Logging in Spring Boot: A Comprehensive Guide to Centralized Logging( Using Docker )- PART 2

Introduction Logging is an essential part of any application. It helps developers debug, monitor, and analyze application behavior. In this blog, we'll explore logging in Spring Boot, covering configuration, best practices, and centralized logging using the ELK stack. 1. Understanding Logging in Spring Boot Spring Boot uses SLF4J as a facade for different logging frameworks like Logback (default), Log4j2, and Java Util Logging (JUL). Logging Levels TRACE – Most detailed information, for troubleshooting. DEBUG – Detailed information useful for debugging. INFO – General application information. WARN – Indication of potential issues. ERROR – Serious errors requiring immediate attention. 2. Folder Structure for a Spring Boot Logging Project Here is the recommended folder structure: springboot-logging/ │── src/ │ ├── main/ │ │ ├── java/com/example/logging/ │ │ │ ├── controller/ │ │ │ │ ├── LoggingController.java │ │ │ ├── service/ │ │ │ │ ├── LoggingService.java │ │ │ ├── LoggingApplication.java │ │ ├── resources/ │ │ │ ├── application.properties │ │ │ ├── logback.xml │── logs/ (Generated log files) │── docker-compose.yml (For ELK Stack) │── pom.xml (For Maven Dependencies) │── README.md 3. Configuring Logging in Spring Boot Using application.properties or application.yml # application.properties logging.level.root=INFO logging.level.org.springframework=DEBUG logging.file.name=logs/app.log logging.file.path=logs # application.yml logging: level: root: INFO org.springframework: DEBUG file: name: logs/app.log Using logback.xml for Custom Configuration %d{yyyy-MM-dd HH:mm:ss} %-5level %logger{36} - %msg%n 4. Implementing Logging in a Spring Boot Application Injecting Logger in a Spring Boot Service import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.stereotype.Service; @Service public class LoggingService { private static final Logger logger = LoggerFactory.getLogger(LoggingService.class); public void process() { logger.info("Processing request..."); try { // Simulated processing } catch (Exception e) { logger.error("Exception occurred: ", e); } } } Logging in a Controller import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RestController; @RestController @RequestMapping("/api") public class LoggingController { private static final Logger logger = LoggerFactory.getLogger(LoggingController.class); @GetMapping("/log") public String logExample() { logger.info("INFO: API hit at /log"); logger.warn("WARN: Example warning"); logger.error("ERROR: Example error"); return "Check the logs for details."; } } 5. Centralized Logging with ELK Stack Why Centralized Logging? Aggregate logs from multiple services. Real-time monitoring. Improved debugging and analysis. Setting Up ELK Stack with Docker Create a docker-compose.yml file: version: '3' services: elasticsearch: image: docker.elastic.co/elasticsearch/elasticsearch:8.0.0 container_name: elasticsearch environment: - discovery.type=single-node ports: - "9200:9200" networks: - elk logstash: image: docker.elastic.co/logstash/logstash:8.0.0 container_name: logstash volumes: - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf ports: - "5000:5000" depends_on: - elasticsearch networks: - elk kibana: image: docker.elastic.co/kibana/kibana:8.0.0 container_name: kibana ports: - "5601:5601" depends_on: - elasticsearch networks: - elk networks: elk: driver: bridge Logstash Configuration (logstash.conf) input { tcp { port => 5000 codec => json } } output { elasticsearch { hosts => ["http://elasticsearch:9200"] } } Sending Logs to Logstash from Spring Boot Modify logback.xml: logstash:5000 Viewing Logs in Kibana Start the ELK stack: docker-compose up -d Open Kibana at http://localhost:5601 Create an index pattern to visualize logs. 6. Best Practices for Logging Use Structured Logging (JSON format) for better parsing. Avoid Logging Sensitive Information (e.g., passwords, tokens). Use MDC (Mapped Diagnostic Context) for tracking requests across services. Example: JSON Logging 7. Conclusion Logging is crucial for debugging and monitoring ap

Feb 26, 2025 - 02:17

Logging in Spring Boot: A Comprehensive Guide to Centralized Logging( Using Docker )- PART 2

Introduction

Logging is an essential part of any application. It helps developers debug, monitor, and analyze application behavior. In this blog, we'll explore logging in Spring Boot, covering configuration, best practices, and centralized logging using the ELK stack.

1. Understanding Logging in Spring Boot

Spring Boot uses SLF4J as a facade for different logging frameworks like Logback (default), Log4j2, and Java Util Logging (JUL).

