1. 日志基础概念

1.1 什么是日志

日志是应用程序运行时记录的事件、状态和信息的集合，用于跟踪应用程序的运行状况、调试问题和监控系统行为。

通俗理解：就像飞机的黑匣子，记录着系统运行的所有关键信息，当出现问题时可以回放查看。

1.2 为什么需要日志管理

1.3 Java常见日志框架对比

2. Spring Boot日志基础

2.1 默认日志配置

Spring Boot默认使用Logback作为日志框架，并通过spring-boot-starter-logging自动配置。

简单使用示例：

import org.slf4j.Logger; import org.slf4j.LoggerFactory; @RestController public class MyController { // 获取Logger实例（通常在每个类中声明） private static final Logger logger = LoggerFactory.getLogger(MyController.class); @GetMapping("/hello") public String hello() { logger.trace("This is a TRACE message"); logger.debug("This is a DEBUG message"); logger.info("This is an INFO message"); // 最常用 logger.warn("This is a WARN message"); logger.error("This is an ERROR message"); return "Hello World"; } }

2.2 日志级别详解

通俗理解：就像医院的分诊系统，TRACE是全面体检，DEBUG是专科检查，INFO是常规体检，WARN是轻微症状，ERROR是需要立即处理的病症。

3. 日志配置详解

3.1 配置文件格式

Spring Boot支持以下格式的日志配置文件：

logback-spring.xml (推荐)logback.xmlapplication.properties/application.yml中的简单配置

3.2 application.properties配置

# 设置全局日志级别 logging.level.root=WARN # 设置特定包日志级别 logging.level.com.myapp=DEBUG # 文件输出配置 logging.file.name=myapp.log # 或者使用logging.file.path指定目录 logging.file.path=/var/logs # 日志格式配置 logging.pattern.console=%d{yyyy-MM-dd HH:mm:ss} [%thread] %-5level %logger{36} - %msg%n logging.pattern.file=%d{yyyy-MM-dd HH:mm:ss} [%thread] %-5level %logger{36} - %msg%n # 日志文件大小限制和保留策略 logging.logback.rollingpolicy.max-file-size=10MB logging.logback.rollingpolicy.max-history=7

3.3 logback-spring.xml详细配置

<?xml version="1.0" encoding="UTF-8"?> <configuration scan="true" scanPeriod="30 seconds"> <!-- 定义变量 --> <property name="LOG_PATH" value="./logs" /> <property name="APP_NAME" value="my-application" /> <!-- 控制台输出appender --> <appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender"> <encoder> <pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 文件输出appender --> <appender name="FILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>${LOG_PATH}/${APP_NAME}.log</file> <rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> <fileNamePattern>${LOG_PATH}/${APP_NAME}-%d{yyyy-MM-dd}.%i.log</fileNamePattern> <maxFileSize>10MB</maxFileSize> <maxHistory>30</maxHistory> <totalSizeCap>1GB</totalSizeCap> </rollingPolicy> <encoder> <pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 异步日志appender --> <appender name="ASYNC_FILE" class="ch.qos.logback.classic.AsyncAppender"> <queueSize>512</queueSize> <discardingThreshold>0</discardingThreshold> <appender-ref ref="FILE" /> </appender> <!-- 日志级别配置 --> <root level="INFO"> <appender-ref ref="CONSOLE" /> <appender-ref ref="ASYNC_FILE" /> </root> <!-- 特定包日志级别 --> <logger name="com.myapp" level="DEBUG" /> <logger name="org.springframework" level="WARN" /> <!-- 环境特定配置 --> <springProfile name="dev"> <logger name="com.myapp" level="TRACE" /> <root level="DEBUG"> <appender-ref ref="CONSOLE" /> </root> </springProfile> <springProfile name="prod"> <root level="INFO"> <appender-ref ref="ASYNC_FILE" /> </root> </springProfile> </configuration>

