Skip to content

Why LeanMQ?

The Problem with Internal Webhooks

If you're building a microservice architecture, you've likely encountered these challenges with traditional internal webhooks:

  • Message loss: When a service is down, webhooks can be lost forever
  • Retry complexity: Building robust retry mechanisms is difficult and error-prone
  • Scalability issues: As your system grows, managing webhook reliability becomes increasingly complex
  • Monitoring blindspots: Hard to track failed or delayed webhooks

The LeanMQ Solution

LeanMQ addresses these problems by providing:

  • Persistent message storage: Messages are stored in Redis until successfully processed
  • Dead letter queues: Failed messages are automatically moved to DLQs for inspection and reprocessing
  • Simple retry mechanisms: Built-in support for tracking delivery attempts
  • Familiar webhook-like API: Use decorators similar to web frameworks

Best of all, you can adopt LeanMQ with minimal changes to your existing code.

Key Features

  • Dead Letter Queues: Automatically capture and isolate failed messages
  • Message Time-to-Live (TTL): Set expiration times for messages
  • Atomic Transactions: Ensure all-or-nothing operations across multiple queues
  • Consumer Groups: Distribute message processing across multiple workers
  • Message Retry Tracking: Monitor delivery attempts for better reliability
  • Webhook-like Pattern: Familiar API for service-to-service communication

When to Use LeanMQ

LeanMQ is ideal for:

  • Internal service communication: Replace HTTP-based internal webhooks
  • Event-driven architectures: Reliable event propagation between services
  • Task processing: Distribute work across multiple services
  • Decoupling systems: Reduce direct dependencies between components

It's particularly valuable when:

  • You need higher reliability than HTTP webhooks provide
  • You want to decouple services for better scalability
  • You're already using Redis in your infrastructure
  • You want simplicity without the operational complexity of larger message brokers