一. 前言
其实早前就想计划出这篇文章，但是最近主要精力在完善微服务、系统权限设计、微信小程序和管理前端的功能，不过好在有群里小伙伴的一起帮忙反馈问题，基础版的功能已经差不多，也在此谢过，希望今后大家还是能够相互学习，一起进步~
ELK是Elasticsearch、Logstash、Kibana三个开源软件的组合，相信很多童鞋使用ELK有去做过分布式日志收集。流程概括为：微服务应用把Logback输出的日志通过HTTP传输至LogStash，然后经过分析过滤，转发至ES，再由Kibana提供检索和统计可视化界面。
在本实战案例中，使用Spring AOP、Logback横切认证接口来记录用户登录日志，收集到ELK，通过SpringBoot整合RestHighLevelClient实现对ElasticSearch数据检索和统计。从日志搜集到数据统计，一次性的走个完整，快速入门ElasticSearch。
本篇涉及的前后端全部源码已上传gitee和github，熟悉有来项目的童鞋快速过一下步骤即可。
| 项目名称 | Github | 码云 |
|---|---|---|
| 后台 | youlai-mall | youlai-mall |
| 前端 | youlai-mall-admin | youlai-mall-admin |
二. 需求
基于ELK的日志搜集的功能，本篇实现的需求如下：
- 记录系统用户登录日志，信息包括用户IP、登录耗时、认证令牌JWT
- 统计十天内用户登录次数、今日访问IP和总访问IP
- 充分利用记录的JWT信息，通过黑名单的方式让JWT失效实现强制下线
实现效果：
- Kibana日志可视化统计
- 登录次数统计、今日访问IP统计、总访问IP统计
- 登录信息，强制用户下线，演示的是自己强制自己下线的效果
三. Docker快速搭建ELK环境
1. 拉取镜像
docker pull elasticsearch:7.10.1
docker pull kibana:7.10.1
docker pull logstash:7.10.1
2. elasticsearch部署
1. 环境准备
# 创建文件
mkdir -p /opt/elasticsearch/{plugins,data} /etc/elasticsearch
touch /etc/elasticsearch/elasticsearch.yml
chmod -R 777 /opt/elasticsearch/data/
vim /etc/elasticsearch/elasticsearch.yml
# 写入
cluster.name: elasticsearch
http.cors.enabled: true
http.cors.allow-origin: "*"
http.host: 0.0.0.0
node.max_local_storage_nodes: 100
2. 启动容器
docker run -d --name=elasticsearch --restart=always
-e discovery.type=single-node
-e ES_JAVA_OPTS="-Xms256m -Xmx256m"
-p 9200:9200
-p 9300:9300
-v /etc/elasticsearch/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
-v /opt/elasticsearch/data:/usr/share/elasticsearch/data
-v /opt/elasticsearch/plugins:/usr/share/elasticsearch/plugins
elasticsearch:7.10.1
3. 验证和查看ElasticSearch版本
curl -XGET localhost:9200
2. kibana部署
1. 环境准备
# 创建文件
mkdir -p /etc/kibana
vim /etc/kibana/kibana.yml
# 写入
server.name: kibana
server.host: "0"
elasticsearch.hosts: [ "http://elasticsearch:9200" ]
i18n.locale: "zh-CN"
2. 启动容器
docker run -d --restart always -p 5601:5601 --name kibana --link elasticsearch
-e ELASTICSEARCH_URL=http://elasticsearch:9200
-v /etc/kibana/kibana.yml:/usr/share/kibana/config/kibana.yml
kibana:7.10.1
3. logstash部署
1. 环境准备
- 配置
logstash.yml
# 创建文件
mkdir -p /etc/logstash/config
vim /etc/logstash/config/logstash.yml
# 写入
http.host: "0.0.0.0"
xpack.monitoring.elasticsearch.hosts: [ "http://elasticsearch:9200" ]
xpack.management.pipeline.id: ["main"]
- 配置
pipeline.yml
# 创建文件
vim /etc/logstash/config/pipeline.yml
# 写入(注意空格)
- pipeline.id: main
path.config: "/usr/share/logstash/pipeline/logstash.config"
- 配置
logstash.conf
# 创建文件
mkdir -p /etc/logstash/pipeline
vim /etc/logstash/pipeline/logstash.conf
# 写入
input {
tcp {
port => 5044
mode => "server"
host => "0.0.0.0"
codec => json_lines
}
}
filter{
}
output {
elasticsearch {
hosts => ["elasticsearch:9200"]
# 索引名称，没有会自动创建
index => "%{[project]}-%{[action]}-%{+YYYY-MM-dd}"
}
}
2. 启动容器
docker run -d --restart always -p 5044:5044 -p 9600:9600 --name logstash --link elasticsearch
-v /etc/logstash/config/logstash.yml:/usr/share/logstash/config/logstash.yml
-v /etc/logstash/config/pipeline.yml:/usr/share/logstash/config/pipeline.yml
-v /etc/logstash/pipeline/logstash.conf:/usr/share/logstash/pipeline/logstash.conf
logstash:7.10.1
4. 测试
四. Spring AOP + Logback 横切打印登录日志
1. Spring AOP横切认证接口添加日志
代码坐标： common-web#LoginLogAspect
@Aspect
@Component
@AllArgsConstructor
@Slf4j
@ConditionalOnProperty(value = "spring.application.name", havingValue = "youlai-auth")
public class LoginLogAspect {
@Pointcut("execution(public * com.youlai.auth.controller.AuthController.postAccessToken(..))")
