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.zipInstalls 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.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
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 orsentry-sdk>= 2.0.0) tracesSampleRate > 0set inSentry.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: 0.2and adjust based on volume and budget tracesSamplertakes priority when defined —tracesSampleRatebecomes the fallbackprofilesSampleRateis relative to sampled transactions (0.1 means 10% of the 20% that are sampled)- Return
0fromtracesSamplerto explicitly drop a transaction, notfalse
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):
| Integration | What it traces | Enabled by |
|---|---|---|
httpIntegration() | All outbound HTTP/HTTPS requests | Default |
expressIntegration() | Express route handlers and middleware | Default with Express |
fastifyIntegration() | Fastify routes | Default with Fastify |
graphqlIntegration() | GraphQL resolvers | Default with graphql |
mongoIntegration() | MongoDB queries | Default with mongodb driver |
postgresIntegration() | PostgreSQL queries (pg driver) | Default with pg |
mysqlIntegration() | MySQL queries | Default with mysql2 |
redisIntegration() | Redis commands | Default with ioredis/redis |
prismaIntegration() | Prisma ORM queries | Default 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
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.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| sentry-performance-tracing (this skill) | 1 | 26d | Review | Advanced |
| autotel | 0 | 1mo | Review | Intermediate |
| ai-debug-harness | 0 | 3mo | Review | Advanced |
| worker-benchmarks | 3 | 2mo | Review | Advanced |
Try saying
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