When a Kafka topic’s consumer lag suddenly spiked to over one million messages, the author traced the issue to improper acknowledgment handling, implemented emergency scaling, corrected exception processing, added a dead‑letter queue, and created a reusable checklist to prevent future backlogs.
This article explains RabbitMQ's transaction mechanism, walks through the four-step process of opening, executing, committing, or rolling back a transaction, provides a complete Java example with Maven setup, and discusses performance impacts and when to prefer acknowledgments over transactions.
This guide explains why guaranteeing 100% message reliability in MQ is a critical system‑design interview topic and presents a three‑layer architecture—production, storage, and consumption—detailing ACK settings, local message tables, broker replication, leader election safeguards, manual offset commits, and idempotent processing to prevent any message loss.
This article explains the three types of IM packets—Request, Acknowledge, and Notify—illustrates the basic message flow between client and server, identifies reliability gaps such as lost notifications, and proposes an application‑level solution using acknowledgments, timeout‑driven retransmission, and message deduplication to achieve dependable delivery.
This article explains how to configure durable queues and persistent messages in RabbitMQ, avoid message loss when producers or consumers crash, use manual acknowledgments and NACK handling, and control unacknowledged message flow with prefetch settings for high‑throughput backend systems.
This article explains why messages can be lost in RabbitMQ and Kafka, identifies three critical points—producer, broker storage, and consumer—and provides concrete configurations and acknowledgment mechanisms to ensure reliable, loss‑free message delivery.
This article explains Apache Pulsar’s core architecture—including its message model, producer and consumer behavior, subscription types, storage hierarchy, acknowledgment mechanisms, cursor handling, backlog concepts, retention policies, and storage size calculations—helping readers understand why storage size can exceed backlog size.
This article demystifies socket communication by illustrating the end‑to‑end process of TCP/UDP message exchange, detailing how client and server serialize objects, interact with kernel read/write buffers, handle blocking, acknowledgments, packet headers, and flow control, and why understanding these low‑level mechanisms is crucial for reliable network programming.
This article explains RabbitMQ's typical workflow, demonstrates basic message publishing and consumption with async/await in Node.js, introduces work queues with persistent messages and prefetch, and discusses key concepts such as default exchanges, queue durability, and acknowledgment modes.
