sentry-performance-tuning
Optimize Sentry performance monitoring for lower overhead and higher signal. Use when tuning tracesSampleRate vs tracesSampler, configuring continuous profiling, fixing high-cardinality transaction names, adding custom span measurements, reducing SDK overhead, or setting Web Vitals thresholds. Trigger: "sentry performance optimize", "tune sentry sampling", "reduce sentry overhead", "sentry web vitals", "sentry profiling setup".
Best use case
sentry-performance-tuning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Optimize Sentry performance monitoring for lower overhead and higher signal. Use when tuning tracesSampleRate vs tracesSampler, configuring continuous profiling, fixing high-cardinality transaction names, adding custom span measurements, reducing SDK overhead, or setting Web Vitals thresholds. Trigger: "sentry performance optimize", "tune sentry sampling", "reduce sentry overhead", "sentry web vitals", "sentry profiling setup".
Teams using sentry-performance-tuning should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sentry-performance-tuning/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sentry-performance-tuning Compares
| Feature / Agent | sentry-performance-tuning | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Optimize Sentry performance monitoring for lower overhead and higher signal. Use when tuning tracesSampleRate vs tracesSampler, configuring continuous profiling, fixing high-cardinality transaction names, adding custom span measurements, reducing SDK overhead, or setting Web Vitals thresholds. Trigger: "sentry performance optimize", "tune sentry sampling", "reduce sentry overhead", "sentry web vitals", "sentry profiling setup".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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.
```typescript
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.
```typescript
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.**
```typescript
// 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'`.
```typescript
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;
}
);
```
| Measurement | Unit | Use case |
|-------------|------|----------|
| `cart.total_cents` | `none` | Revenue correlation with latency |
| `query.rows_scanned` | `none` | Database query efficiency |
| `cache.hit_rate` | `percent` | Cache performance per route |
| `upload.file_size` | `byte` | File upload impact on response time |
### Step 5 — Reduce SDK Overhead
For high-throughput services (>1000 req/s), every integration and breadcrumb counts.
```typescript
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):
```typescript
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.
```typescript
// 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.
```typescript
Sentry.init({
dsn: process.env.SENTRY_DSN,
integrations: [
Sentry.browserTracingIntegration({
shouldCreateSpanForRequest: (url) =>
!url.includes('googleapis.com') && !url.includes('analytics'),
}),
],
tracesSampleRate: 0.1,
});
```
| Metric | Good | Poor | Measures |
|--------|------|------|----------|
| **LCP** | < 2.5s | > 4.0s | Visual load completion |
| **INP** | < 200ms | > 500ms | Input responsiveness (replaced FID) |
| **CLS** | < 0.1 | > 0.25 | Visual stability |
| **TTFB** | < 800ms | > 1800ms | Server response time |
**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
| Symptom | Root Cause | Fix |
|---------|-----------|-----|
| Performance tab empty | `tracesSampler` returns 0 for all routes | Log sampler decisions; check default return |
| "Too many unique transaction names" | Dynamic IDs in names | Parameterize names; IDs in `attributes` (Step 3) |
| SDK adds >50ms latency | Too many integrations/breadcrumbs | Reduce `maxBreadcrumbs` to 20; disable `Console` |
| Profiling tab empty | Missing `@sentry/profiling-node` | Install package; set `profilesSampleRate: 1.0` |
| Incomplete distributed traces | Independent sampling decisions | Check `parentSampled` first in sampler (Step 1) |
| `setMeasurement` values missing | Called outside active span | Call inside `Sentry.startSpan()` callback |
| Web Vitals null | Missing `browserTracingIntegration` | Add integration; set `tracesSampleRate > 0` |
## Examples
### TypeScript — Express Production Setup
```typescript
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)$/)) return 0;
if (name?.includes('/checkout')) return 1.0;
if (name?.startsWith('POST ')) return 0.25;
if (name?.startsWith('GET /api/')) return 0.1;
return 0.05;
},
profilesSampleRate: 1.0,
maxBreadcrumbs: 20,
beforeSendSpan: (span) =>
span.description?.includes('health') ? null : span,
});
const app = express();
Sentry.setupExpressErrorHandler(app);
app.get('/api/search', async (req, res) => {
const results = await Sentry.startSpan(
{ name: 'search.execute', op: 'function' },
async () => {
const data = await searchService.query(req.query.q as string);
Sentry.setMeasurement('search.result_count', data.length, 'none');
return data;
}
);
res.json(results);
});
```
### Python — FastAPI Production Setup
```python
import os, re, sentry_sdk
from fastapi import FastAPI
def traces_sampler(ctx: dict) -> float:
tx = ctx.get("transaction_context", {})
name = tx.get("name", "")
parent = ctx.get("parent_sampled")
if parent is not None:
return 1.0 if parent else 0.0
if re.search(r"/(health|ready|ping)$", 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](https://docs.sentry.io/product/performance/) — Dashboard overview and configuration
- [Sampling Configuration](https://docs.sentry.io/platforms/javascript/configuration/sampling/) — `tracesSampler` deep dive
- [Profiling (Node.js)](https://docs.sentry.io/platforms/javascript/guides/node/profiling/) — Setup and tuning
- [Profiling (Python)](https://docs.sentry.io/platforms/python/profiling/) — `sentry-sdk[profiling]` setup
- [Web Vitals](https://docs.sentry.io/product/insights/web-vitals/) — LCP, INP, CLS dashboards
- [Custom Instrumentation](https://docs.sentry.io/platforms/javascript/performance/instrumentation/custom-instrumentation/) — `setMeasurement()` API
- [Discover Queries](https://docs.sentry.io/product/explore/discover-queries/) — SQL-like query builder
- [Span Operations](https://develop.sentry.dev/sdk/performance/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 deploysRelated Skills
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