Observability Concept with Spring Boot, Prometheus, and JSON Logging

Observability refers to a system’s ability to provide insights into its internal state by exposing external outputs. It is typically built on three pillars: Logging, Monitoring, and Alerting.

1. 🔍 Logging

Logging captures structured or unstructured information about system events. In a production-ready setup, logs are written in JSON format to facilitate automated processing and analysis.

1.1. Technology: Spring Boot + JSON Logging

  • Use a logging framework such as Logback or Log4j2 with a JSON encoder.

  • Example configuration using Logback in logback-spring.xml:

<configuration>
  <appender name="JSON_CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
    <encoder class="net.logstash.logback.encoder.LogstashEncoder" />
  </appender>

  <root level="INFO">
    <appender-ref ref="JSON_CONSOLE" />
  </root>
</configuration>

  • Example log output:

{
  "timestamp": "2025-04-13T12:34:56.789Z",
  "level": "INFO",
  "logger": "com.example.MyService",
  "message": "User successfully created",
  "userId": "12345"
}

2. 📊 Monitoring

Monitoring collects metrics (e.g. latency, memory usage, throughput) to continuously observe system performance and health.

2.1. Technology: Spring Boot Actuator + Prometheus

  • spring-boot-actuator exposes metrics via the /actuator/metrics endpoint.

  • Integration with micrometer enables Prometheus as a metrics backend.

2.2. Example configuration (application.yml)

management:
  endpoints:
    web:
      exposure:
        include: prometheus
  metrics:
    export:
      prometheus:
        enabled: true

  • Prometheus is configured with a scrape job to periodically collect metrics:

scrape_configs:
  - job_name: 'spring-boot-app'
    static_configs:
      - targets: ['localhost:8080']

3. 🚨 Alerting

Alerting generates notifications based on defined thresholds in metrics, enabling rapid responses to potential issues.

3.1. Technology: Prometheus + Alertmanager

  • Prometheus evaluates metrics and triggers alerts according to alerting rules.

  • Example permission (Prometheus):

groups:
  - name: spring-alerts
    rules:
      - alert: HighErrorRate
        expr: rate(http_server_requests_seconds_count{status=~"5.."}[1m]) > 5
        for: 1m
        labels:
          severity: warning
        annotations:
          summary: "High error rate detected"
          description: "More than 5 errors per second in the last 60 seconds"

  • Alertmanager handles routing and escalation (e.g. email, Slack).

4. ✅ Summary

The observability setup is composed of the following components:

Component Technology

Logging

Spring Boot + Logback + JSON

Monitoring

Spring Boot Actuator + Micrometer + Prometheus

Alerting

Prometheus Alert Rules + Alertmanager

This setup provides deep visibility into the system’s behavior and ensures quick incident response.