Skip to main content 首页 创作者 jeremylongshore tons-of-skills-marketplace sentry-observability
sentry-observability Integrate Sentry with your observability stack — logging, metrics, APM, and dashboards.
Use when connecting Sentry to winston/pino/structlog, correlating errors with business
metrics, deciding between Sentry performance and Datadog/New Relic, building Sentry
Discover dashboards, or linking events to external tools via extra context.
Trigger: "sentry observability", "sentry logging", "sentry metrics", "sentry grafana",
"sentry datadog correlation", "sentry discover dashboard".
跳到安装 Skills Marketplace 发现并探索由社区构建的 Agent Skills
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace --skill sentry-observability命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
下载 Zip 下载中... 同仓库更多 Skills langchain-deploy-integration Deploy a LangChain 1.0 / LangGraph 1.0 app to Cloud Run, Vercel, or LangServe correctly — with timeouts sized for chain length, cold-start mitigation, SSE anti-buffering headers, and Secret Manager over .env. Use when prepping a first production deploy, debugging a stream that hangs behind a proxy, or diagnosing p99 latency spikes. Trigger with "langchain deploy", "langchain cloud run", "langchain vercel python", "langchain langserve", or "langchain docker".
langchain-langgraph-agents Build a correct LangGraph 1.0 ReAct agent with create_react_agent — typed tools, error propagation, recursion caps, and stop conditions that actually stop. Use when writing a first tool-calling agent, migrating from AgentExecutor or initialize_agent, or diagnosing an agent that loops on vague prompts. Trigger with "langgraph agent", "create_react_agent", "langgraph tool calling", "AgentExecutor migration", or "agent loop cost".
langchain-langgraph-human-in-loop Build LangGraph 1.0 human-in-the-loop approval flows with interrupt_before /
interrupt_after and Command(resume=...) — JSON-serializable state, clean
resume semantics, and UI wiring for approval decisions. Use when adding an
approval gate before an expensive tool call, wiring a Slack/web UI for agent
approvals, or debugging a graph that crashes on interrupt.
Trigger with "langgraph human in loop", "langgraph interrupt_before",
"langgraph approval flow", "Command resume", "langgraph HITL".
jeremylongshore
jeremylongshore/tons-of-skills-marketplace
打开 GitHub 仓库 name sentry-observability description Integrate Sentry with your observability stack — logging, metrics, APM, and dashboards.
Use when connecting Sentry to winston/pino/structlog, correlating errors with business
metrics, deciding between Sentry performance and Datadog/New Relic, building Sentry
Discover dashboards, or linking events to external tools via extra context.
Trigger: "sentry observability", "sentry logging", "sentry metrics", "sentry grafana",
"sentry datadog correlation", "sentry discover dashboard".
allowed-tools Read, Write, Edit, Grep, Bash(node:*), Bash(npx:*), Bash(pip:*) version 1.51.0 license MIT author Jeremy Longshore <jeremy@intentsolutions.io> tags ["saas","sentry","observability","logging","metrics","apm","grafana","opentelemetry"] compatibility Designed for Claude Code
Sentry Observability Integration
Overview
Wire Sentry into your logging, metrics, APM, and dashboard toolchain so every error carries full context and every metric correlates back to root-cause events. This skill covers three integration layers: structured logging (winston, pino, structlog) with Sentry event ID correlation, business metrics with error-rate tracking, and cross-tool linking via Sentry Discover, Grafana webhooks, and APM tools.
See also: Logging integration details | Metrics patterns | APM tool cross-linking
Prerequisites
Sentry SDK v8+ installed (@sentry/node for Node.js, sentry-sdk for Python)
At least one structured logger configured (winston, pino, or structlog)
Sentry project DSN available in environment (SENTRY_DSN)
Dashboard platform accessible (Sentry Discover, Grafana, or Datadog)
Alert routing strategy decided (who gets paged, where warnings go)
Instructions
Step 1 — Attach Sentry Event IDs to Structured Logs
The core pattern: every log line that triggers a Sentry event carries the event ID, and every Sentry event carries the log context. This creates a two-way link between your log aggregator and Sentry.