public void Log() {
}
@Around("Log()")
public Object doAround(ProceedingJoinPoint joinPoint) throws Throwable {
LocalDateTime startTime = LocalDateTime.now();
Object result = joinPoint.proceed();
// 获取请求信息
ServletRequestAttributes attributes = (ServletRequestAttributes) RequestContextHolder.getRequestAttributes();
HttpServletRequest request = attributes.getRequest();
// 刷新token不记录
String grantType=request.getParameter(AuthConstants.GRANT_TYPE_KEY);
if(grantType.equals(AuthConstants.REFRESH_TOKEN)){
return result;
}
// 时间统计
LocalDateTime endTime = LocalDateTime.now();
long elapsedTime = Duration.between(startTime, endTime).toMillis(); // 请求耗时（毫秒）
// 获取接口描述信息
MethodSignature signature = (MethodSignature) joinPoint.getSignature();
String description = signature.getMethod().getAnnotation(ApiOperation.class).value();// 方法描述
String username = request.getParameter(AuthConstants.USER_NAME_KEY); // 登录用户名
String date = startTime.format(DateTimeFormatter.ofPattern("yyyy-MM-dd")); // 索引名需要，因为默认生成索引的date时区不一致
// 获取token
String token = Strings.EMPTY;
if (request != null) {
JSONObject jsonObject = JSONUtil.parseObj(result);
token = jsonObject.getStr("value");
}
String clientIP = IPUtils.getIpAddr(request); // 客户端请求IP（注意：如果使用Nginx代理需配置）
String region = IPUtils.getCityInfo(clientIP); // IP对应的城市信息
// MDC 扩展logback字段，具体请看logback-spring.xml的自定义日志输出格式
MDC.put("elapsedTime", StrUtil.toString(elapsedTime));
MDC.put("description", description);
MDC.put("region", region);
MDC.put("username", username);
MDC.put("date", date);
MDC.put("token", token);
MDC.put("clientIP", clientIP);
log.info("{} 登录，耗费时间 {} 毫秒", username, elapsedTime); // 收集日志这里必须打印一条日志，内容随便吧，记录在message字段，具体看logback-spring.xml文件
return result;
}
}
2. Logback日志上传至LogStash
代码坐标：common-web#logback-spring.xml
<!-- Logstash收集登录日志输出到ElasticSearch -->
<appender name="LOGIN_LOGSTASH" class="net.logstash.logback.appender.LogstashTcpSocketAppender">
<destination>localhost:5044</destination>
<encoder charset="UTF-8" class="net.logstash.logback.encoder.LoggingEventCompositeJsonEncoder">
<providers>
<timestamp>
<timeZone>Asia/Shanghai</timeZone>
</timestamp>
<!--自定义日志输出格式-->
<pattern>
<pattern>
{
"project": "${APP_NAME}",
"date": "%X{date}", <!-- 索引名时区同步 -->
"action":"login",
"pid": "${PID:-}",
"thread": "%thread",
"message": "%message",
"elapsedTime": "%X{elapsedTime}",
"username":"%X{username}",
"clientIP": "%X{clientIP}",
"region":"%X{region}",
"token":"%X{token}",
"loginTime": "%date{"yyyy-MM-dd HH:mm:ss"}",
"description":"%X{description}"
}
</pattern>
</pattern>
</providers>
</encoder>
<keepAliveDuration>5 minutes</keepAliveDuration>
</appender>
<!-- additivity="true" 默认是true 会向上传递至root -->
<logger name="com.youlai.common.web.aspect.LoginLogAspect" level="INFO" additivity="true">
<appender-ref ref="LOGIN_LOGSTASH"/>
</logger>
- localhost:5044 Logstash配置的input收集数据的监听
- %X{username} 输出MDC添加的username的值
五. SpringBoot整合ElasticSearch客户端RestHighLevelClient
1. pom依赖
代码坐标： common-elasticsearch#pom.xml
客户端的版本需和服务器的版本对应，这里也就是7.10.1
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-high-level-client</artifactId>
<exclusions>
<exclusion>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-client</artifactId>
