posthog-observability

jeremylongshore's avatarfrom jeremylongshore

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".

⭐939stars🔀114forks📁View on GitHub🕐Updated Jan 11, 2026

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.
nameposthog-observability
description|
allowed-toolsRead, Write, Edit
version1.0.0
licenseMIT
authorJeremy 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.