feat: GCS-based error store (dead letter queue) #29
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Add GCS-based error store for failed events: - ErrorRecord model with full event context - GCSErrorStore with Hive-style partitioning (date + error_type) - Parquet format for BigQuery compatibility - Retry logic with tenacity - Health check support Storage structure: - errors/date=YYYY-MM-DD/error_type=validation/ - errors/date=YYYY-MM-DD/error_type=processing/ Tests: - 10 unit tests (all passing) - ErrorRecord model validation - Path generation logic - Store operations with mocked GCS
Update ErrorStore protocol and Processor integration: - Updated ErrorStore protocol to match GCSErrorStore interface - Updated LoggingErrorStore for compatibility - Processor now catches all exceptions and stores to ErrorStore - Two error types: validation_error (expected) and processing_error (unexpected) - Updated dependencies to use GCSErrorStore instead of LoggingErrorStore - Updated processor tests to match new interface Error handling: - Validation failures → validation_error (adapter failures) - Processing exceptions → processing_error (with stack trace) - Never loses events - all go to EventStore or ErrorStore Tests: - 252 unit tests passing - Processor tests updated for new interface - No regressions
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Add BigQuery schema: - Create errors table with partitioning and clustering - Metadata table for tracking loaded files - Example queries for debugging Update README: - Error Store (Dead Letter Queue) section - Storage structure and usage examples - BigQuery setup and query examples - Updated roadmap (error store complete) Features documented: - Two error types (validation vs processing) - 30-day retention with GCS lifecycle - Full event context for debugging - BigQuery integration for analysis
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Summary
Implement production-grade error store for failed events using GCS + BigQuery.
Changes
Core Implementation
Integration
Storage Structure
BigQuery Support
Documentation
Tests