Monitor Spring reactive microservices with Prometheus and Grafana: a how-to guide

Elattar Saad

Fri, 27th October 2023

5 min read

#spring #spring reactive #webflux #prometheus #grafana #docker

Monitor Spring reactive microservices with Prometheus and Grafana: a how-to guide

Microservices monitoring is a crucial aspect of managing modern, complex software architectures. Unlike traditional monolithic applications, micro-services break down functionality into smaller, independent services that can be developed, deployed, and scaled independently. Monitoring these services involves tracking their performance, availability, and overall health in real-time. It includes collecting and analyzing various metrics such as response times, error rates, and resource usage. Effective microservices monitoring ensures early detection of issues, enabling quick resolution, minimizing downtime, and optimizing the user experience.

This article will serve as POC, integrating Prometheus and Garafana as monitoriong technologies with a reactive spring application with docker support.

What is Prometheus?

An open-source monitoring system with a dimensional data model, flexible query language, efficient time series database and modern alerting approach. — Source

In other words, Prometheus is used to gather the health information and store in a time series database which we can access later on using queries.

What is Garafana?

Grafana is a multi-platform open source analytics and interactive visualization web application. It provides charts, graphs, and alerts for the web when connected to supported data sources. — Source

In other words, again, Garafana is an analytics and vizualization tool, which will be used to visualize a set of interactive graphs, charts and alerts based on a data source (Prometheus for our case here).

Project Setup

In this project, we will be using Spring Webflux and Spring Docker support, my previous article details the use of theses approaches.

In this app we will be using:

Java version 17.
Spring Boot version 3.1.3. And the following dependencies:

For demo purposes, we’ll create a simple /GET movies endpoint.

In order to expose the health info via prometheus, we need to setup a simple config in our application.yaml file:

To make sure it works, we can check the following url (GET): http://localhost:8080/actuator/prometheus

The results of the request must look like this:

SpringPrometheusGrafana

This data will be our input for the Prometheus instance which we’ll going to create next.

Using Spring Docker support, we’re going to create the Prometheus and Grafana containers:

Prometheus Container:

First we must set the needed Prometheus config as /config/prometheus.yaml:

Then we must define our prometheus service in the /compose.yaml

Once we start our Spring Boot app, we must see the Prometheus container up and running at http://localhost:9090/

SpringPrometheusGrafana

We can use it to look for the health data we previously fetched filtered by a metric (i.g. jvm_buffer_memory_used_bytes):

SpringPrometheusGrafana

In the status > targets we can see that the Spring Boot App is Up as a target:

SpringPrometheusGrafana

Grafana Container:

Similar to Prometheus, Grafana is going to be configured the same way in /config/grafana.env:

And the service should be added to the compose.yaml file:

After running our app, we should be able to access Grafana dashboard using this url: http://localhost:3000/

SpringPrometheusGrafana

Then we can log in using admin/admin combination, after skipping the password update interface, we must see the dashboard:

SpringPrometheusGrafana

Then, we can set up our datasource:

SpringPrometheusGrafana

We need to select Prometheus:

SpringPrometheusGrafana

After defining the url to the Prometheus service we can test it.

SpringPrometheusGrafana

We can now build our dashboard based on the health info data from the Spring Boot app:

SpringPrometheusGrafana

Adding a new visualization:

SpringPrometheusGrafana

Adding Prometheus as datasource:

SpringPrometheusGrafana

Setting up the search query using the metric explorer:

SpringPrometheusGrafana

We use the jvm_memory_used_bytes to have the app used memory:

SpringPrometheusGrafana

We use the application label to filter only our app’s data:

SpringPrometheusGrafana

Also, we add another filter to only have the heap area:

SpringPrometheusGrafana

Then we name our dashboard:

SpringPrometheusGrafana

After setting the interval to 5 mins and resizing our graph it should look like this:

SpringPrometheusGrafana

We can create also another graph, the same way, for the non-heap memory in the same dashboard:

SpringPrometheusGrafana

Then adding names to our charts for better visibility:

SpringPrometheusGrafana

Finally

A major benefit of using Prometheus and Gafana for monitoring is that they may greatly aid in the early detection of malfunctions. These incredible tools have countless applications beyond what is demonstrated in this post; this proof of concept is only the beginning.

