Official account of Tencent Cloud Middleware. Focuses on microservices, messaging middleware and other cloud‑native technology trends, publishing product updates, case studies, and technical insights. Regularly hosts tech salons to share effective solutions.
By integrating large language models, Chatbox, MCP, and GraphQL, the TDMQ RocketMQ team enables operators to retrieve cluster, topic, and message data across heterogeneous sources using a single natural‑language query, dramatically simplifying diagnostics and reducing manual query effort.
This article explains why high‑throughput producers and consumers can saturate CPU, memory, network and disk I/O in TDMQ Pulsar clusters, describes the built‑in cluster‑level distributed and topic‑partition rate‑limiting mechanisms, and provides practical guidance for configuration, monitoring, and troubleshooting.
This article explains CKafka's cluster‑level and topic‑level throttling mechanisms, the soft‑limit token‑bucket algorithm, practical configuration tips, monitoring methods, and common troubleshooting scenarios to help users maintain stable and high‑performance message‑queue services.
This article explains why rate limiting is essential for high‑traffic microservices, outlines the key design considerations, compares major algorithms such as fixed‑window, sliding‑window, leaky‑bucket and token‑bucket, and details how Tencent Service Framework (TSF), Polaris, and TSF‑Consul implement distributed rate limiting with practical configuration examples and post‑limit handling strategies.
Maoyan, a leading ticketing platform, migrated its Dubbo‑based microservice registry from Nacos to Tencent Cloud Polaris, achieving a 30% improvement in registration discovery speed, higher scalability, and stronger fault tolerance across millions of services.
This article explains the motivation, design choices, architecture, and core technical details of implementing the AMQP protocol on top of RocketMQ, including model mapping, proxy layer, LMQ queues, message flow, binary protocol handling, feature comparison, performance tuning, and future plans.
This article thoroughly examines Apache Kafka’s architecture, covering its macro components, ack strategies, replication mechanisms, high‑watermark handling, leader election, and performance optimizations such as batch sending, compression, PageCache, zero‑copy, mmap and sendfile, while also explaining common pitfalls like data loss and log corruption.
This article details Tencent Cloud engineers' technical solutions for large‑scale Apache Pulsar deployments, covering multi‑network access challenges, a routing‑addressing redesign, product deployment models, a four‑step cluster migration process with subscription‑progress compensation, and high‑availability best practices such as rack‑aware and cross‑AZ replica distribution.
Since September 2024, TDMQ Pulsar professional clusters offer message‑level and metadata‑level cross‑region replication, providing solutions for worldwide data archiving and core‑business disaster recovery, with detailed deployment steps, configuration guidance, and a financial‑industry best‑practice case study.
This article explores Polaris‑Mesh’s server‑side health‑check mechanism, detailing how client heartbeat requests are received via gRPC, processed through Apiserver, Resource Auth Filter, Service, Healthcheck, and Checker Plugin, and how the system’s configuration, plugins, and time‑wheel ensure reliable instance health monitoring.