Winston (Node.js) — custom transport:
import winston from 'winston' ;
import * as Sentry from '@sentry/node' ;
class SentryTransport extends winston.Transport {
log (info : any , callback : () => void
setImmediate
if
level
'error'
level
'fatal'
const
error
instanceof
Error
error
new
Error
message
Sentry
withScope
(scope ) =>
setTag
'logger'
'winston'
setContext
'log_entry'
level
level
timestamp
timestamp
service
service
const
Sentry
captureException
sentry_event_id
sentry_url
`https://${process.env.SENTRY_ORG} .sentry.io/issues/?query=${eventId} `
const
createLogger
defaultMeta
service
'api-gateway'
transports
new
transports
Console
format
format
json
new
SentryTransport
Pino (Node.js) — hooks pattern:
import pino from 'pino' ;
import * as Sentry from '@sentry/node' ;
const logger = pino ({
hooks : {
logMethod (inputArgs, method, level ) {
if (level >= 50 ) {
const [obj, msg] = typeof inputArgs[0 ] === 'object'
? [inputArgs[0 ], inputArgs[1 ]]
: [{}, inputArgs[0 ]];
Sentry .withScope ((scope ) => {
scope.setTag ('logger' , 'pino' );
const eventId = Sentry .captureException (
obj.err instanceof Error ? obj.err : new Error (String (msg))
);
if (typeof inputArgs[0 ] === 'object' ) {
inputArgs[0 ].sentry_event_id = eventId;
}
});
}
return method.apply (this , inputArgs);
},
},
});
Request ID correlation middleware:
import { randomUUID } from 'crypto' ;
import * as Sentry from '@sentry/node' ;
app.use ((req, res, next ) => {
const requestId = (req.headers ['x-request-id' ] as string ) || randomUUID ();
req.requestId = requestId;
res.setHeader ('x-request-id' , requestId);
Sentry .setTag ('request_id' , requestId);
req.log = logger.child ({ requestId, path : req.path });
next ();
});
Step 2 — Correlate Errors with Business Metrics and APM Connect Sentry events to your metrics pipeline and decide when Sentry performance monitoring is sufficient versus when to add Datadog or New Relic.
Sentry custom metrics (built-in, no extra tools):
import * as Sentry from '@sentry/node' ;
Sentry .metrics .increment ('checkout.attempted' , 1 , {
tags : { payment_provider : 'stripe' , plan : 'enterprise' },
});
Sentry .metrics .increment ('checkout.failed' , 1 , {
tags : { payment_provider : 'stripe' , failure_reason : 'timeout' },
});
Sentry .metrics .distribution ('api.response_time' , responseTimeMs, {
tags : { endpoint : '/api/orders' , status_code : String (res.statusCode ) },
unit : 'millisecond' ,
});
Sentry .metrics .gauge ('db.pool.active' , pool.activeCount , {
tags : { database : 'primary' },
});
Sentry .metrics .set ('incident.affected_users' , userId, {
tags : { incident : 'payment-outage-2026-03' },
});
When to use Sentry performance vs Datadog/New Relic:
Scenario Use Sentry Performance Use Datadog/New Relic Frontend + backend in one view Yes — unified error + perf traces Overkill if Sentry covers your stack Infrastructure metrics (CPU, memory) No — Sentry does not collect infra Yes — native host agent collection 100+ custom metric series Limited query constraints Yes — built for high-cardinality Budget-constrained, < 5 services Yes — one tool, one bill Unnecessary cost
Datadog + Sentry cross-linking via beforeSend:
import tracer from 'dd-trace' ;
import * as Sentry from '@sentry/node' ;
Sentry .init ({
dsn : process.env .SENTRY_DSN ,
beforeSend (event ) {
const span = tracer.scope ().active ();
if (span) {
const traceId = span.context ().toTraceId ();
event.tags = { ...event.tags , 'dd.trace_id' : traceId };
event.contexts = {
...event.contexts ,
datadog : {
trace_url : `https://app.datadoghq.com/apm/trace/${traceId} ` ,
trace_id : traceId,
},
};
}
return event;
},
});
Step 3 — Build Dashboards and Connect External Tools Use Sentry Discover for error analytics, set up Grafana webhooks for unified dashboards, and link Sentry events to external tools via setContext.
Linking all tools via Sentry.setContext('monitoring', ...):
import * as Sentry from '@sentry/node' ;
function setMonitoringContext (req : Request const traceId = Sentry .getActiveSpan ()?.spanContext ().traceId ;
const spanId = Sentry .getActiveSpan ()?.spanContext ().spanId ;
const requestId = req.headers ['x-request-id' ] as string || crypto.randomUUID ();
Sentry .setContext ('monitoring' , {
traceId,
spanId,
requestId,
grafana_dashboard : `https://grafana.example.com/d/abc123?var-trace_id=${traceId} ` ,
kibana_logs : `https://kibana.example.com/app/logs?query=request_id:${requestId} ` ,
datadog_trace : traceId
? `https://app.datadoghq.com/apm/trace/${traceId} `
: undefined ,
});
Sentry .setTag ('request_id' , requestId);
Sentry .setTag ('trace_id' , traceId || 'none' );
Sentry .setTag ('deployment' , process.env .DEPLOYMENT_ID || 'unknown' );
}
app.use ((req, res, next ) => {
setMonitoringContext (req);
next ();
});
Grafana integration via Sentry webhooks:
Configure in Settings > Integrations > Internal Integrations. Point the webhook URL at a receiver that transforms Sentry events into Grafana annotations:
app.post ('/sentry-to-grafana' , async (req, res) => {
const { event } = req.body ;