</exclusion>
<exclusion>
<artifactId>elasticsearch</artifactId>
<groupId>org.elasticsearch</groupId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.elasticsearch</groupId>
<artifactId>elasticsearch</artifactId>
<version>7.10.1</version>
</dependency>
<dependency>
<groupId>org.elasticsearch.client</groupId>
<artifactId>elasticsearch-rest-client</artifactId>
<version>7.10.1</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-elasticsearch</artifactId>
</dependency>
2. yml 配置
spring:
elasticsearch:
rest:
uris: ["http://localhost:9200"]
cluster-nodes:
- localhost:9200
3. RestHighLevelClientConfig 配置类
代码坐标： common-elasticsearch#RestHighLevelClientConfig
@ConfigurationProperties(prefix = "spring.elasticsearch.rest")
@Configuration
@AllArgsConstructor
public class RestHighLevelClientConfig {
@Setter
private List<String> clusterNodes;
@Bean
public RestHighLevelClient restHighLevelClient() {
HttpHost[] hosts = clusterNodes.stream()
.map(this::buildHttpHost) // eg: new HttpHost("127.0.0.1", 9200, "http")
.toArray(HttpHost[]::new);
return new RestHighLevelClient(RestClient.builder(hosts));
}
private HttpHost buildHttpHost(String node) {
String[] nodeInfo = node.split(":");
return new HttpHost(nodeInfo[0].trim(), Integer.parseInt(nodeInfo[1].trim()), "http");
}
}
4. RestHighLevelClient API封装
代码坐标： common-elasticsearch#ElasticSearchService
- 暂只简单封装实现需求里需要的几个方法，计数、去重计数、日期聚合统计、列表查询、分页查询、删除，后续可扩展...
@Service
@AllArgsConstructor
public class ElasticSearchService {
private RestHighLevelClient client;
/**
* 计数
*/
@SneakyThrows
public long count(QueryBuilder queryBuilder, String... indices) {
// 构造请求
CountRequest countRequest = new CountRequest(indices);
countRequest.query(queryBuilder);
// 执行请求
CountResponse countResponse = client.count(countRequest, RequestOptions.DEFAULT);
long count = countResponse.getCount();
return count;
}
/**
* 去重计数
*/
@SneakyThrows
public long countDistinct(QueryBuilder queryBuilder, String field, String... indices) {
String distinctKey = "distinctKey"; // 自定义计数去重key，保证上下文一致
// 构造计数聚合 cardinality:集合中元素的个数
CardinalityAggregationBuilder aggregationBuilder = AggregationBuilders
.cardinality(distinctKey).field(field);
// 构造搜索源
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(queryBuilder).aggregation(aggregationBuilder);
// 构造请求
SearchRequest searchRequest = new SearchRequest(indices);
searchRequest.source(searchSourceBuilder);
// 执行请求
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
ParsedCardinality result = searchResponse.getAggregations().get(distinctKey);
return result.getValue();
}
/**
* 日期聚合统计
*
* @param queryBuilder 查询条件
* @param field 聚合字段，如：登录日志的 date 字段
* @param interval 统计时间间隔，如：1天、1周
* @param indices 索引名称
* @return
*/
@SneakyThrows
public Map<String, Long> dateHistogram(QueryBuilder queryBuilder, String field, DateHistogramInterval interval, String... indices) {
String dateHistogramKey = "dateHistogramKey"; // 自定义日期聚合key，保证上下文一致
// 构造聚合
AggregationBuilder aggregationBuilder = AggregationBuilders
.dateHistogram(dateHistogramKey) //自定义统计名，和下文获取需一致
.field(field) // 日期字段名
.format("yyyy-MM-dd") // 时间格式
.calendarInterval(interval) // 日历间隔，例： 1s->1秒 1d->1天 1w->1周 1M->1月 1y->1年 ...
