Java SpringBoot 日志
某些业务需求需要追踪接口访问情况,也就是把请求和响应记录下来。基本的记录维度包含了请求入参(路径query参数,请求体)、请求路径(uri)、请求方法(method)、请求头(headers)以及响应状态、响应头、甚至包含了敏感的响应体等等。总结了几种方法,可以按需选择。
请求追踪的实现方式
网关层
很多网关设施都具有httptrace的功能,可以帮助集中记录请求流量的情况。Orange、Kong、Apache Apisix这些基于Nginx的网关都具有该能力,就连Nginx本身也提供了记录httptrace日志的能力。
优点是可以集中的管理httptrace日志,免开发;缺点是技术要求高,需要配套的分发、存储、查询的设施。
Spring Boot Actuator
在Spring Boot中,其实提供了简单的追踪功能。只需要集成:
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
开启/actuator/httptrace:
management:
endpoints:
web:
exposure:
include: 'httptrace'
就可以通过http://server:port/actuator/httptrace获取最近的Http请求信息了。
不过在最新的版本中可能需要显式的声明这些追踪信息的存储方式,也就是实现HttpTraceRepository
接口并注入Spring IoC。
例如放在内存中并限制为最近的100条(不推荐生产使用):
@Bean
public HttpTraceRepository httpTraceRepository(){
return new InMemoryHttpTraceRepository();
}
追踪日志以json格式呈现:
Spring Boot Actuator记录的httptrace
记录的维度不多,当然如果够用的话可以试试。
优点在于集成起来简单,几乎免除开发;缺点在于记录的维度不多,而且需要搭建缓冲消费这些日志信息的设施。
CommonsRequestLoggingFilter
Spring Web模块还提供了一个过滤器CommonsRequestLoggingFilter
,它可以对请求的细节进行日志输出。配置起来也比较简单:
@Bean
CommonsRequestLoggingFilter loggingFilter(){
CommonsRequestLoggingFilter loggingFilter = new CommonsRequestLoggingFilter();
// 记录 客户端 IP信息
loggingFilter.setIncludeClientInfo(true);
// 记录请求头
loggingFilter.setIncludeHeaders(true);
// 如果记录请求头的话,可以指定哪些记录,哪些不记录
// loggingFilter.setHeaderPredicate();
// 记录 请求体 特别是POST请求的body参数
loggingFilter.setIncludePayload(true);
// 请求体的大小限制 默认50
loggingFilter.setMaxPayloadLength(10000);
//记录请求路径中的query参数
loggingFilter.setIncludeQueryString(true);
return loggingFilter;
}
而且必须开启对CommonsRequestLoggingFilter
的debug
日志:
logging:
level:
org:
springframework:
web:
filter:
CommonsRequestLoggingFilter: debug
一次请求会输出两次日志,一次是在第一次经过过滤器前;一次是完成过滤器链后。
CommonsRequestLoggingFilter记录请求日志
这里多说一句其实可以改造成输出json格式的。
优点是灵活配置、而且对请求追踪的维度全面,缺点是只记录请求而不记录响应。
ResponseBodyAdvice
Spring Boot统一返回体其实也能记录,需要自行实现。这里借鉴了CommonsRequestLoggingFilter
解析请求的方法。响应体也可以获取了,不过响应头和状态因为生命周期还不清楚,这里获取还不清楚是否合适,不过这是一个思路。
@Slf4j
@RestControllerAdvice(basePackages = {"cn.fcant.logging"})
public class RestBodyAdvice implements ResponseBodyAdvice<Object> {
private static final int DEFAULT_MAX_PAYLOAD_LENGTH = 10000;
public static final String REQUEST_MESSAGE_PREFIX = "Request [";
public static final String REQUEST_MESSAGE_SUFFIX = "]";
private ObjectMapper objectMapper = new ObjectMapper();
@Override
public boolean supports(MethodParameter returnType, Class<? extends HttpMessageConverter<?>> converterType) {
return true;
}
@SneakyThrows
@Override
public Object beforeBodyWrite(Object body,
MethodParameter returnType,
MediaType selectedContentType,
Class<? extends HttpMessageConverter<?>> selectedConverterType,
ServerHttpRequest request,
ServerHttpResponse response) {
ServletServerHttpRequest servletServerHttpRequest = (ServletServerHttpRequest) request;
log.debug(createRequestMessage(servletServerHttpRequest.getServletRequest(), REQUEST_MESSAGE_PREFIX, REQUEST_MESSAGE_SUFFIX));
Rest<Object> objectRest;
if (body == null) {
objectRest = RestBody.okData(Collections.emptyMap());
} else if (Rest.class.isAssignableFrom(body.getClass())) {
objectRest = (Rest<Object>) body;
}
else if (checkPrimitive(body)) {
return RestBody.okData(Collections.singletonMap("result", body));
}else {
objectRest = RestBody.okData(body);
}
log.debug("Response Body ["+ objectMapper.writeValueAsString(objectRest) +"]");
return objectRest;
}
private boolean checkPrimitive(Object body) {
Class<?> clazz = body.getClass();
return clazz.isPrimitive()
|| clazz.isArray()
|| Collection.class.isAssignableFrom(clazz)
|| body instanceof Number
|| body instanceof Boolean
|| body instanceof Character
|| body instanceof String;
}
protected String createRequestMessage(HttpServletRequest request, String prefix, String suffix) {
