1 link tagged with all of: reliability + incident management + data mesh + observability
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Grab built an automated system called Data Production Issues (DPIs) that detects when certified data products fail their contracts, diagnoses root causes without manual intervention, and fixes common failures automatically. The system keeps data quality issues actionable by filtering noise, assigning problems to the right owner, and closing issues only when the underlying data actually recovers.
- DPIs use a standardized Data Health API with four error categories (upstream, platform, job, data) to route failures to the correct team without requiring platform-specific knowledge, enabling consistent incident management across Grab's heterogeneous data systems.
- The triage phase deduplicates alerts and groups related failures by root cause, preventing responders from drowning in repetitive notifications while ensuring only real contract breaches become operational issues.
- Hugo, Grab's ingestion platform, consolidates signals from multiple sources into a three-layer diagnosis workflow that automatically identifies root causes and recommends fixes, eliminating manual log inspection and shortening remediation time.