Known as the next-generation visual monitoring system, combined with SpringBoot, it is cool!

When faced with a complex system, we often need monitoring tools to help us solve some performance problems. For example, we used SpringBoot Admin to monitor the application before to obtain the index information exposed by SpringBoot Actuator Today, I will introduce you to Grafana, a powerful monitoring tool. As long as you need to use it for monitoring, use it for visualization!

SpringBoot actual combat e-commerce project mall (50k+star) address: https://github.com/macrozheng/mall

Introduction to Grafana

Grafana is an open source data visualization and analysis tool. No matter where your indicator information is stored, you can use it to visualize the data. At the same time, it also has an alarm function, which will alert you when the indicator exceeds the specified range.

Introduction to Prometheus

Prometheus is a time series database, which can be simply understood as a MySQL database with time. Since Grafana can only convert data into visual charts and has no storage function, we need to use it in conjunction with a time series database such as Prometheus.

installation

Using Docker to install Grafana and Prometheus is undoubtedly the easiest, we will use this method next.

• First download Grafana's Docker image;

docker pull grafana/grafana

• Run Grafana after the download is complete;

docker run -p 3000:3000 --name grafana \
-d grafana/grafana

• Next download the Docker image of Prometheus;

docker pull prom/prometheus

• Create Prometheus configuration file prometheus.yml in the /mydata/prometheus/ directory:

global:
  scrape_interval: 5s

• Run Prometheus and prometheus.yml in the host to the container;

docker run -p 9090:9090 --name prometheus \
-v /mydata/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml \
-d prom/prometheus

• At this point, the installation is complete, is it very simple! Grafana can be accessed through the following address, the login account password is admin:admin , and the access address: http://192.168.5.78:3000/

• After logging in to Grafana, the display interface is as follows;

• In fact, Prometheus also has a visual interface, which is a bit crude. The access address: http://192.168.5.78:9090/

use

After Grafana has been installed, it's time to come to practice in Poland. Next, let's introduce the use of Grafana to monitor Linux systems and SpringBoot applications.

Monitoring system information

Using node_explorer can expose the indicator information of the Linux system, and then Prometheus can obtain and store the indicator information through regular scanning.

• Download the installation package of node_explorer https://prometheus.io/download/#node_exporter

• This time we directly install node_explorer on the Linux server (if using Docker container installation, the monitoring will be the indicator information of the Docker container), unzip the downloaded installation package to the specified directory, and modify the folder name:

cd /mydata
tar -zxvf node_exporter-1.1.2.linux-amd64.tar.gz
mv node_exporter-1.1.2.linux-amd64 node_exporter

• Enter the decompression directory, use the following command to run node_explorer , the service will run on port 9100

cd node_exporter
./node_exporter >log.file 2>&1 &

• Use the curl command to access the interface for obtaining indicator information, and the information obtained indicates that the operation is successful;

curl http://localhost:9100/metrics

# HELP promhttp_metric_handler_requests_in_flight Current number of scrapes being served.
# TYPE promhttp_metric_handler_requests_in_flight gauge
promhttp_metric_handler_requests_in_flight 1
# HELP promhttp_metric_handler_requests_total Total number of scrapes by HTTP status code.
# TYPE promhttp_metric_handler_requests_total counter
promhttp_metric_handler_requests_total{code="200"} 2175
promhttp_metric_handler_requests_total{code="500"} 0
promhttp_metric_handler_requests_total{code="503"} 0

• Next, modify the Prometheus configuration file prometheus.yml , and create a task to scan the index information exposed by node_explorer

scrape_configs:
  - job_name: node
    static_configs:
    - targets: ['192.168.5.78:9100']

• Restart the Prometheus container, you can create a dashboard plus sign -> Dashboard;

• Of course, you can also choose to download a Dashboard from Grafana's dashboard market, the market address: https://grafana.com/grafana/dashboards

• Here I chose the Node Exporter Full , remember its ID, access address: https://grafana.com/grafana/dashboards/1860

• Select Import Dashboard and enter the ID, and finally click Load ;

• Select the data source as Prometheus, and finally click Import ;

• After the import is successful, you can see the real-time monitoring information in Grafana, is it cool enough?

Monitor SpringBoot applications

Monitoring SpringBoot applications needs to rely on actuator and micrometer . By exposing actuator , Prometheus can periodically obtain and store indicator information.

• Modify the pom.xml file of the actuator and micrometer dependencies;

<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-actuator</artifactId>
    </dependency>
    <!-- 集成micrometer，将监控数据存储到prometheus -->
    <dependency>
        <groupId>io.micrometer</groupId>
        <artifactId>micrometer-registry-prometheus</artifactId>
    </dependency>
</dependencies>

• Modify the application configuration file application.yml , by actuator exposure monitoring port /actuator/prometheus ;

management:
  endpoints:
    web:
      exposure:
        # 暴露端点`/actuator/prometheus`
        include: 'prometheus'
  metrics:
    tags:
      application: ${spring.application.name}

• Before monitoring the SpringBoot application, we need to run a SpringBoot application first, and run it with the following command;

docker run -p 8088:8088 --name mall-tiny-grafana \
-v /etc/localtime:/etc/localtime \
-v /mydata/app/mall-tiny-grafana/logs:/var/logs \
-e TZ="Asia/Shanghai" \
-d mall-tiny/mall-tiny-grafana:1.0-SNAPSHOT

• Modify the configuration file prometheus.yml Prometheus and create a task to periodically scan actuator . It should be noted here that since the SpringBoot application runs in a Docker container, you need to use docker inspect mall-tiny-grafana |grep IPAddress to obtain the container IP address;

scrape_configs:
  # 采集任务名称
  - job_name: 'mall-tiny-grafana'
    # 采集时间间隔
    scrape_interval: 5s
    # 采集超时时间
    scrape_timeout: 10s
    # 采集数据路径
    metrics_path: '/actuator/prometheus'
    # 采集服务的地址
    static_configs:
      - targets: ['172.17.0.5:8088']

• We can determine whether Prometheus can obtain indicator information through the visual interface of Prometheus;

• Similarly, we can import dashboards from the dashboard market, visit the address: https://grafana.com/grafana/dashboards/14370

• After the import is successful, you can see the SpringBoot real-time monitoring information in Grafana, which is really cool!

to sum up

Through a wave of practice of Grafana, we can find that the process of using Grafana to visualize data is as follows: first we have to let the monitored party expose the indicator information, then use Prometheus to obtain and store the indicator information at regular intervals, and finally add Prometheus Configured as a visual data source for Grafana.

Reference

• Grafana official document: https://grafana.com/docs/grafana/latest/getting-started/getting-started-prometheus/
• Use of node-exporter: https://prometheus.io/docs/guides/node-exporter/

Project source code address

https://github.com/macrozheng/mall-learning/tree/master/mall-tiny-grafana

This article GitHub https://github.com/macrozheng/mall-learning has been included, welcome to Star!