3.4 配置项详细解析

3.4.1 Appender类型

3.4.2 RollingPolicy策略

3.4.3 日志格式模式

4. 高级日志功能

4.1 MDC (Mapped Diagnostic Context)

MDC用于在日志中添加上下文信息，如用户ID、请求ID等。

使用示例：

import org.slf4j.MDC; @RestController public class OrderController { private static final Logger logger = LoggerFactory.getLogger(OrderController.class); @GetMapping("/order/{id}") public Order getOrder(@PathVariable String id) { // 添加上下文信息 MDC.put("userId", "user123"); MDC.put("orderId", id); MDC.put("ip", "192.168.1.1"); try { logger.info("Fetching order details"); // 业务逻辑... return orderService.getOrder(id); } finally { // 清除MDC MDC.clear(); } } }

logback配置中添加MDC：

<pattern>%d{yyyy-MM-dd HH:mm:ss} [%thread] [%X{userId}] [%X{orderId}] %-5level %logger{36} - %msg%n</pattern>

4.2 日志过滤

可以根据条件过滤日志，只记录满足条件的日志。

示例：只记录包含"important"的ERROR日志

<appender name="IMPORTANT_ERRORS" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>important-errors.log</file> <filter class="ch.qos.logback.classic.filter.LevelFilter"> <level>ERROR</level> <onMatch>ACCEPT</onMatch> <onMismatch>DENY</onMismatch> </filter> <filter class="ch.qos.logback.core.filter.EvaluatorFilter"> <evaluator class="ch.qos.logback.classic.boolex.JaninoEventEvaluator"> <expression>message.contains("important")</expression> </evaluator> <onMatch>ACCEPT</onMatch> <onMismatch>DENY</onMismatch> </filter> <!-- 其他配置 --> </appender>

4.3 日志异步输出

对于性能敏感的应用，可以使用异步日志减少I/O阻塞。

配置示例：

<appender name="ASYNC" class="ch.qos.logback.classic.AsyncAppender"> <!-- 队列大小，默认256 --> <queueSize>512</queueSize> <!-- 当队列剩余容量小于此值时，丢弃TRACE/DEBUG/INFO级别日志 --> <discardingThreshold>0</discardingThreshold> <!-- 引用实际的appender --> <appender-ref ref="FILE" /> </appender>

4.4 多环境日志配置

利用Spring Profile为不同环境配置不同的日志策略。

<!-- 开发环境配置 --> <springProfile name="dev"> <root level="DEBUG"> <appender-ref ref="CONSOLE" /> </root> </springProfile> <!-- 生产环境配置 --> <springProfile name="prod"> <root level="INFO"> <appender-ref ref="ASYNC_FILE" /> </root> <logger name="org.hibernate.SQL" level="WARN" /> </springProfile>

5. 日志最佳实践

5.1 日志记录原则

有意义的消息：避免无意义的日志，如"进入方法"、"退出方法"不好：logger.info("Method called");好：logger.info("Processing order {} for user {}", orderId, userId);适当的日志级别：ERROR：需要立即处理的问题WARN：潜在问题INFO：重要业务事件DEBUG：调试信息TRACE：详细跟踪避免副作用：日志记录不应该改变程序行为不好：logger.debug("Value: " + expensiveOperation());好：logger.debug("Value: {}", () -> expensiveOperation());

5.2 性能优化

使用参数化日志：

// 不好 - 即使日志级别高于DEBUG也会执行字符串拼接

logger.debug("User " + userId + " accessed resource " + resourceId);

// 好 - 只有在DEBUG级别才会格式化字符串

logger.debug("User {} accessed resource {}", userId, resourceId); 异步日志：对于文件、网络等慢速Appender使用异步方式合理配置日志级别：生产环境适当提高日志级别

5.3 日志监控与分析

ELK Stack (Elasticsearch, Logstash, Kibana)SplunkPrometheus + Grafana (配合日志指标)

6. 常见问题与解决方案

6.1 日志文件过大

解决方案：

配置合理的滚动策略

logs/app-%d{yyyy-MM-dd}.%i.log

50MB

30

5GB

</rollingPolicy> 定期归档和清理旧日志

6.2 日志输出混乱

解决方案：

使用MDC区分不同请求配置合理的日志格式<pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] [%X{requestId}] %-5level %logger{36} - %msg%n</pattern>

