How to Set Up Alibaba Sentinel for Rate Limiting in a Spring Boot Microservice

Introduction

Sentinel is an open‑source rate‑limiting and circuit‑breaker framework from Alibaba that includes a visual dashboard for monitoring and rule management. It is widely used in microservice architectures to protect services from overload, burst traffic, and downstream failures.

Key Features

Rich application scenarios : Handles flash‑sale spikes, message peak‑shaving, and real‑time circuit breaking.

Real‑time monitoring : Shows per‑instance and aggregated metrics in the dashboard.

Broad ecosystem : Provides out‑of‑the‑box integrations with Spring Cloud, Dubbo, gRPC, etc.

Extensible SPI : Allows custom rule management and data‑source adapters.

Running the Sentinel Dashboard (Server)

Download the latest sentinel-dashboard JAR from the GitHub releases page ( https://github.com/alibaba/Sentinel/releases) and start it: java -jar sentinel-dashboard-1.6.0.jar The dashboard runs on port 8080 by default. Open http://localhost:8080 and log in with the default username/password sentinel.

Setting Up the Spring Boot Client

Create a Spring Boot project and add the following Maven dependencies:

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>2.0.5.RELEASE</version>
    </parent>
    <groupId>com.example</groupId>
    <artifactId>sentinel-demo</artifactId>
    <version>0.0.1-SNAPSHOT</version>
    <properties>
        <java.version>1.8</java.version>
        <spring-cloud.version>Finchley.SR1</spring-cloud.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.cloud</groupId>
            <artifactId>spring-cloud-starter-alibaba-sentinel</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    <dependencyManagement>
        <dependencies>
            <dependency>
                <groupId>org.springframework.cloud</groupId>
                <artifactId>spring-cloud-dependencies</artifactId>
                <version>${spring-cloud.version}</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
            <dependency>
                <groupId>org.springframework.cloud</groupId>
                <artifactId>spring-cloud-alibaba-dependencies</artifactId>
                <version>0.2.2.RELEASE</version>
                <type>pom</type>
                <scope>import</scope>
            </dependency>
        </dependencies>
    </dependencyManagement>
</project>

Note: Use version 0.2.x for Spring Boot 2.x projects; older Spring Boot 1.x requires 0.1.x.

Configuration

Add the Sentinel dashboard address to application.yml:

spring:
  application:
    name: sentinel-demo
  cloud:
    sentinel:
      transport:
        dashboard: localhost:8080
      #eager: true   # Uncomment to disable lazy loading

Controller Example

@RestController
public class TestController {
    @GetMapping("/hello")
    public String hello() {
        return "Hello Sentinel";
    }
}

Run the Spring Boot application. The dashboard will initially show no client because Sentinel loads rules lazily.

Defining a Flow Rule

After the first request to /hello, the client appears in the dashboard. Open the “Flow Control” tab for the /hello resource and set the QPS threshold to 1. This limits the endpoint to one request per second.

Verification

Send multiple rapid requests to /hello. The dashboard shows the QPS statistics and the requests exceeding the limit are blocked, confirming that rate limiting is active.

By following these steps you have a functional Sentinel setup that provides real‑time monitoring, rule management, and effective traffic throttling for your Spring Boot microservice.