Please, find the full code here.

Monitor Spring reactive microservices with Prometheus and Grafana: a how-to guide

Elattar Saad

Fri, 27th October 2023

5 min read

Read on Medium

#spring #spring reactive #webflux #prometheus #grafana #docker

This article will serve as POC, integrating Prometheus and Garafana as monitoriong technologies with a reactive spring application with docker support.

What is Prometheus?

An open-source monitoring system with a dimensional data model, flexible query language, efficient time series database and modern alerting approach. — Source

In other words, Prometheus is used to gather the health information and store in a time series database which we can access later on using queries.

What is Garafana?

Project Setup

In this project, we will be using Spring Webflux and Spring Docker support, my previous article details the use of theses approaches.

In this app we will be using:

Java version 17.
Spring Boot version 3.1.3. And the following dependencies:

For demo purposes, we’ll create a simple /GET movies endpoint.

In order to expose the health info via prometheus, we need to setup a simple config in our application.yaml file:

To make sure it works, we can check the following url (GET): http://localhost:8080/actuator/prometheus

The results of the request must look like this:

SpringPrometheusGrafana

This data will be our input for the Prometheus instance which we’ll going to create next.

Using Spring Docker support, we’re going to create the Prometheus and Grafana containers:

Prometheus Container:

First we must set the needed Prometheus config as /config/prometheus.yaml:

Then we must define our prometheus service in the /compose.yaml

Once we start our Spring Boot app, we must see the Prometheus container up and running at http://localhost:9090/

SpringPrometheusGrafana

We can use it to look for the health data we previously fetched filtered by a metric (i.g. jvm_buffer_memory_used_bytes):

SpringPrometheusGrafana

In the status > targets we can see that the Spring Boot App is Up as a target:

SpringPrometheusGrafana

Grafana Container:

Similar to Prometheus, Grafana is going to be configured the same way in /config/grafana.env:

And the service should be added to the compose.yaml file:

After running our app, we should be able to access Grafana dashboard using this url: http://localhost:3000/

SpringPrometheusGrafana

Then we can log in using admin/admin combination, after skipping the password update interface, we must see the dashboard:

SpringPrometheusGrafana

Then, we can set up our datasource:

SpringPrometheusGrafana

We need to select Prometheus:

SpringPrometheusGrafana

After defining the url to the Prometheus service we can test it.

SpringPrometheusGrafana

We can now build our dashboard based on the health info data from the Spring Boot app:

SpringPrometheusGrafana

Adding a new visualization:

SpringPrometheusGrafana

Adding Prometheus as datasource:

SpringPrometheusGrafana

Setting up the search query using the metric explorer:

SpringPrometheusGrafana

We use the jvm_memory_used_bytes to have the app used memory:

SpringPrometheusGrafana

We use the application label to filter only our app’s data:

SpringPrometheusGrafana

Also, we add another filter to only have the heap area:

SpringPrometheusGrafana

Then we name our dashboard:

SpringPrometheusGrafana

After setting the interval to 5 mins and resizing our graph it should look like this:

SpringPrometheusGrafana

We can create also another graph, the same way, for the non-heap memory in the same dashboard:

SpringPrometheusGrafana

Then adding names to our charts for better visibility:

SpringPrometheusGrafana

Finally

Please, find the full code here.

<dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-webflux</artifactId>
 </dependency>

 <dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-docker-compose</artifactId>
   <scope>runtime</scope>
   <optional>true</optional>
 </dependency>

 <!-- Prometheus starter-->
 <dependency>
   <groupId>io.micrometer</groupId>
   <artifactId>micrometer-registry-prometheus</artifactId>
   <scope>runtime</scope>
 </dependency>

  <dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
  </dependency>

  <dependency>
   <groupId>org.springframework.boot</groupId>
   <artifactId>spring-boot-starter-test</artifactId>
   <scope>test</scope>
  </dependency>

  <dependency>
   <groupId>io.projectreactor</groupId>
   <artifactId>reactor-test</artifactId>
   <scope>test</scope>
  </dependency>

Movie.java

public record Movie(String title, Integer releaseYear, String director) { }

MovieController.java

import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import reactor.core.publisher.Flux;

@RestController
@RequestMapping("/movies")
public record MovieController() {

    @GetMapping
    public Flux<Movie> findAll() {
        return Flux.just(
                new Movie("Catch Me If You Can", 2002, "Steven Spielberg"),
                new Movie("Interstellar", 2014, "Christopher Nolan"),
                new Movie("Fight Club", 1999, "David Fincher"),
                new Movie("Creed", 2015, "Ryan Coogler"),
                new Movie("The Godfather", 1972, "Francis Ford Coppola"),
                new Movie("Avatar", 2009, "James Cameron"),
                new Movie("Inception", 2010, "Christopher Nolan"),
                new Movie("Forrest Gump", 1994, "Robert Zemeckis"),
                new Movie("Pulp Fiction", 1994, "Quentin Tarantino"),
                new Movie("Gladiator", 2000, "Ridley Scott"),
                new Movie("The Shawshank Redemption", 1994, "Frank Darabont"),
                new Movie("The Matrix", 1999, "The Wachowskis"),
                new Movie("The Dark Knight", 2008, "Christopher Nolan"),
                new Movie("Schindler's List", 1993, "Steven Spielberg"),
                new Movie("Inglourious Basterds", 2009, "Quentin Tarantino")
        );
    }

}

application.yaml

management:
  endpoints:
    web:
      exposure:
        include:
          - prometheus
  endpoint:
    health:
      show-details: always

/config/prometheus.yaml

global: # Global config which can be overridden.
  scrape_interval: 120s # By default, scrape targets every 15 seconds.

# Specific scrape config per endpoint.
scrape_configs:
  # This job is used to get data from prometheus itself (container running on port 9090).
  - job_name: 'prometheus'
    # Override the global default and scrape targets from this job every 5 seconds.
    scrape_interval: 5s
    static_configs:
      - targets: ['localhost:9090'] # Simply, pointing out the target to be scrapped

  # This job is used to get data from the movies api (Spring app running on port 8082).
  - job_name: 'movies-api'
    # Override the global default and scrape targets from this job every 5 seconds.
    scrape_interval: 5s
    metrics_path: /actuator/prometheus # this is the path on movies api used to provide prometheus with health info.
    static_configs:
      - targets: ['host.docker.internal:8080'] # Simply, pointing out the target to be scrapped
        labels:
          application: "Movies API"

compose.yaml

version: '3'
services:
  prometheus:
    image: prom/prometheus
    container_name: prometheus
    restart: unless-stopped
    volumes:
      - ./config/prometheus.yaml:/etc/prometheus/prometheus.yaml
    ports:
      - "9090:9090"

# Grafana service will be added next.

# [server]
GF_SERVER_DOMAIN=localhost
GF_SERVER_HTTP_PORT=3000
GF_SERVER_PROTOCOL=http

compose.yaml

version: '3'
services:
  prometheus:
    image: prom/prometheus
    container_name: prometheus
    restart: unless-stopped
    volumes:
      - ./config/prometheus.yaml:/etc/prometheus/prometheus.yaml
    ports:
      - "9090:9090"
# Nothing changed in the Prometheus service config.

  grafana:
    image: grafana/grafana
    container_name: grafana
    ports:
      - "3000:3000"
    env_file:
      - config/grafana.env

Monitor Spring reactive microservices with Prometheus and Grafana: a how-to guide

Elattar Saad

Fri, 27th October 2023

What is Prometheus?

What is Garafana?

Project Setup

Prometheus Container:

Grafana Container:

Finally

Read next

Monitor Spring reactive microservices with Prometheus and Grafana: a how-to guide

Elattar Saad

Fri, 27th October 2023

What is Prometheus?

What is Garafana?

Project Setup

Prometheus Container:

Grafana Container:

Finally

Read next