Comprehensive Overview of Microservice Architecture Components

Preface

Microservice architecture has been widely adopted in many companies; this article presents a concise diagram of common components and emphasizes the need for a holistic understanding beyond merely moving code.

Traffic Entry – Nginx

Nginx serves as the external gateway, handling request routing, load balancing, and static/dynamic separation, typically deployed in multi‑node mode with keepalived for high availability.

Gateway

Placed after Nginx, the gateway (e.g., Spring Cloud Gateway, Zuul, Kong) manages authentication, routing, protocol conversion, and traffic monitoring; token‑based authentication such as JWT and OAuth2 are commonly used.

Business Services

After the gateway, business services (microservices) like account, order, invoice, and cashier services communicate via Feign, which integrates Ribbon for client‑side load balancing; proper domain‑driven design is essential for service boundaries.

Service Registry

Whether using Dubbo or Spring Cloud, a service registry (Zookeeper, Eureka, Nacos) is required for dynamic service discovery; Nacos is recommended for its dual role as a configuration center.

Cache and Distributed Lock

Redis is employed for caching hot data and implementing distributed locks; high availability can be achieved with Sentinel or Redis Cluster for scaling.

Data Persistence Layer

MySQL is commonly used with master‑slave replication and read/write separation; when data volume grows, horizontal and vertical sharding become necessary.

Structured Data Storage

For JSON or other non‑relational data, Elasticsearch or MongoDB are preferred, especially when advanced search capabilities are needed.

Message Middleware

Asynchronous decoupling between services is handled by MQ solutions such as RabbitMQ or RocketMQ to ensure reliable message delivery.

Log Collection

Log aggregation is achieved with the ELK stack (Filebeat → Logstash → Elasticsearch → Kibana) to centralize and visualize logs from distributed nodes.

Task Scheduling Center

Scheduled tasks use Spring Schedule or Quartz for single‑node scenarios; distributed scheduling can be implemented with Quartz (DB‑backed), Elastic‑Job, or XXL‑JOB.

Distributed Object Storage

File storage in distributed systems utilizes solutions like MinIO, Alibaba OSS, or FastDFS to handle large media files.

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