6.3 日志性能问题

解决方案：

使用异步日志减少不必要的日志记录避免在日志中执行复杂操作

7. 实战案例：电商系统日志配置

7.1 完整logback-spring.xml配置

<?xml version="1.0" encoding="UTF-8"?> <configuration> <!-- 公共属性 --> <property name="LOG_HOME" value="/var/logs/ecommerce" /> <property name="APP_NAME" value="ecommerce-app" /> <property name="LOG_PATTERN" value="%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] [%X{userId}] [%X{requestId}] %-5level %logger{36} - %msg%n" /> <!-- 控制台输出 --> <appender name="CONSOLE" class="ch.qos.logback.core.ConsoleAppender"> <encoder> <pattern>${LOG_PATTERN}</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 主日志文件 --> <appender name="FILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>${LOG_HOME}/${APP_NAME}.log</file> <rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> <fileNamePattern>${LOG_HOME}/${APP_NAME}-%d{yyyy-MM-dd}.%i.log</fileNamePattern> <maxFileSize>50MB</maxFileSize> <maxHistory>30</maxHistory> <totalSizeCap>10GB</totalSizeCap> </rollingPolicy> <encoder> <pattern>${LOG_PATTERN}</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 错误日志单独文件 --> <appender name="ERROR_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>${LOG_HOME}/${APP_NAME}-error.log</file> <filter class="ch.qos.logback.classic.filter.ThresholdFilter"> <level>ERROR</level> </filter> <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy"> <fileNamePattern>${LOG_HOME}/${APP_NAME}-error-%d{yyyy-MM-dd}.log</fileNamePattern> <maxHistory>90</maxHistory> </rollingPolicy> <encoder> <pattern>${LOG_PATTERN}</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 异步appender --> <appender name="ASYNC_FILE" class="ch.qos.logback.classic.AsyncAppender"> <queueSize>1024</queueSize> <discardingThreshold>0</discardingThreshold> <includeCallerData>true</includeCallerData> <appender-ref ref="FILE" /> </appender> <!-- 异步错误appender --> <appender name="ASYNC_ERROR" class="ch.qos.logback.classic.AsyncAppender"> <queueSize>512</queueSize> <appender-ref ref="ERROR_FILE" /> </appender> <!-- 慢查询日志 --> <appender name="SLOW_QUERY" class="ch.qos.logback.core.rolling.RollingFileAppender"> <file>${LOG_HOME}/slow-query.log</file> <filter class="ch.qos.logback.core.filter.EvaluatorFilter"> <evaluator class="ch.qos.logback.classic.boolex.JaninoEventEvaluator"> <expression> (message.contains("SQL") || message.contains("Query")) && (contains("took") || contains("duration")) && (getMarker() != null && getMarker().contains("SLOW")) </expression> </evaluator> <onMatch>ACCEPT</onMatch> <onMismatch>DENY</onMismatch> </filter> <rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy"> <fileNamePattern>${LOG_HOME}/slow-query-%d{yyyy-MM-dd}.log</fileNamePattern> <maxHistory>60</maxHistory> </rollingPolicy> <encoder> <pattern>${LOG_PATTERN}</pattern> <charset>UTF-8</charset> </encoder> </appender> <!-- 根日志配置 --> <root level="INFO"> <appender-ref ref="CONSOLE" /> <appender-ref ref="ASYNC_FILE" /> <appender-ref ref="ASYNC_ERROR" /> </root> <!-- 特定包配置 --> <logger name="com.ecommerce.dao" level="DEBUG" /> <logger name="com.ecommerce.service" level="INFO" /> <logger name="org.hibernate.SQL" level="WARN" /> <logger name="org.springframework" level="WARN" /> <!-- 开发环境特殊配置 --> <springProfile name="dev"> <root level="DEBUG"> <appender-ref ref="CONSOLE" /> </root> <logger name="com.ecommerce" level="DEBUG" /> </springProfile> <!-- 生产环境特殊配置 --> <springProfile name="prod"> <root level="INFO"> <appender-ref ref="ASYNC_FILE" /> <appender-ref ref="ASYNC_ERROR" /> </root> <logger name="com.ecommerce.api" level="INFO" additivity="false"> <appender-ref ref="SLOW_QUERY" /> </logger> </springProfile> </configuration>

