posthog-observability
Set up comprehensive observability for PostHog integrations with metrics, traces, and alerts.Use when implementing monitoring for PostHog operations, setting up dashboards,or configuring alerting for PostHog integration health.Trigger with phrases like "posthog monitoring", "posthog metrics","posthog observability", "monitor posthog", "posthog alerts", "posthog tracing".
When & Why to Use This Skill
This Claude skill provides a comprehensive framework for implementing observability in PostHog integrations. It streamlines the setup of Prometheus metrics, OpenTelemetry distributed tracing, and structured logging, enabling developers to maintain high system reliability through real-time performance tracking and automated alerting.
Use Cases
- API Performance Tracking: Monitor PostHog request latency and duration using Prometheus histograms to identify and resolve performance bottlenecks.
- Automated Incident Alerting: Configure AlertManager rules to receive instant notifications for high error rates, latency spikes, or integration downtime.
- End-to-End Debugging: Utilize OpenTelemetry distributed tracing to visualize request flows and pinpoint failures within complex PostHog integration pipelines.
- Health & Capacity Management: Track API rate limits and request volumes via Grafana dashboards to ensure service stability and optimize resource usage.
| name | posthog-observability |
|---|---|
| description | | |
| allowed-tools | Read, Write, Edit |
| version | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
PostHog Observability
Overview
Set up comprehensive observability for PostHog integrations.
Prerequisites
- Prometheus or compatible metrics backend
- OpenTelemetry SDK installed
- Grafana or similar dashboarding tool
- AlertManager configured
Metrics Collection
Key Metrics
| Metric | Type | Description |
|---|---|---|
posthog_requests_total |
Counter | Total API requests |
posthog_request_duration_seconds |
Histogram | Request latency |
posthog_errors_total |
Counter | Error count by type |
posthog_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: 'posthog_requests_total',
help: 'Total PostHog API requests',
labelNames: ['method', 'status'],
registers: [registry],
});
const requestDuration = new Histogram({
name: 'posthog_request_duration_seconds',
help: 'PostHog request duration',
labelNames: ['method'],
buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
registers: [registry],
});
const errorCounter = new Counter({
name: 'posthog_errors_total',
help: 'PostHog 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('posthog-client');
async function tracedPostHogCall<T>(
operationName: string,
operation: () => Promise<T>
): Promise<T> {
return tracer.startActiveSpan(`posthog.${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: 'posthog',
level: process.env.LOG_LEVEL || 'info',
});
function logPostHogOperation(
operation: string,
data: Record<string, any>,
duration: number
) {
logger.info({
service: 'posthog',
operation,
duration_ms: duration,
...data,
});
}
Alert Configuration
Prometheus AlertManager Rules
# posthog_alerts.yaml
groups:
- name: posthog_alerts
rules:
- alert: PostHogHighErrorRate
expr: |
rate(posthog_errors_total[5m]) /
rate(posthog_requests_total[5m]) > 0.05
for: 5m
labels:
severity: warning
annotations:
summary: "PostHog error rate > 5%"
- alert: PostHogHighLatency
expr: |
histogram_quantile(0.95,
rate(posthog_request_duration_seconds_bucket[5m])
) > 2
for: 5m
labels:
severity: warning
annotations:
summary: "PostHog P95 latency > 2s"
- alert: PostHogDown
expr: up{job="posthog"} == 0
for: 1m
labels:
severity: critical
annotations:
summary: "PostHog integration is down"
Dashboard
Grafana Panel Queries
{
"panels": [
{
"title": "PostHog Request Rate",
"targets": [{
"expr": "rate(posthog_requests_total[5m])"
}]
},
{
"title": "PostHog Latency P50/P95/P99",
"targets": [{
"expr": "histogram_quantile(0.5, rate(posthog_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 posthog-incident-runbook.