Getting Started with Spring Boot Application monitoring using Prometheus and Grafana

5 min readMay 21, 2021

Monitoring an application has become a very important part of software lifecycle as we want to be able to answer the “when or why” questions with data to proof it then avoid assumptions and surprises. i recently got to know about these tools and i was happy to use then share. Let jump right into this subject matter.

Application metrics and performance data is generated and exposed easily with the help of the micrometer and actuator, then prometheus fetches and stores these information at interval also allowing users to query the information stored but we need a dashboard for monitoring purpose and having an overview of the system, then we bring in grafana which is used to connect to the prometheus and build dashboard easily. These can be done for several instances of an application.

Spring Boot Application

The application is built using spring boot. To ensure that the application details are available, we have to ensure that the dependencies below are added to the project. (i am using Maven, you can try to import the gradle way if you are using gradle instead of maven).

<dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-actuator</artifactId></dependency>
<dependency>
   <groupId>io.micrometer</groupId>
   <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
<dependency>
   <groupId>javax.interceptor</groupId>
   <artifactId>javax.interceptor-api</artifactId>
   <version>1.2.2</version>
</dependency>

java.interceptor-api is optional

Also ensure that prometheus is enable and exposed on the configuration file(application.properties).

management.endpoints.web.exposure.include=prometheus,info,health
management.endpoint.prometheus.enabled=true

Ensure that you can view the details below when you visit the url : <scheme>://<host>:<port>/<context-path>/actuator/prometheus

Docker Compose to set up prometheus and grafana

version: “3”services:
 prometheus:
  image: prom/prometheus:latest
  container_name: ‘prometheus’
  volumes:
  — ./prometheus.yml:/etc/prometheus/prometheus.yml
  — ./rules.yml:/etc/prometheus/rules.yml
  ports:
  — ‘9090:9090’
 grafana:
  image: grafana/grafana:latest
  container_name: ‘grafana’
  ports:
  — ‘3000:3000’
  depends_on:
  — prometheus
 alertmanager:
  image: prom/alertmanager:latest
  ports:
  — 9093:9093
  volumes:
  — ./alertmanager.yml:/etc/alertmanager/alertmanager.yml

Prometheus

So Prometheus pulls metrics from the spring boot application. This process is called scrap but we need to create the configuration file called prometheus.yml. Below is a sample prometheus.yml file

scrape_configs:
  # Path can be different depending on your Spring Boot configuration
  - job_name: 'application_x'
    scrape_interval: 5s
    metrics_path: '/actuator/prometheus'
    scheme: http
    static_configs:
      - targets: ['<ip>:<port>']
  - job_name: 'application_y'
    scrape_interval: 5s
    metrics_path: '/actuator/prometheus'
    scheme: http
    static_configs:
      - targets: ['<ip>:<port>']

rule_files:
  - 'rules.yml' #file containing all the alert rules
alerting:
  alertmanagers:
    - static_configs:
      - targets:
          - alertmanager:9093  #location to the alert manager

job_name should be unique while scrape_interval is how often prometheus scrapes the targets for that job_name.

Note that if your spring-boot application is running on your local machine but not as a docker container, please use “docker.for.mac.localhost” for mac or “docker.for.win.localhost” for windows as your ip.

I guess you will be wondering whats these configurations for…

rule_files:
  - 'rules.yml' #file containing all the alert rules
alerting:
  alertmanagers:
    - static_configs:
      - targets:
          - alertmanager:9093  #location to the alert manager

They are alert configuration on prometheus but we need to set the rules which can be tailored to suit what you want. we have a sample rule which is set on the rules.yml file

— ./rules.yml:/etc/prometheus/rules.yml

you also noticed the line above on the prometheus.yml file. thats where the rules are set.

rules.yml

#This is where the rules are set
groups:
  - name: default
    rules:
      - alert: RequestRate #alert name
        expr: rate(http_server_requests_seconds_count{uri="/test"}[5m]) > 0 #Actual spring boot - prometheus report to monitor
        for: 1m #this is how long it monitors before triggering alerts
        labels:
          severity: high
        annotations:
          summary: Application receiving too many request #email content

Also we need to configure the alertmanager. the configuration is done on the alertmanager.yml.

route:
  receiver: emailer
receivers:
  - name: emailer
    email_configs:
      - to: <smtp_username>
        from: <smtp_username>
        smarthost: smtp.gmail.com:587
        auth_username: <smtp_username>
        auth_identity: <smtp_username>
        auth_password: <smtp_password>

Wow, we have setup prometheus and alertmanager.

Please run the docker-compose file by running the cmd “docker-compose -f <docker-compose file.yml> up -d”, once the containers are up. Please visit the url : http://localhost:9090

View the alert configured by clicking on “Alerts”

Grafana

Next is Grafana which is used to visualize the reports stored on prometheus. Please visit http://localhost:3000

Default username and password is admin

First we need to configure the datasource which is prometheus on grafana.

Finally, we need to create the dashboard. Good news, we don’t have to create a dashboard manually, you can import a dashboard from https://grafana.com/grafana/dashboards but i will recommend

To import a dashboard. Click on Import