7.2 日志使用示例代码

@RestController @RequestMapping("/orders") public class OrderController { private static final Logger logger = LoggerFactory.getLogger(OrderController.class); private static final Marker SLOW_OPERATION_MARKER = MarkerFactory.getMarker("SLOW"); @Autowired private OrderService orderService; @GetMapping("/{id}") public ResponseEntity<Order> getOrder(@PathVariable String id, HttpServletRequest request) { // 设置MDC MDC.put("requestId", UUID.randomUUID().toString()); MDC.put("userId", request.getRemoteUser()); MDC.put("clientIp", request.getRemoteAddr()); try { logger.info("Fetching order with id: {}", id); long startTime = System.currentTimeMillis(); Order order = orderService.getOrderById(id); long duration = System.currentTimeMillis() - startTime; if (duration > 500) { logger.warn(SLOW_OPERATION_MARKER, "Slow order retrieval took {}ms for order {}", duration, id); } logger.debug("Order details: {}", order); return ResponseEntity.ok(order); } catch (OrderNotFoundException e) { logger.error("Order not found with id: {}", id, e); return ResponseEntity.notFound().build(); } catch (Exception e) { logger.error("Unexpected error fetching order {}", id, e); return ResponseEntity.internalServerError().build(); } finally { MDC.clear(); } } @PostMapping public ResponseEntity<Order> createOrder(@RequestBody OrderRequest request, @RequestHeader("X-User-Id") String userId) { MDC.put("userId", userId); try { logger.info("Creating new order for user {}", userId); logger.debug("Order request details: {}", request); Order createdOrder = orderService.createOrder(request, userId); logger.info("Order created successfully with id: {}", createdOrder.getId()); return ResponseEntity.ok(createdOrder); } catch (InvalidOrderException e) { logger.warn("Invalid order request from user {}: {}", userId, e.getMessage()); return ResponseEntity.badRequest().build(); } finally { MDC.clear(); } } }

8. 日志框架切换

8.1 切换到Log4j2

排除默认的Logback依赖添加Log4j2依赖<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> <exclusions> <exclusion> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-logging</artifactId> </exclusion> </exclusions> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-log4j2</artifactId> </dependency>

8.2 Log4j2配置示例

log4j2-spring.xml:

<?xml version="1.0" encoding="UTF-8"?> <Configuration status="WARN" monitorInterval="30"> <Properties> <Property name="LOG_PATTERN">%d{yyyy-MM-dd HH:mm:ss.SSS} [%t] [%X{requestId}] %-5level %logger{36} - %msg%n</Property> <Property name="LOG_DIR">logs</Property> </Properties> <Appenders> <Console name="Console" target="SYSTEM_OUT"> <PatternLayout pattern="${LOG_PATTERN}"/> </Console> <RollingFile name="File" fileName="${LOG_DIR}/app.log" filePattern="${LOG_DIR}/app-%d{yyyy-MM-dd}-%i.log"> <PatternLayout pattern="${LOG_PATTERN}"/> <Policies> <SizeBasedTriggeringPolicy size="50MB"/> <TimeBasedTriggeringPolicy/> </Policies> <DefaultRolloverStrategy max="30"/> </RollingFile> <Async name="AsyncFile" bufferSize="512"> <AppenderRef ref="File"/> </Async> </Appenders> <Loggers> <Root level="info"> <AppenderRef ref="Console"/> <AppenderRef ref="AsyncFile"/> </Root> <Logger name="com.myapp" level="debug" additivity="false"> <AppenderRef ref="Console"/> </Logger> </Loggers> </Configuration>

9. 日志监控与告警

9.1 常用监控指标

9.2 集成Prometheus监控

@Configuration public class LogMetricsConfig { private static final Counter errorCounter = Counter.build() .name("log_errors_total") .help("Total number of ERROR logs") .labelNames("logger", "exception") .register(); @Bean public MeterRegistryCustomizer<MeterRegistry> metricsCommonTags() { return registry -> registry.config().commonTags("application", "my-spring-app"); } @Bean public ApplicationListener<ApplicationReadyEvent> logMetricsListener() { return event -> { LoggerContext loggerContext = (LoggerContext) LoggerFactory.getILoggerFactory(); loggerContext.getLoggerList().forEach(logger -> { ((ch.qos.logback.classic.Logger) logger).addAppender(new AppenderBase<ILoggingEvent>() { @Override protected void append(ILoggingEvent event) { if (event.getLevel().isGreaterOrEqual(Level.ERROR)) { errorCounter.labels( event.getLoggerName(), event.getThrowableProxy() != null ? event.getThrowableProxy().getClassName() : "none" ).inc(); } } }); }); }; } }

本文结束得如此突然，就像你永远猜不到老板下一秒要改的需求。

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