This article explains why Kafka message backlog happens, then details practical solutions such as adding consumer instances, using batch consumption, applying asynchronous processing, and simplifying business logic to improve consumer efficiency.
This article explains how to use RocketMQ with Spring Boot to implement peak‑shaving, covering core components, consumer configuration, Maven setup, code examples, performance testing, and strategies for dynamic scaling and batch consumption.
This article explains how to integrate RocketMQ with Spring Boot to implement peak‑shaving, detailing core components, consumer pull parameters, one‑way sending, batch consumption configuration, and practical performance testing with code examples and deployment tips.
This article explains how RocketMQ’s decoupling, asynchronous and peak‑shaving features can be applied in a Spring Boot project to buffer massive like‑click traffic, reduce database pressure, and dynamically tune consumer pull parameters for optimal throughput.
