Over ten years of BAT architecture experience, shared generously!
This article explains how Nginx can separate static assets from dynamic requests using location rules and reverse‑proxying, provides a complete configuration example, and details the performance gains from zero‑copy file serving, gzip compression, caching headers, and CDN integration.
This article explains how Docker focuses on packaging and running containers while Kubernetes handles cluster-wide orchestration, detailing control granularity, scope, typical use cases, and the complementary roles they play in modern cloud‑native architectures.
This article provides a comprehensive technical overview of Kubernetes, covering its core problems, master‑worker architecture, essential components such as API server, etcd, scheduler, controller manager, kubelet, kube-proxy, container runtimes, and a step‑by‑step deployment workflow, illustrated with diagrams.
When a production server suddenly hits 100% CPU, this guide shows a systematic two‑minute workflow—using top, thread inspection, hexadecimal conversion, and jstack—to quickly identify the offending process or Java thread and restore service stability.
This article clarifies the distinct concepts of concurrency, parallelism, and asynchrony, detailing their definitions, implementation mechanisms, resource needs, timing semantics, and ideal use‑cases to help developers choose the right model for high‑performance systems.
This article explains Kafka's high‑availability architecture, covering multi‑replica replication, leader‑follower election and failover, the role of In‑Sync Replicas, and producer acknowledgment settings with min.insync.replicas for reliable, zero‑data‑loss streaming.
Learn how to package each microservice into containers and host them on a Kubernetes cluster, covering architecture diagrams, Ingress traffic routing, service discovery, ConfigMap and Secret management, persistent storage, deployment manifests, autoscaling, and CI/CD automation, while avoiding promotional fluff.
This article explains four core load‑balancing algorithms—Round Robin, Weighted Round Robin, Random, and Least Connections—detailing their principles, advantages, drawbacks, and typical scenarios where each method best fits modern backend systems.
Increasing a database connection pool size often worsens performance under massive traffic because the bottleneck lies in hardware limits and management overhead, so developers must adopt async processing, read‑write splitting, caching, sharding, and proper pool tuning to sustain high concurrency.
This guide outlines four primary microservice deployment strategies—Kubernetes orchestration, service‑mesh architecture, containerization, and serverless functions—detailing their principles, core advantages, and ideal use cases for large‑scale distributed systems, and highlights self‑healing, auto‑scaling, zero‑ops, and observability features that help handle massive traffic spikes.
