How we debug production issues at PostHog (Complete Walkthrough)

Learn how PostHog's Error Tracking helped us identify and fix a critical production bug in minutes. In this tutorial, Ross from the Batch Exports team walks through a real-world debugging session, showing you: ✅ How to set up error tracking with the PostHog Python SDK ✅ Using try-except blocks with posthog.capture_exception() ✅ Enriching errors with custom properties for better debugging ✅ Setting up auto-assignment rules to route errors to the right team ✅ Filtering errors by environment and team ✅ Using stack traces and custom properties to diagnose issues ✅ A complete walkthrough of debugging a ClickHouse query error We're using Temporal for workflow execution and demonstrate how to integrate PostHog Error Tracking into your batch processing jobs. Watch as we trace an error from the dashboard through the stack trace to find the root cause: an unsupported model type being passed to our HTTP batch export. Perfect for product engineers, backend developers, and anyone working with Python applications who wants to improve their error monitoring and debugging workflow. 🔗 Try PostHog: https://posthog.com 📚 PostHog Python SDK: https://posthog.com/docs/libraries/python 📖 Error Tracking Docs: https://posthog.com/docs/error-tracking #ErrorTracking #Python #Debugging #PostHog #ProductEngineering #SoftwareDevelopment What is PostHog? PostHog is an all-in-one developer platform for building successful products. We provide product analytics, web analytics, session replay, error tracking, feature flags, experiments, surveys, LLM analytics, data warehouse, CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack.