What is message queuing middleware (RabbitMQ, Kafka) in email pipelines?

Message queuing middleware sits between email-generating applications and sending infrastructure, buffering and managing the flow of messages.

How it works in email pipelines:

Application generates email job (recipient, content, metadata)

Job goes into queue (RabbitMQ, Kafka, SQS, etc.)

Worker processes pull jobs from queue

Workers render content and submit to MTA

Queue ensures jobs aren't lost, enables retry, provides backpressure

Benefits:

Decoupling: Application doesn't wait for email to send; it just queues the job

Reliability: Jobs persist in queue; workers can crash without losing work

Scaling: Add more workers to increase throughput; queue buffers during spikes

Retry handling: Failed jobs can be requeued automatically

Rate limiting: Control how fast workers pull from queue

Common tools:

RabbitMQ: Popular, feature-rich, good for job queues

Apache Kafka: High-throughput, durable, good for large-scale pipelines

Amazon SQS: Managed queue service, simple to operate

Redis: Sometimes used for lighter-weight queuing

Use cases:

High-volume transactional email pipelines

Batch processing of marketing sends

Event-driven email triggers

Multi-tenant platforms managing many customers' email