Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.
apm install @decebals/logging-patterns[](https://apm-p1ls2dz87-atlamors-projects.vercel.app/packages/@decebals/logging-patterns)---
name: logging-patterns
description: Java logging best practices with SLF4J, structured logging (JSON), and MDC for request tracing. Includes AI-friendly log formats for Claude Code debugging. Use when user asks about logging, debugging application flow, or analyzing logs.
---
# Logging Patterns Skill
Effective logging for Java applications with focus on structured, AI-parsable formats.
## When to Use
- User says "add logging" / "improve logs" / "debug this"
- Analyzing application flow from logs
- Setting up structured logging (JSON)
- Request tracing with correlation IDs
- AI/Claude Code needs to analyze application behavior
---
## AI-Friendly Logging
> **Key insight:** JSON logs are better for AI analysis - faster parsing, fewer tokens, direct field access.
### Why JSON for AI/Claude Code?
```
# Text format - AI must "interpret" the string
2026-01-29 10:15:30 INFO OrderService - Order 12345 created for user-789, total: 99.99
# JSON format - AI extracts fields directly
{"timestamp":"2026-01-29T10:15:30Z","level":"INFO","orderId":12345,"userId":"user-789","total":99.99}
```
| Aspect | Text | JSON |
|--------|------|------|
| Parsing | Regex/interpretation | Direct field access |
| Token usage | Higher (repeated patterns) | Lower (structured) |
| Error extraction | Parse stack trace text | `exception` field |
| Filtering | grep patterns | `jq` queries |
### Recommended Setup for AI-Assisted Development
```yaml
# application.yml - JSON by default
logging:
structured:
format:
console: logstash # Spring Boot 3.4+
# When YOU need to read logs manually:
# Option 1: Use jq
# tail -f app.log | jq .
# Option 2: Switch profile temporarily
# java -jar app.jar --spring.profiles.active=human-logs
```
### Log Format Optimized for AI Analysis
```json
{
"timestamp": "2026-01-29T10:15:30.123Z",
"level": "INFO",
"logger": "com.example.OrderService",
"message": "Order created",
"requestId": "req-abc123",
"traceId": "trace-xyz",
"orderId": 12345,
"userId": "user-789",
"duration_ms": 45,
"step": "payment_completed"
}
```
**Key fields for AI debugging:**
- `requestId` - group all logs from same request
- `step` - track progress through flow
- `duration_ms` - identify slow operations
- `level` - quick filter for errors
### Reading Logs with AI/Claude Code
When asking AI to analyze logs:
```bash
# Get recent errors
cat app.log | jq 'select(.level == "ERROR")' | tail -20
# Follow specific request
cat app.log | jq 'select(.requestId == "req-abc123")'
# Find slow operations
cat app.log | jq 'select(.duration_ms > 1000)'
```
AI can then:
1. Parse JSON directly (no guessing)
2. Follow request flow via requestId
3. Identify exactly where errors occurred
4. Measure timing between steps
---
## Quick Setup (Spring Boot 3.4+)
### Native Structured Logging
Spring Boot 3.4+ has built-in support - no extra dependencies!