Logging Levels

TRACE – Most detailed information, for troubleshooting.
DEBUG – Detailed information useful for debugging.
INFO – General application information.
WARN – Indication of potential issues.
ERROR – Serious errors requiring immediate attention.

2. Folder Structure for a Spring Boot Logging Project

Here is the recommended folder structure:

springboot-logging/
│── src/
│   ├── main/
│   │   ├── java/com/example/logging/
│   │   │   ├── controller/
│   │   │   │   ├── LoggingController.java
│   │   │   ├── service/
│   │   │   │   ├── LoggingService.java
│   │   │   ├── LoggingApplication.java
│   │   ├── resources/
│   │   │   ├── application.properties
│   │   │   ├── logback.xml
│── logs/ (Generated log files)
│── docker-compose.yml (For ELK Stack)
│── pom.xml (For Maven Dependencies)
│── README.md

3. Configuring Logging in Spring Boot

Using `application.properties` or `application.yml`

# application.properties
logging.level.root=INFO
logging.level.org.springframework=DEBUG
logging.file.name=logs/app.log
logging.file.path=logs

# application.yml
logging:
  level:
    root: INFO
    org.springframework: DEBUG
  file:
    name: logs/app.log

Using `logback.xml` for Custom Configuration


     name="Console" class="ch.qos.logback.core.ConsoleAppender">
        
            %d{yyyy-MM-dd HH:mm:ss} %-5level %logger{36} - %msg%n
        
    
     level="INFO">
         ref="Console"/>

4. Implementing Logging in a Spring Boot Application

Injecting Logger in a Spring Boot Service

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.stereotype.Service;

@Service
public class LoggingService {
    private static final Logger logger = LoggerFactory.getLogger(LoggingService.class);

    public void process() {
        logger.info("Processing request...");
        try {
            // Simulated processing
        } catch (Exception e) {
            logger.error("Exception occurred: ", e);
        }
    }
}

Logging in a Controller

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
@RequestMapping("/api")
public class LoggingController {
    private static final Logger logger = LoggerFactory.getLogger(LoggingController.class);

    @GetMapping("/log")
    public String logExample() {
        logger.info("INFO: API hit at /log");
        logger.warn("WARN: Example warning");
        logger.error("ERROR: Example error");
        return "Check the logs for details.";
    }
}

5. Centralized Logging with ELK Stack

Why Centralized Logging?

Aggregate logs from multiple services.
Real-time monitoring.
Improved debugging and analysis.

Setting Up ELK Stack with Docker

Create a docker-compose.yml file:

version: '3'
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.0.0
    container_name: elasticsearch
    environment:
      - discovery.type=single-node
    ports:
      - "9200:9200"
    networks:
      - elk

  logstash:
    image: docker.elastic.co/logstash/logstash:8.0.0
    container_name: logstash
    volumes:
      - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf
    ports:
      - "5000:5000"
    depends_on:
      - elasticsearch
    networks:
      - elk

  kibana:
    image: docker.elastic.co/kibana/kibana:8.0.0
    container_name: kibana
    ports:
      - "5601:5601"
    depends_on:
      - elasticsearch
    networks:
      - elk

networks:
  elk:
    driver: bridge

Logstash Configuration (`logstash.conf`)

input {
  tcp {
    port => 5000
    codec => json
  }
}
output {
  elasticsearch {
    hosts => ["http://elasticsearch:9200"]
  }
}

Sending Logs to Logstash from Spring Boot

Modify logback.xml:

 name="LOGSTASH" class="net.logstash.logback.appender.LogstashTcpSocketAppender">
    logstash:5000
     class="net.logstash.logback.encoder.LogstashEncoder"/>


 level="INFO">
     ref="LOGSTASH"/>

Viewing Logs in Kibana

Start the ELK stack: docker-compose up -d
Open Kibana at http://localhost:5601
Create an index pattern to visualize logs.

6. Best Practices for Logging

Use Structured Logging (JSON format) for better parsing.
Avoid Logging Sensitive Information (e.g., passwords, tokens).
Use MDC (Mapped Diagnostic Context) for tracking requests across services.

Example: JSON Logging

 class="net.logstash.logback.encoder.LogstashEncoder"/>

7. Conclusion

Logging is crucial for debugging and monitoring applications. Using Spring Boot’s built-in support with centralized logging tools like ELK enhances visibility and troubleshooting.

Would you like a GitHub repository with a working example?