$ show rudderlabs/rudder-server
This is a production-grade Customer Data Platform (CDP) backend written in Go. It ingests events via HTTP (gateway), transforms and enriches them (processor), and routes them to over 90 destinations including streaming services (e.g., Kafka, Kinesis) and data warehouses (e.g., Snowflake, BigQuery, ClickHouse). The core of the system is a PostgreSQL-backed job queue (JobsDB) that provides partitioned, multi-consumer, durable processing. The architecture is a monolith with multiple internal services that can be deployed in different modes (gateway-only, processor-only, embedded). It includes enterprise features like OAuth token management, user suppression, regulatory deletion (GDPR), and reporting with HyperLogLog aggregation. The codebase is well-structured with clear separation of concerns, extensive unit and integration tests, and many reusable patterns (worker pool, circuit breaker, transaction listeners, config reloading). It is actively maintained with regular commits and security patching.
The LLM identified 5 files worth highlighting for reuse:
Provides a wrapper around `database/sql.Tx` that allows attaching success, failure, and finally callbacks to a database transaction. This decouples transaction lifecycle from business logic and enables clean instrumentation or cleanup. It is self-contained (only depends on standard library and internal `utils/misc` for logging) and can be extracted into any Go project needing transactional hooks.
Implements a per-account circuit breaker for OAuth token refresh operations. It tracks success and error counts within a sliding window and opens the circuit after a configurable threshold, preventing cascading failures. The design is generic (parameterized on account key) and could be reused in any system needing per-tenant circuit breaking.
A generic worker pool that manages a pool of goroutines with configurable idle cleanup. Workers can be added and removed dynamically, and the pool supports sending tasks to any idle worker via a channel. It is well-tested and independent of any project-specific types, making it a reusable building block for concurrent task processing.
Provides a per-user event ordering barrier that ensures jobs for the same user are committed in order. It uses a map of user keys to a single-goroutine executor, guaranteeing sequential processing per key while allowing concurrency across different users. This pattern is self-contained and can be extracted to any system requiring ordered processing of grouped items.
A generic batched uploader that collects items of a generic type `E`, batches them up to a configurable size or interval, and uploads via a `Transformer[E]` interface. It handles retries, backpressure, and stats. The design is cleanly separated from any specific upload protocol and can be reused for any batch-and-upload pattern.