.minDocCount(0); // 最小文档数，比该值小就忽略
// 构造搜索源
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder
.query(queryBuilder)
.aggregation(aggregationBuilder)
.size(0);
// 构造SearchRequest
SearchRequest searchRequest = new SearchRequest(indices);
searchRequest.source(searchSourceBuilder);
searchRequest.indicesOptions(
IndicesOptions.fromOptions(
true, // 是否忽略不可用索引
true, // 是否允许索引不存在
true, // 通配符表达式将扩展为打开的索引
false // 通配符表达式将扩展为关闭的索引
));
// 执行请求
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
// 处理结果
ParsedDateHistogram dateHistogram = searchResponse.getAggregations().get(dateHistogramKey);
Iterator<? extends Histogram.Bucket> iterator = dateHistogram.getBuckets().iterator();
Map<String, Long> map = new HashMap<>();
while (iterator.hasNext()) {
Histogram.Bucket bucket = iterator.next();
map.put(bucket.getKeyAsString(), bucket.getDocCount());
}
return map;
}
/**
* 列表查询
*/
@SneakyThrows
public <T extends BaseDocument> List<T> search(QueryBuilder queryBuilder, Class<T> clazz, String... indices) {
List<T> list = this.search(queryBuilder, null, 1, ESConstants.DEFAULT_PAGE_SIZE, clazz, indices);
return list;
}
/**
* 分页列表查询
*/
@SneakyThrows
public <T extends BaseDocument> List<T> search(QueryBuilder queryBuilder, SortBuilder sortBuilder, Integer page, Integer size, Class<T> clazz, String... indices) {
// 构造SearchSourceBuilder
SearchSourceBuilder searchSourceBuilder = new SearchSourceBuilder();
searchSourceBuilder.query(queryBuilder);
searchSourceBuilder.sort(sortBuilder);
searchSourceBuilder.from((page - 1) * size);
searchSourceBuilder.size(size);
// 构造SearchRequest
SearchRequest searchRequest = new SearchRequest(indices);
searchRequest.source(searchSourceBuilder);
// 执行请求
SearchResponse searchResponse = client.search(searchRequest, RequestOptions.DEFAULT);
SearchHits hits = searchResponse.getHits();
SearchHit[] searchHits = hits.getHits();
List<T> list = CollectionUtil.newArrayList();
for (SearchHit hit : searchHits) {
T t = JSONUtil.toBean(hit.getSourceAsString(), clazz);
t.setId(hit.getId()); // 数据的唯一标识
t.setIndex(hit.getIndex());// 索引
list.add(t);
}
return list;
}
/**
* 删除
*/
@SneakyThrows
public boolean deleteById(String id, String index) {
DeleteRequest deleteRequest = new DeleteRequest(index,id);
DeleteResponse deleteResponse = client.delete(deleteRequest, RequestOptions.DEFAULT);
return true;
}
}
六. 后台接口
在SpringBoot整合了ElasticSearch的高级客户端RestHighLevelClient，以及简单了封装方法之后，接下来就准备为前端提供统计数据、分页列表查询记录、根据ID删除记录接口了。
1. 首页控制台
首页控制台需要今日IP访问数，历史总IP访问数、近十天每天的登录次数统计，具体代码如下：
代码坐标： youlai-admin#DashboardController
@Api(tags = "首页控制台")
@RestController
@RequestMapping("/api.admin/v1/dashboard")
@Slf4j
@AllArgsConstructor
public class DashboardController {
ElasticSearchService elasticSearchService;
@ApiOperation(value = "控制台数据")
@GetMapping
public Result data() {
Map<String, Object> data = new HashMap<>();
// 今日IP数
long todayIpCount = getTodayIpCount();
data.put("todayIpCount", todayIpCount);
// 总IP数
long totalIpCount = getTotalIpCount();
data.put("totalIpCount", totalIpCount);
// 登录统计
int days = 10; // 统计天数
Map loginCount = getLoginCount(days);
data.put("loginCount", loginCount);
return Result.success(data);
}
private long getTodayIpCount() {
String date = LocalDateTime.now().format(DateTimeFormatter.ofPattern("yyyy-MM-dd"));
TermQueryBuilder termQueryBuilder = QueryBuilders.termQuery("date", date);
