| name | firecrawl-observability |
| description | Set up comprehensive observability for FireCrawl integrations with metrics, traces, and alerts. Use when implementing monitoring for FireCrawl operations, setting up dashboards, or configuring alerting for FireCrawl integration health. Trigger with phrases like "firecrawl monitoring", "firecrawl metrics", "firecrawl observability", "monitor firecrawl", "firecrawl alerts", "firecrawl tracing". |
| allowed-tools | Read, Write, Edit |
| version | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
FireCrawl Observability
Overview
Set up comprehensive observability for FireCrawl integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
firecrawl_requests_total |
Counter | Total API requests |
firecrawl_request_duration_seconds |
Histogram | Request latency |
firecrawl_errors_total |
Counter | Error count by type |
firecrawl_rate_limit_remaining |
Gauge | Rate limit headroom |
Prometheus Metrics
import { Registry, Counter, Histogram, Gauge } from 'prom-client';
const registry = new Registry();
const requestCounter = new Counter({
name: 'firecrawl_requests_total',
help: 'Total FireCrawl API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'firecrawl_request_duration_seconds',
help: 'FireCrawl request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'firecrawl_errors_total',
help: 'FireCrawl errors by type',
labelNames: ['error_type'],
registers: [registry],
});
Instrumented Client
async function instrumentedRequest<T>(
method: string,
operation: () => Promise<T>
): Promise<T> {
const timer = requestDuration.startTimer({ method });
try {
const result = await operation();
requestCounter.inc({ method, status: 'success' });
return result;
} catch (error: any) {
requestCounter.inc({ method, status: 'error' });
errorCounter.inc({ error_type: error.code || 'unknown' });
throw error;
} finally {
timer();
}
}
Distributed Tracing
OpenTelemetry Setup
import { trace, SpanStatusCode } from '@opentelemetry/api';
const tracer = trace.getTracer('firecrawl-client');
async function tracedFireCrawlCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`firecrawl.${operationName}`, async (span) => {
try {
const result = await operation();
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (error: any) {
span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
span.recordException(error);
throw error;
} finally {
span.end();
}
});
}
Logging Strategy
Structured Logging
import pino from 'pino';
const logger = pino({
name: 'firecrawl',
level: process.env.LOG_LEVEL || 'info',
});
function logFireCrawlOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'firecrawl',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# firecrawl_alerts.yaml
groups:
- name: firecrawl_alerts
rules:
- alert: FireCrawlHighErrorRate
expr: |
rate(firecrawl_errors_total[5m]) /
rate(firecrawl_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "FireCrawl error rate > 5%"
- alert: FireCrawlHighLatency
expr: |
histogram_quantile(0.95,
rate(firecrawl_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "FireCrawl P95 latency > 2s"
- alert: FireCrawlDown
expr: up{job="firecrawl"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "FireCrawl integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "FireCrawl Request Rate",
"targets": [{
"expr": "rate(firecrawl_requests_total[5m])"
}]
},
{
"title": "FireCrawl Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(firecrawl_request_duration_seconds_bucket[5m]))"
}]
}
]
}
Instructions
Step 1: Set Up Metrics Collection
Implement Prometheus counters, histograms, and gauges for key operations.
Step 2: Add Distributed Tracing
Integrate OpenTelemetry for end-to-end request tracing.
Step 3: Configure Structured Logging
Set up JSON logging with consistent field names.
Step 4: Create Alert Rules
Define Prometheus alerting rules for error rates and latency.
Output
- Metrics collection enabled
- Distributed tracing configured
- Structured logging implemented
- Alert rules deployed
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Missing metrics | No instrumentation | Wrap client calls |
| Trace gaps | Missing propagation | Check context headers |
| Alert storms | Wrong thresholds | Tune alert rules |
| High cardinality | Too many labels | Reduce label values |
Examples
Quick Metrics Endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', registry.contentType);
res.send(await registry.metrics());
});
Resources
Next Steps
For incident response, see firecrawl-incident-runbook.