A high-performance RabbitMQ background processing framework for Ruby, designed for production workloads.
Sneakers is a background processing framework for Ruby that uses RabbitMQ as its message broker. It allows developers to offload time-consuming tasks—like data processing, logging, or external API calls—to asynchronous workers, improving application responsiveness and scalability. The framework is designed for high-performance production workloads with minimal maintenance requirements.
Ruby developers building applications that require reliable background job processing, particularly those already using or willing to adopt RabbitMQ for message queuing. It's suitable for teams running production systems with I/O or CPU intensive asynchronous tasks.
Developers choose Sneakers for its tight integration with RabbitMQ, production-ready performance, and straightforward worker model. Unlike generic job queues, it's specifically optimized for the RabbitMQ ecosystem, offering reliability and efficiency for demanding workloads without complex setup.
A fast background processing framework for Ruby and RabbitMQ
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Optimized for production workloads with efficient message handling, leveraging RabbitMQ's robust queuing for reliable job execution, as emphasized in the README's design goals.
Uses Ruby classes with built-in message acknowledgment and error handling, making worker definition straightforward, as shown in the quick start example with Processor class.
Includes metrics providers like logging_metrics for tracking job execution and performance, aiding in production monitoring without external tools.
Provides Docker and Docker Compose configurations for easy testing and deployment, designed for minimal maintenance overhead in production environments.
The original gem is no longer maintained, forcing users to migrate to the community fork 'kicks', which introduces uncertainty and potential breaking changes.
Tightly coupled to RabbitMQ, adding infrastructure dependency and setup complexity compared to simpler brokers like Redis used in alternatives.
Lacks built-in support for advanced job processing features such as automatic retries with backoff or priority queues, relying on RabbitMQ or manual implementation.