String indexName = ESConstants.LOGIN_INDEX_PATTERN + date; //索引名称
// 这里使用clientIP聚合计数，为什么加.keyword后缀呢？下文给出截图
long todayIpCount = elasticSearchService.countDistinct(termQueryBuilder, "clientIP.keyword", indexName);
return todayIpCount;
}
private long getTotalIpCount() {
long totalIpCount = elasticSearchService.countDistinct(null, "clientIP.keyword", ESConstants.LOGIN_INDEX_PATTERN);
return totalIpCount;
}
private Map getLoginCount(int days) {
LocalDateTime now = LocalDateTime.now();
DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd");
String startDate = now.plusDays(-days).format(formatter);
String endDate = now.format(formatter);
String[] indices = new String[days]; // 查询ES索引数组
String[] xData = new String[days]; // 柱状图x轴数据
for (int i = 0; i < days; i++) {
String date = now.plusDays(-i).format(formatter);
xData[i] = date;
indices[i] = ESConstants.LOGIN_INDEX_PREFIX + date;
}
// 查询条件，范围内日期统计
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("date").from(startDate).to(endDate);
BoolQueryBuilder boolQueryBuilder = QueryBuilders.boolQuery()
.must(rangeQueryBuilder);
// 总数统计
Map<String, Long> totalCountMap = elasticSearchService.dateHistogram(
boolQueryBuilder,
"date", // 根据date字段聚合统计登录数 logback-spring.xml 中的自定义扩展字段 date
DateHistogramInterval.days(1),
indices);
// 当前用户统计
HttpServletRequest request = RequestUtils.getRequest();
String clientIP = IPUtils.getIpAddr(request);
boolQueryBuilder.must(QueryBuilders.termQuery("clientIP", clientIP));
Map<String, Long> myCountMap = elasticSearchService.dateHistogram(boolQueryBuilder, "date", DateHistogramInterval.days(1), indices);
// 组装echarts数据
Long[] totalCount = new Long[days];
Long[] myCount = new Long[days];
Arrays.sort(xData);// 默认升序
for (int i = 0; i < days; i++) {
String key = xData[i];
totalCount[i] = Convert.toLong(totalCountMap.get(key), 0l);
myCount[i] = Convert.toLong(myCountMap.get(key), 0l);
}
Map<String, Object> map = new HashMap<>(4);
map.put("xData", xData); // x轴坐标
map.put("totalCount", totalCount); // 总数
map.put("myCount", myCount); // 我的
return map;
}
}
- 聚合字段clientIP为什么添加.keyword后缀?
2. 登录记录分页查询接口
代码坐标： youlai-admin # LoginRecordController
@Api(tags = "登录记录")
@RestController
@RequestMapping("/api.admin/v1/login_records")
@Slf4j
@AllArgsConstructor
public class LoginRecordController {
ElasticSearchService elasticSearchService;
ITokenService tokenService;
@ApiOperation(value = "列表分页")
@ApiImplicitParams({
@ApiImplicitParam(name = "page", value = "页码", defaultValue = "1", paramType = "query", dataType = "Long"),
@ApiImplicitParam(name = "limit", value = "每页数量", defaultValue = "10", paramType = "query", dataType = "Long"),
@ApiImplicitParam(name = "startDate", value = "开始日期", paramType = "query", dataType = "String"),
@ApiImplicitParam(name = "endDate", value = "结束日期", paramType = "query", dataType = "String"),
@ApiImplicitParam(name = "clientIP", value = "客户端IP", paramType = "query", dataType = "String")
})
@GetMapping
public Result list(
Integer page,
Integer limit,
String startDate,
String endDate,
String clientIP
) {
// 日期范围
RangeQueryBuilder rangeQueryBuilder = QueryBuilders.rangeQuery("date");
if (StrUtil.isNotBlank(startDate)) {
rangeQueryBuilder.from(startDate);
}
if (StrUtil.isNotBlank(endDate)) {
rangeQueryBuilder.to(endDate);
}
BoolQueryBuilder queryBuilder = QueryBuilders.boolQuery().must(rangeQueryBuilder);
if (StrUtil.isNotBlank(clientIP)) {