if (!event) return res.status (200 ).send ('ignored' );
await fetch (`${process.env.GRAFANA_URL} /api/annotations` , {
method : 'POST' ,
headers : {
'Content-Type' : 'application/json' ,
Authorization : `Bearer ${process.env.GRAFANA_API_KEY} ` ,
},
body : JSON .stringify ({
dashboardUID : process.env .GRAFANA_DASHBOARD_UID ,
panelId : 1 ,
time : new Date (event.datetime ).getTime (),
tags : ['sentry' , event.level , event.project ],
text : `**${event.title} **\nLevel: ${event.level} \nView in Sentry` ,
}),
});
res.status (201 ).json ({ status : 'annotation_created' });
});
Alert routing across tools:
Issue Alert: "Critical Production Error"
When: An event is first seen
If: level is fatal AND environment is production
Then: PagerDuty (Critical) + #alerts-critical Slack + Grafana annotation
Frequency: Once per issue
Metric Alert: "Error Rate Spike"
When: Error count > 50 in 5 minutes
Then: PagerDuty (High) + #alerts-production Slack + webhook to Grafana
Resolve: Error count < 5 for 10 minutes
Metric Alert: "Latency Regression"
When: p95(transaction.duration) for /api/* > 2000ms for 10 minutes
Then: #alerts-performance Slack + JIRA ticket via webhook
Resolve: p95 < 1000ms for 15 minutes
Output After completing these steps you will have:
Winston/pino/structlog forwarding errors to Sentry with event IDs stamped into log lines
Sentry custom metrics (counters, gauges, distributions, sets) tracking business KPIs
beforeSend hooks linking Sentry events to Datadog traces and New Relic transactionsSentry.setContext('monitoring', { traceId, spanId }) linking every event to external tool URLsGrafana annotations created from Sentry webhooks on infrastructure dashboards
Tiered alert routing: fatal errors page on-call, warnings go to Slack, latency issues create tickets
Error Handling Error Cause Solution Sentry event IDs missing from logs Transport/processor not wired up Verify SentryTransport is in Winston transports or sentry_processor is in structlog chain beforeSend silently dropping eventsHandler throws or returns undefined Wrap beforeSend in try/catch, always return event on error paths Grafana annotations not appearing Webhook URL wrong or API key expired Test webhook with curl -X POST first; check Grafana API key has annotation write Datadog trace IDs not matching dd-trace not initialized before SentryImport and init dd-trace before @sentry/node Sentry metrics not visible Feature not enabled on plan Custom metrics require Business plan or higher Duplicate events from logger SDK auto-capture and transport both fire Use beforeSend to deduplicate, or disable auto-capture for handled errors Webhook payload format changed Sentry API version upgrade Pin webhook to API v0; validate payload shape in receiver
Examples Example 1 — Full-stack request tracing with log correlation
Request: "Every error in our Express API should show up in both our log aggregator and Sentry with cross-links."
import express from 'express' ;
import pino from 'pino' ;
import * as Sentry from '@sentry/node' ;
import { randomUUID } from 'crypto' ;
Sentry .init ({ dsn : process.env .SENTRY_DSN , tracesSampleRate : 0.1 });
const logger = pino ({ level : 'info' });
const app = express ();
app.use ((req, res, next ) => {
const requestId = (req.headers ['x-request-id' ] as string ) || randomUUID ();
req.requestId = requestId;
res.setHeader ('x-request-id' , requestId);
Sentry .setTag ('request_id' , requestId);
req.log = logger.child ({ requestId, path : req.path , method : req.method });
next ();
});
app.get ('/api/orders/:id' , async (req, res) => {
try {
const order = await db.orders .findById (req.params .id );
if (!order) {
req.log .warn ({ orderId : req.params .id }, 'Order not found' );
return res.status (404 ).json ({ error : 'Not found' });
}
res.json (order);
} catch (error) {
Sentry .withScope ((scope ) => {
scope.setContext ('request' , { params : req.params , requestId : req.requestId });
const eventId = Sentry .captureException (error);
req.log .error ({
err : error,
sentry_event_id : eventId,
sentry_url : `https://sentry.io/issues/?query=${eventId} ` ,
}, 'Order fetch failed' );
});
res.status (500 ).json ({ error : 'Internal error' , request_id : req.requestId });
}
});
Sentry .setupExpressErrorHandler (app);
Example 2 — Grafana dashboard with Sentry error annotations
Request: "Show Sentry errors as annotations on our Grafana latency dashboard."
Result: Create a Sentry internal integration (Settings > Integrations > Internal Integrations) with a webhook URL pointing to your annotation receiver. The receiver transforms Sentry event payloads into Grafana annotation API calls. Error events appear as vertical markers on latency graphs with clickable links back to the Sentry issue.
Resources
Next Steps
Configure sentry-performance-tracing for transaction-level instrumentation
Set up sentry-release-management to correlate deploys with error regressions
Add sentry-ci-integration to catch regressions before they reach production
Review sentry-cost-tuning to manage event volume as observability coverage expands