StringBuilder msg = new StringBuilder();
msg.append(prefix);
msg.append(request.getMethod()).append(" ");
msg.append(request.getRequestURI());
String queryString = request.getQueryString();
if (queryString != null) {
msg.append('?').append(queryString);
}
String client = request.getRemoteAddr();
if (StringUtils.hasLength(client)) {
msg.append(", client=").append(client);
}
HttpSession session = request.getSession(false);
if (session != null) {
msg.append(", session=").append(session.getId());
}
String user = request.getRemoteUser();
if (user != null) {
msg.append(", user=").append(user);
}
HttpHeaders headers = new ServletServerHttpRequest(request).getHeaders();
msg.append(", headers=").append(headers);
String payload = getMessagePayload(request);
if (payload != null) {
msg.append(", payload=").append(payload);
}
msg.append(suffix);
return msg.toString();
}
protected String getMessagePayload(HttpServletRequest request) {
ContentCachingRequestWrapper wrapper =
WebUtils.getNativeRequest(request, ContentCachingRequestWrapper.class);
if (wrapper != null) {
byte[] buf = wrapper.getContentAsByteArray();
if (buf.length > 0) {
int length = Math.min(buf.length, DEFAULT_MAX_PAYLOAD_LENGTH);
try {
return new String(buf, 0, length, wrapper.getCharacterEncoding());
} catch (UnsupportedEncodingException ex) {
return "[unknown]";
}
}
}
return null;
}
}
别忘记配置ResponseBodyAdvice
的logging级别为DEBUG
。
logstash-logback-encoder
这个是logstash的logback编码器,可以结构化输出httptrace为json。引入:
<dependency>
<groupId>net.logstash.logback</groupId>
<artifactId>logstash-logback-encoder</artifactId>
<version>6.6</version>
</dependency>
配置logback的ConsoleAppender
为LogstashEncoder
:
<configuration>
<appender name="jsonConsoleAppender" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="net.logstash.logback.encoder.LogstashEncoder"/>
</appender>
<root level=" INFO">
<appender-ref ref="jsonConsoleAppender"/>
</root>
</configuration>
然后同样实现一个解析的Filter
:
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.slf4j.MDC;
import org.springframework.core.annotation.Order;
import org.springframework.stereotype.Component;
import javax.servlet.*;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
import java.util.UUID;
@Order(1)
@Component
public class MDCFilter implements Filter {
private final Logger LOGGER = LoggerFactory.getLogger(MDCFilter.class);
private final String X_REQUEST_ID = "X-Request-ID";
@Override
public void doFilter(ServletRequest request,
ServletResponse response,
FilterChain chain) throws IOException, ServletException {
HttpServletRequest req = (HttpServletRequest) request;
HttpServletResponse res = (HttpServletResponse) response;
try {
addXRequestId(req);
LOGGER.info("path: {}, method: {}, query {}",
req.getRequestURI(), req.getMethod(), req.getQueryString());
res.setHeader(X_REQUEST_ID, MDC.get(X_REQUEST_ID));
chain.doFilter(request, response);
} finally {
LOGGER.info("statusCode {}, path: {}, method: {}, query {}",
res.getStatus(), req.getRequestURI(), req.getMethod(), req.getQueryString());
MDC.clear();
}
}
private void addXRequestId(HttpServletRequest request) {
String xRequestId = request.getHeader(X_REQUEST_ID);
if (xRequestId == null) {
MDC.put(X_REQUEST_ID, UUID.randomUUID().toString());
} else {
MDC.put(X_REQUEST_ID, xRequestId);
}
}
}
这里解析方式其实还可以更加精细一些。
然后所有的日志都可以结构化为json了:
{
"@timestamp":"2021-08-10T23:48:51.322+08:00",
"@version":"1",
"message":"statusCode 200, path: /log/get, method: GET, query foo=xxx&bar=ooo",
"logger_name":"cn.fcant.logging.MDCFilter",
"thread_name":"http-nio-8080-exec-1",
"level":"INFO",
"level_value":20000,
"X-Request-ID":"7c0db56c-b1f2-4d85-ad9a-7ead67660f96"
}