queryBuilder.must(QueryBuilders.wildcardQuery("clientIP", "*" + clientIP + "*"));
}
// 总记录数
long count = elasticSearchService.count(queryBuilder, ESConstants.LOGIN_INDEX_PATTERN);
// 排序
FieldSortBuilder sortBuilder = new FieldSortBuilder("@timestamp").order(SortOrder.DESC);
// 分页查询
List<LoginRecord> list = elasticSearchService.search(queryBuilder, sortBuilder, page, limit, LoginRecord.class, ESConstants.LOGIN_INDEX_PATTERN);
// 遍历获取会话状态
list.forEach(item -> {
String token = item.getToken();
int tokenStatus = 0;
if (StrUtil.isNotBlank(token)) {
tokenStatus = tokenService.getTokenStatus(item.getToken());
}
item.setStatus(tokenStatus);
});
return Result.success(list, count);
}
@ApiOperation(value = "删除登录记录")
@ApiImplicitParam(name = "ids", value = "id集合", required = true, paramType = "query", dataType = "String")
@DeleteMapping
public Result delete(@RequestBody List<BaseDocument> documents) {
documents.forEach(document -> elasticSearchService.deleteById(document.getId(), document.getIndex()));
return Result.success();
}
}
3. 强制下线接口
代码坐标： youlai-admin#TokenController
- 这里还是将JWT添加至黑名单，然后在网关限制被加入黑名单的JWT登录
@Api(tags = "令牌接口")
@RestController
@RequestMapping("/api.admin/v1/tokens")
@Slf4j
@AllArgsConstructor
public class TokenController {
ITokenService tokenService;
@ApiOperation(value = "强制下线")
@ApiImplicitParam(name = "token", value = "访问令牌", required = true, paramType = "query", dataType = "String")
@PostMapping("/{token}/_invalidate")
@SneakyThrows
public Result invalidateToken(@PathVariable String token) {
boolean status = tokenService.invalidateToken(token);
return Result.judge(status);
}
}
代码坐标： youlai-admin#TokenServiceImpl
@Override
@SneakyThrows
public boolean invalidateToken(String token) {
JWTPayload payload = JWTUtils.getJWTPayload(token);
// 计算是否过期
long currentTimeSeconds = System.currentTimeMillis() / 1000;
Long exp = payload.getExp();
if (exp < currentTimeSeconds) { // token已过期，无需加入黑名单
return true;
}
// 添加至黑名单使其失效
redisTemplate.opsForValue().set(AuthConstants.TOKEN_BLACKLIST_PREFIX + payload.getJti(), null, (exp - currentTimeSeconds), TimeUnit.SECONDS);
return true;
}
七. 前端界面
项目前端源码：youlai-mall-admin，以下只贴出页面路径，有兴趣下载到本地查看源码和效果
代码坐标: src/views/dashboard/common/components/LoginCountChart.vue
- 登录次数统计、今日访问IP统计、总访问IP统计
代码坐标: src/views/admin/record/login/index.vue
- 登录信息，强制用户下线，演示的是自己强制自己下线的效果
八. 问题
1. 日志记录登录时间比正常时间晚了8个小时
项目使用Docker部署，其中依赖openjdk镜像时区是UTC，比北京时间晚了8个小时，执行以下命令修改时区解决问题
docker exec -it youlai-auth /bin/sh
echo "Asia/Shanghai" > /etc/timezone
docker restart youlai-auth
2. 用Nginx代理转发，怎么获取用户的真实IP？
在配置代理转发的时候添加:
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
九. Kibana索引检索
在LogStash的logout我们指定了索引的名称 "%{[project]}-%{[action]}-%{+YYYY-MM-dd}"
在logback-spring.xml指定了project为youlai-auth,action为login,替换生成类似youlai-auth-login-2021-3-25的索引，其中日期是可变的，然后我们在Kibana界面创建youlai-auth-login-*索引模式来对日志进行检索。
- 创建youlai-auth-login-*索引模式
- 根据索引模式，设置日期范围，进行登录日志的检索
十. 结语
至此，整个实战过程已经完成，搭建了ELK环境，使用Spring AOP横切来对登录日志的定点的搜集，最后通过SpringBoot整合ElasticSearch的高级Java客户端RestHighLevelClient来对搜集登录日志信息进行聚合计数、统计、以及日志中访问令牌操作来实现无状态的JWT会话管理，强制JWT失效让用户下线。文中只贴出关键的代码，其中还有像IP转地区的工具使用鉴于篇幅的原因并未一一说明，完整代码请参考git上的完整源代码。点击跳转
希望大家通过本篇文章能够快速入门ElasticSearch，如果有问题欢迎留言或者加我微信(haoxianrui)。
终. 附录
欢迎大家加入开源项目有来项目交流群，一起学习Spring Cloud微服务生态组件、分布式、Docker、K8S、Vue、element-ui、uni-app等全栈技术。
最后附上有来项目往期文章
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