
      { name: 'payment.charge', op: 'http.client' },
      async () => chargePayment(order.total)
    );

    // Set span status based on outcome
    if (!charged.success) {
      span.setStatus({ code: 2, message: 'payment_failed' });
    }

    // Add custom measurements visible in Performance dashboard
    Sentry.setMeasurement('order.item_count', items.length, 'none');
    Sentry.setMeasurement('order.total_cents', order.total, 'none');

    return { validated, charged };
  }
);
// Span automatically ends when callback resolves or rejects

Sentry.startSpanManual() — for spans that cross callback boundaries:

Sentry.startSpanManual(
  { name: 'queue.process', op: 'queue.task' },
  (span) => {
    queue.on('message', async (msg) => {
      try {
        await processMessage(msg);
        span.setStatus({ code: 1 }); // OK
      } catch (error) {
        span.setStatus({ code: 2, message: 'processing_failed' });
        Sentry.captureException(error);
      } finally {
        span.end(); // REQUIRED — must call end() manually
      }
    });
  }
);

Sentry.startInactiveSpan() — background work without changing active context:

const span = Sentry.startInactiveSpan({
  name: 'cache.warmup',
  op: 'cache',
});

await warmCache(); // Other spans created here won't be children of this span

span.end();

Span attributes and measurements:

await Sentry.startSpan(
  { name: 'search.query', op: 'db.query' },
  async (span) => {
    const start = Date.now();
    const results = await searchIndex(query);

    // Attributes — appear in span details, filterable in Sentry UI
    span.setAttribute('search.query', query);
    span.setAttribute('search.results_count', results.length);
    span.setAttribute('search.index', indexName);

    // Measurements — appear in Performance dashboard charts
    Sentry.setMeasurement('search.duration_ms', Date.now() - start, 'millisecond');
    Sentry.setMeasurement('search.result_count', results.length, 'none');

    return results;
  }
);

Python equivalent:

import sentry_sdk

with sentry_sdk.start_span(op="task", name="process_order") as span:
    span.set_data("order_id", order_id)
    span.set_data("item_count", len(items))

    with sentry_sdk.start_span(op="validation", name="validate_input"):
        validate(input_data)

    with sentry_sdk.start_span(op="http.client", name="charge_payment"):
        result = charge(payment)

    if not result.success:
        span.set_status("internal_error")

Step 3 — Enable Auto-Instrumentation and Distributed Tracing

SDK v8 auto-instruments most I/O without configuration. For distributed tracing across services, Sentry propagates sentry-trace and baggage headers automatically on HTTP calls. Custom propagation is needed only for non-HTTP transports (message queues, gRPC, etc.).

Auto-instrumented integrations (Node.js v8):

IntegrationWhat it tracesEnabled by
httpIntegration()All outbound HTTP/HTTPS requestsDefault
expressIntegration()Express route handlers and middlewareDefault with Express
fastifyIntegration()Fastify routesDefault with Fastify
graphqlIntegration()GraphQL resolversDefault with graphql
mongoIntegration()MongoDB queriesDefault with mongodb driver
postgresIntegration()PostgreSQL queries (pg driver)Default with pg
mysqlIntegration()MySQL queriesDefault with mysql2
redisIntegration()Redis commandsDefault with ioredis/redis
prismaIntegration()Prisma ORM queriesDefault with @prisma/client

Express with custom middleware spans:

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

const app = express();

// Sentry auto-instruments all Express routes
// Add custom spans for specific middleware:
app.use('/api', async (req, res, next) => {
  await Sentry.startSpan(
    { name: 'middleware.auth', op: 'middleware' },
    async () => {
      req.user = await authenticateRequest(req);
    }
  );
  next();
});

// Parameterized route names prevent cardinality explosion
// Sentry automatically uses '/api/users/:id' not '/api/users/12345'
app.get('/api/users/:id', async (req, res) => {
  const user = await Sentry.startSpan(
    { name: 'db.getUser', op: 'db.query' },
    () => db.users.findById(req.params.id)
  );
  res.json(user);
});

// Must be after all routes
Sentry.setupExpressErrorHandler(app);

Django/Flask auto-instrumentation (Python):

import sentry_sdk
from sentry_sdk.integrations.django import DjangoIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[DjangoIntegration()],
    traces_sample_rate=0.2,
    profiles_sample_rate=0.1,
)
# All Django views, middleware, and template rendering are traced automatically
# Flask equivalent
from sentry_sdk.integrations.flask import FlaskIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[FlaskIntegration()],
    traces_sample_rate=0.2,
)
# FastAPI equivalent
from sentry_sdk.integrations.fastapi import FastApiIntegration
from sentry_sdk.integrations.starlette import StarletteIntegration

sentry_sdk.init(
    dsn=os.environ["SENTRY_DSN"],
    integrations=[FastApiIntegration(), StarletteIntegration()],
    traces_sample_rate=0.2,
)

Distributed tracing — custom header propagation:

When Sentry cannot automatically propagate headers (non-HTTP transports, custom fetch wrappers), extract and inject manually:

// Service A: Extract trace headers from the active span
const activeSpan = Sentry.getActiveSpan();
const traceHeaders = {
  'sentry-trace': Sentry.spanToTraceHeader(activeSpan),
  'baggage': Sentry.spanToBaggageHeader(activeSpan),
};

// Pass headers to downstream service via HTTP, message queue, etc.
await fetch('https://service-b.internal/api/process', {
  headers: { ...traceHeaders, 'Content-Type': 'application/json' },
  body: JSON.stringify(payload),
});

// Service B: Sentry SDK automatically reads sentry-trace and baggage
// from incoming request headers and continues the same t

---

*Content truncated.*

When not to use it

  • When tracesSampleRate is set to zero
  • When services are not initialized with the Sentry SDK

Prerequisites

Sentry SDK v8+Performance monitoring enabled in project settings

Limitations

  • Performance data is not collected if tracesSampleRate is zero
  • Dynamic sampling overrides tracesSampleRate when defined

How it compares

This workflow provides function-level profiling and distributed tracing rather than simple request logging.

Compared to similar skills

sentry-performance-tracing side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
sentry-performance-tracing (this skill)126dReviewAdvanced
autotel01moReviewIntermediate
ai-debug-harness03moReviewAdvanced
worker-benchmarks32moReviewAdvanced

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