It depends on what you're trying to achieve. These three options solve different problems rather than competing directly.
| Goal | Best choice | Why |
|---|
| Machine-readable application logs | Logback + JSON encoder | Structured logs that work well with Elasticsearch, Loki, Splunk, Datadog, etc. |
| High-performance logging framework | Log4j2 | Faster asynchronous logging and advanced configuration options. |
| Distributed tracing between services | Micrometer Tracing | Tracks requests across microservices using trace/span IDs; complements logging. |
1. Logback with JSON (recommended for most Spring Boot apps)
If you're using Spring Boot, this is usually the simplest and most common setup.
Typical stack:
- Logback (default logger)
- Logstash Logback Encoder
- JSON output
- Centralized log collector (ELK, Loki, Datadog)
Example JSON log:
{
"timestamp":"2026-07-16T10:15:34.123Z",
"level":"INFO",
"logger":"com.example.OrderService",
"traceId":"8d6f1a...",
"spanId":"6b12...",
"message":"Order created",
"userId":"12345"
}
Pros:
- Works out of the box with Spring Boot
- Excellent ecosystem support
- Easy to enrich with MDC values (userId, requestId, tenantId)
- Great for log aggregation
Best when:
- You mainly need searchable logs.
2. Log4j2
Choose Log4j2 if logging performance is a priority.
Advantages:
- Very fast asynchronous logging using the LMAX Disruptor
- Advanced routing and filtering
- JSON layouts built in
- Flexible configuration
Good for:
- High-throughput applications
- Large enterprise systems
- Applications writing thousands of log events per second
Unless you specifically need its performance or features, many Spring Boot teams stick with Logback.
3. Micrometer Tracing
Micrometer Tracing is not a logging framework.
Instead, it provides:
- Trace IDs
- Span IDs
- Distributed request tracking
- Integration with OpenTelemetry, Zipkin, and Jaeger
Example:
Gateway
│
▼
Order Service
│
▼
Payment Service
│
▼
Inventory Service
One HTTP request gets a single trace ID, making it possible to follow the request across all services.
Typical log output:
INFO traceId=8d6f1a spanId=2ab9 Processing payment
This makes troubleshooting distributed systems much easier.
Recommended architecture (Spring Boot microservices)
Rather than choosing one over the others, many teams combine them:
Application
│
▼
Micrometer Tracing
│
adds Trace ID / Span ID
│
▼
Logback (JSON)
│
▼
ELK / Loki / Datadog
This gives you:
- Structured JSON logs
- Automatic trace and span IDs in every log entry
- End-to-end request tracing
- Compatibility with observability platforms
Recommendation by application type
- Small Spring Boot app: Logback + JSON.
- Most production Spring Boot services: Logback + JSON + Micrometer Tracing.
- High-throughput systems with specialized logging needs: Log4j2 + Micrometer Tracing.
For most modern Spring Boot applications, Logback with JSON logging plus Micrometer Tracing provides the best balance of simplicity, observability, and integration.