```yaml
# application.yml
logging:
structured:
format:
console: logstash # or "ecs" for Elastic Common Schema
# Supported formats: logstash, ecs, gelf
```
### Profile-Based Switching
```yaml
# application.yml (default - JSON for AI/prod)
spring:
profiles:
default: json-logs
---
spring:
config:
activate:
on-profile: json-logs
logging:
structured:
format:
console: logstash
---
spring:
config:
activate:
on-profile: human-logs
# No structured format = human-readable default
logging:
pattern:
console: "%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n"
```
**Usage:**
```bash
# Default: JSON (for AI, CI/CD, production)
./mvnw spring-boot:run
# Human-readable when needed
./mvnw spring-boot:run -Dspring.profiles.active=human-logs
```
---
## Setup for Spring Boot < 3.4
### Logstash Logback Encoder
**pom.xml:**
```xml
<dependency>
<groupId>net.logstash.logback</groupId>
<artifactId>logstash-logback-encoder</artifactId>
<version>7.4</version>
</dependency>
```
**logback-spring.xml:**
```xml
<?xml version="1.0" encoding="UTF-8"?>
<configuration>
<!-- JSON (default) -->
<springProfile name="!human-logs">
<appender name="JSON" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="net.logstash.logback.encoder.LogstashEncoder">
<includeMdcKeyName>requestId</includeMdcKeyName>
<includeMdcKeyName>userId</includeMdcKeyName>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="JSON"/>
</root>
</springProfile>
<!-- Human-readable (optional) -->
<springProfile name="human-logs">
<appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender">
<encoder>
<pattern>%d{HH:mm:ss.SSS} %-5level [%thread] %logger{36} - %msg%n</pattern>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="CONSOLE"/>
</root>
</springProfile>
</configuration>
```
### Adding Custom Fields (Logstash Encoder)
```java
import static net.logstash.logback.argument.StructuredArguments.kv;
// Fields appear as separate JSON keys
log.info("Order created",
kv("orderId", order.getId()),
kv("userId", user.getId()),
kv("total", order.getTotal()),
kv("step", "order_created")
);
// Output:
// {"message":"Order created","orderId":123,"userId":"u-456","total":99.99,"step":"order_created"}
```
---
## SLF4J Basics
### Logger Declaration
```java
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
@Service
public class OrderService {
private static final Logger log = LoggerFactory.getLogger(OrderService.class);
}
// Or with Lombok
@Slf4j
@Service
public class OrderService {
// use `log` directly
}
```
### Parameterized Logging
```java
// ✅ GOOD: Evaluated only if level enabled
log.debug("Processing order {} for user {}", orderId, userId);
// ❌ BAD: Always concatenates
log.debug("Processing order " + orderId + " for user " + userId);
// ✅ For expensive operations
if (log.isDebugEnabled()) {
log.debug("Full order details: {}", order.toJson());
}
```
---
## Log Levels
| Level | When | Example |
|-------|------|---------|
| **ERROR** | Failures needing attention | Unhandled exception, service down |
| **WARN** | Unexpected but handled | Retry succeeded, deprecated API used |
| **INFO** | Business events | Order created, payment processed |
| **DEBUG** | Technical details | Method params, SQL queries |
| **TRACE** | Very detailed | Loop iterations (rarely used) |
```java
log.error("Payment failed", kv("orderId", id), kv("reason", reason), exception);
log.warn("Retry succeeded", kv("attempt", 3), kv("orderId", id));
log.info("Order shipped", kv("orderId", id), kv("trackingNumber", tracking));
log.debug("Fetching from DB", kv("query", "findById"), kv("id", id));
```
---
## MDC (Mapped Diagnostic Context)
MDC adds context to every log entry in a request - essential for tracing.
### Request ID Filter
```java
@Component
@Order(Ordered.HIGHEST_PRECEDENCE)
public class RequestContextFilter extends OncePerRequestFilter {
@Override
protected void doFilterInternal(HttpServletRequest request,
HttpServletResponse response,
FilterChain chain) throws ServletException, IOException {
try {
String requestId = Optional.ofNullable(request.getHeader("X-Request-ID"))
.filter(s -> !s.isBlank())
.orElse(UUID.randomUUID().toString().substring(0, 8));
MDC.put("requestId", requestId);
response.setHeader("X-Request-ID", requestId);
chain.doFilter(request, response);
} finally {
MDC.clear();
}
}
}
```
### Add User Context
```java
// After authentication
MDC.put("userId", authentication.getName());
// All subsequent logs include userId automatically
log.info("User action performed"); // {"userId":"john123","message":"User action performed"}
```
### MDC in Async Operations
```java
// MDC doesn't auto-propagate to new threads!
