monitoring-expert
Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments…
Skill by https://github.com/Jeffallan
Install
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About
Use cases: testing, devops
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
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- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/monitoring-expert
What's inside
- Skill name
monitoring-expert- Description
- Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing. Implements Prometheus/Grafana stacks, conducts load testing, performs application profiling, and plans infrastructure capacity. Use when setting up application monitoring, adding observability to services, debugging production issues with logs/metrics/traces, running load tests with k6 or Artillery, profiling CPU/memory bottlenecks, or forecasting capacity needs.
- License
- MIT
- Metadata
- role: specialist · scope: implementation · author: https://github.com/Jeffallan · domain: devops · company: https://synergetic.solutions · version: 1.1.0 · triggers: monitoring, observability, logging, metrics, tracing, alerting, Prometheus, Grafana, DataDog, APM, performance testing, load testing, profiling, capacity planning, bottleneck · output-format: code · related-skills: devops-engineer, debugging-wizard, architecture-designer
- Instructions
- 167 lines in SKILL.md · view on GitHub
Files (9)
- SKILL.md
- alerting-rules.md · references/
- application-profiling.md · references/
- capacity-planning.md · references/
- dashboards.md · references/
- opentelemetry.md · references/
- performance-testing.md · references/
- prometheus-metrics.md · references/
- structured-logging.md · references/
SKILL.md (first lines)
# Monitoring Expert
Observability and performance specialist implementing comprehensive monitoring, alerting, tracing, and performance testing systems.
## Core Workflow
1. **Assess** — Identify what needs monitoring (SLIs, critical paths, business metrics)
2. **Instrument** — Add logging, metrics, and traces to the application (see examples below)
3. **Collect** — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
4. **Visualize** — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
5. **Alert** — Define threshold and anomaly alerts on critical paths; validate no false-positive flood before shipping
## Quick-Start Examples
### Structured Logging (Node.js / Pino)
```js
import pino from 'pino';
const logger = pino({ level: 'info' });
// Good — structured fields, includes correlation ID
logger.info({ requestId: req.id, userId: req.user.id, durationMs: elapsed }, 'order.created');
// Bad — string interpolation, no correlation
console.log(`Order created for user ${userId}`);
```
### Prometheus Metrics (Node.js)
```js
import { Counter, Histogram, register } from 'prom-client';
const httpRequests = new Counter({
name: 'http_requests_total',
help: 'Total HTTP requests',
labelNames: ['method', 'route', 'status'],
});
const httpDuration = new Histogram({
name: 'http_request_duration_seconds',
help: 'HTTP request latency',
labelNames: ['method', 'route'],
buckets: [0.05, 0.1, 0.3, 0.5, 1, 2, 5],
});
// Instrument a route
app.use((req, res, next) => {
const end = httpDuration.startTimer({ method: req.method, route: req.path });
res.on('finish', () => {
httpRequests.inc({ method: req.method, route: req.path, status: res.statusCode });
end();
});
next();
});
// Expose scrape endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', register.contentType);
res.end(await register.metrics());
});
```
### OpenTelemetry Tracing (Node.js)
```js
import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { trace } from '@opentelemetry/api';
const sdk = new NodeSDK({
traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),
});
sdk.start();
// Manual span around a critical operation
const tracer = trace.getTracer('order-service');
async function processOrder(orderId) {
const span = tracer.startSpan('order.process');
span.setAttribute('order.id', orderId);
try {
const result = await db.saveOrder(orderId);
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (err) {
span.recordException(err);
span.setStatus({ code: SpanStatusCode.ERROR });
throw err;
} finally {
span.end();
}
}
```
### Prometheus Alerting Rule
```yaml
groups:
- name: api.rules
rules:
- alert: HighErrorRate
expr: |
rate(http_requests_total{status=~"5.."}[5m])
/ rate(http_requests_total[5m]) > 0.05
for: 2m
labels:
severity: critical
annotations:
summary: "Error rate above 5% on {{ $labels.route }}"
```
### k6 Load Test
```js
import http from 'k6/http';
import { check, sleep } from 'k6';
export const options = {
stages: [
{ duration: '1m', target: 50 }, // ramp up
{ duration: '5m', target: 50 }, // sustained load
{ duration: '1m', target: 0 }, // ramp down
],
thresholds: {From Jeffallan/claude-skills, MIT.
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Signals
- Stars
- 12,039
- Forks
- 1,151
- Open issues
- 32
- Last commit (this folder)
- Oct 15, 2026 (13 days ago)
- Last release
- Oct 16, 2026 (12 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.1.0
- License
- MIT
- Repository
- github.com/Jeffallan/claude-skills
- Website
- jarvisaios.vercel.app
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
monitoring-expert skill. Agent Mart. https://agentmart.dev/skills/jeffallan-monitoring-expert (last updated 2026-10-24)