Build an end to end JSON logging system for clients apps
Article Summary
Liang Ma and Wei Zhu from Pinterest built a JSON logging system that catches production issues hours before traditional metrics even notice. Here's how they gave mobile teams real-time visibility into 300 billion ideas.
After a critical iOS memory incident exposed blind spots in client monitoring, Pinterest's engineering team created an end-to-end logging pipeline. The system needed zero backend work from developers, supported schemaless payloads, and delivered real-time querying through OpenSearch integration.
Key Takeaways
- Schemaless JSON logs flow from apps through Kafka to OpenSearch and Hive
- Log-based metrics enable real-time alerting on production issues
- Developers query logs by app version, device model, and network type instantly
- Teams catch feature failures hours before daily metric aggregation runs
- Zero schema definition required: just log name and payload
Critical Insight
Pinterest's self-service logging pipeline gives mobile developers production visibility and real-time alerting without touching backend infrastructure or defining schemas upfront.