// ✅ Copy MDC context
Map<String, String> context = MDC.getCopyOfContextMap();
CompletableFuture.runAsync(() -> {
try {
if (context != null) MDC.setContextMap(context);
log.info("Async task running"); // Has requestId, userId
} finally {
MDC.clear();
}
});
```
---
## What to Log
### Business Events (INFO)
```java
// Include key identifiers and state
log.info("Order created",
kv("orderId", id),
kv("userId", userId),
kv("total", total),
kv("itemCount", items.size()),
kv("step", "order_created"));
log.info("Payment processed",
kv("orderId", id),
kv("amount", amount),
kv("method", "card"),
kv("step", "payment_completed"));
```
### External Calls (with timing)
```java
long start = System.currentTimeMillis();
try {
Result result = externalService.call(params);
log.info("External call succeeded",
kv("service", "PaymentGateway"),
kv("operation", "charge"),
kv("duration_ms", System.currentTimeMillis() - start));
return result;
} catch (Exception e) {
log.error("External call failed",
kv("service", "PaymentGateway"),
kv("operation", "charge"),
kv("duration_ms", System.currentTimeMillis() - start),
e);
throw e;
}
```
### Flow Steps (for AI tracing)
```java
public Order processOrder(CreateOrderRequest request) {
log.info("Processing started", kv("step", "start"), kv("requestData", request.summary()));
Order order = createOrder(request);
log.info("Order created", kv("step", "order_created"), kv("orderId", order.getId()));
validateInventory(order);
log.info("Inventory validated", kv("step", "inventory_ok"), kv("orderId", order.getId()));
processPayment(order);
log.info("Payment processed", kv("step", "payment_done"), kv("orderId", order.getId()));
log.info("Processing completed", kv("step", "complete"), kv("orderId", order.getId()));
return order;
}
```
---
## What NOT to Log
```java
// ❌ NEVER log sensitive data
log.info("Login", kv("password", password)); // Passwords
log.info("Payment", kv("cardNumber", card)); // Full card numbers
log.info("Request", kv("token", jwtToken)); // Tokens
log.info("User", kv("ssn", socialSecurity)); // PII
// ✅ Safe alternatives
log.info("Login attempted", kv("userId", userId));
log.info("Payment", kv("cardLast4", last4));
log.info("Token validated", kv("subject", sub), kv("exp", expiry));
```
---
## Exception Logging
### Log Once at Boundary
```java
// ❌ BAD: Logs same exception multiple times
void methodA() {
try { methodB(); }
catch (Exception e) { log.error("Error", e); throw e; } // Log #1
}
void methodB() {
try { methodC(); }
catch (Exception e) { log.error("Error", e); throw e; } // Log #2
}
// ✅ GOOD: Log at service boundary only
@RestControllerAdvice
public class GlobalExceptionHandler {
@ExceptionHandler(Exception.class)
public ResponseEntity<?> handle(Exception e, HttpServletRequest request) {
log.error("Request failed",
kv("path", request.getRequestURI()),
kv("method", request.getMethod()),
kv("errorType", e.getClass().getSimpleName()),
e); // Full stack trace
return ResponseEntity.status(500).body(errorResponse);
}
}
```
### Include Context
```java
// ❌ Useless
log.error("Error occurred", e);
// ✅ Useful for debugging
log.error("Order processing failed",
kv("orderId", orderId),
kv("step", "payment"),
kv("userId", userId),
kv("attemptNumber", attempt),
e);
```
---
## Quick Reference
```java
// === Setup ===
private static final Logger log = LoggerFactory.getLogger(MyClass.class);
// === Logging with structured fields ===
import static net.logstash.logback.argument.StructuredArguments.kv;
log.info("Event", kv("key1", value1), kv("key2", value2));
log.error("Failed", kv("context", ctx), exception);
// === MDC ===
MDC.put("requestId", requestId);
MDC.put("userId", userId);
// ... all logs now include these
MDC.clear(); // cleanup
// === Levels ===
log.error() // Failures
log.warn() // Handled issues
log.info() // Business events
log.debug() // Technical details
```
---
## Analyzing Logs (AI/Human)
```bash
# Pretty print JSON logs
tail -f app.log | jq .
# Filter errors
cat app.log | jq 'select(.level == "ERROR")'
# Follow request flow
cat app.log | jq 'select(.requestId == "abc123")'
# Find slow operations (>1s)
cat app.log | jq 'select(.duration_ms > 1000)'
# Get timeline of steps
cat app.log | jq 'select(.requestId == "abc123") | {time: .timestamp, step: .step, message: .message}'
```
---
## Related Skills
- `spring-boot-patterns` - Spring Boot configuration
- `jpa-patterns` - Database logging (SQL queries)
- Future: `observability-patterns` - Metrics, tracing, full observability