Over a decade of BAT architecture experience, shared generously!
The article explains how Nginx sustains one million simultaneous connections by using asynchronous non‑blocking I/O, a robust multi‑process architecture, zero‑copy file transmission, and optimized caching strategies, with concrete configuration examples and performance reasoning.
This article explains how Kafka’s sequential disk writes, zero‑copy data path, partition‑based parallelism, and configurable broker and partition settings enable linear‑scale throughput that can reach millions of transactions per second in large‑scale streaming systems.
This article explains what Kafka message backlog is, outlines the main reasons it occurs—such as producer speed outpacing consumers, slow consumer processing, and downstream bottlenecks—and provides practical steps for producer throttling, consumer scaling and logic improvements, and Kafka cluster enhancements to eliminate the backlog.
This article provides a comprehensive overview of Kubernetes, explaining why container orchestration is needed, describing the master‑node and worker‑node architecture, detailing each core component such as API Server, Scheduler, Controller Manager, etcd, kubelet and kube‑proxy, and illustrating the end‑to‑end workflow that enables automated deployment, scaling, and management of containerized applications.
This article explains how Docker achieves container isolation and resource management using Linux kernel features—Namespaces for process, network, and filesystem isolation, and Cgroups for CPU, memory, and I/O control—along with practical command examples and configuration details.
This article explains how Docker uses Linux kernel features—Namespaces for process isolation and Control Groups (cgroups) for resource limiting—to build a secure, lightweight container runtime, detailing their mechanisms, key structures, and practical configuration examples.
This article explains why message ordering is critical in scenarios such as financial transactions, e‑commerce order updates, audit logs, and IoT devices, then details Kafka’s core components—topics, partitions, offsets, producers, brokers, and consumer groups—and describes how single‑partition consumption and consistent key hashing ensure ordered processing while balancing throughput.
This article presents nine practical strategies—including load balancing, database sharding, read‑write separation, caching, index tuning, CDN usage, asynchronous processing, code refinement, and algorithm selection—to dramatically improve the performance and scalability of large‑scale backend architectures.
This article explains how Nginx achieves high‑concurrency handling through its event‑driven architecture, asynchronous non‑blocking I/O, modular design, and key configuration optimizations such as worker processes, connections, keepalive timeout, and sendfile, providing practical code examples and performance tips.
In high‑concurrency systems, Kafka message backlog occurs when producers outpace consumers, leading to unprocessed messages that threaten stability and real‑time performance, and this article explains the root causes and provides practical producer‑side and consumer‑side optimization techniques to resolve the issue.
