SpringBoot教程（三十二） SpringBoot集成Skywalking链路跟踪 - ToB企服应用市场:ToB评测及商务社交产业平台

storage:
selector: ${SW_STORAGE:h2}
elasticsearch:
namespace: ${SW_NAMESPACE:""}
clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
connectTimeout: ${SW_STORAGE_ES_CONNECT_TIMEOUT:500}
socketTimeout: ${SW_STORAGE_ES_SOCKET_TIMEOUT:30000}
numHttpClientThread: ${SW_STORAGE_ES_NUM_HTTP_CLIENT_THREAD:0}
user: ${SW_ES_USER:""}
password: ${SW_ES_PASSWORD:""}
trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
# Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} # This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
indexTemplateOrder: ${SW_STORAGE_ES_INDEX_TEMPLATE_ORDER:0} # the order of index template
bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
# flush the bulk every 10 seconds whatever the number of requests
# INT(flushInterval * 2/3) would be used for index refresh period.
flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:15}
concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
oapAnalyzer: ${SW_STORAGE_ES_OAP_ANALYZER:"{"analyzer":{"oap_analyzer":{"type":"stop"}}}"} # the oap analyzer.
oapLogAnalyzer: ${SW_STORAGE_ES_OAP_LOG_ANALYZER:"{"analyzer":{"oap_log_analyzer":{"type":"standard"}}}"} # the oap log analyzer. It could be customized by the ES analyzer configuration to support more language log formats, such as Chinese log, Japanese log and etc.
advanced: ${SW_STORAGE_ES_ADVANCED:""}
h2:
driver: ${SW_STORAGE_H2_DRIVER:org.h2.jdbcx.JdbcDataSource}
url: ${SW_STORAGE_H2_URL:jdbc:h2:mem:skywalking-oap-db;DB_CLOSE_DELAY=-1}
user: ${SW_STORAGE_H2_USER:sa}
metadataQueryMaxSize: ${SW_STORAGE_H2_QUERY_MAX_SIZE:5000}
maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
maxSizeOfBatchSql: ${SW_STORAGE_MAX_SIZE_OF_BATCH_SQL:100}
asyncBatchPersistentPoolSize: ${SW_STORAGE_ASYNC_BATCH_PERSISTENT_POOL_SIZE:1}
mysql:
properties:
jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:3306/swtest?rewriteBatchedStatements=true"}
dataSource.user: ${SW_DATA_SOURCE_USER:root}
dataSource.password: ${SW_DATA_SOURCE_PASSWORD:root@1234}
dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
maxSizeOfBatchSql: ${SW_STORAGE_MAX_SIZE_OF_BATCH_SQL:2000}
asyncBatchPersistentPoolSize: ${SW_STORAGE_ASYNC_BATCH_PERSISTENT_POOL_SIZE:4}
tidb:
properties:
jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:4000/tidbswtest?rewriteBatchedStatements=true"}
dataSource.user: ${SW_DATA_SOURCE_USER:root}
dataSource.password: ${SW_DATA_SOURCE_PASSWORD:""}
dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
dataSource.useAffectedRows: ${SW_DATA_SOURCE_USE_AFFECTED_ROWS:true}
metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
maxSizeOfBatchSql: ${SW_STORAGE_MAX_SIZE_OF_BATCH_SQL:2000}
asyncBatchPersistentPoolSize: ${SW_STORAGE_ASYNC_BATCH_PERSISTENT_POOL_SIZE:4}
influxdb:
# InfluxDB configuration
url: ${SW_STORAGE_INFLUXDB_URL:http://localhost:8086}
user: ${SW_STORAGE_INFLUXDB_USER:root}
password: ${SW_STORAGE_INFLUXDB_PASSWORD:}
database: ${SW_STORAGE_INFLUXDB_DATABASE:skywalking}
actions: ${SW_STORAGE_INFLUXDB_ACTIONS:1000} # the number of actions to collect
duration: ${SW_STORAGE_INFLUXDB_DURATION:1000} # the time to wait at most (milliseconds)
batchEnabled: ${SW_STORAGE_INFLUXDB_BATCH_ENABLED:true}
fetchTaskLogMaxSize: ${SW_STORAGE_INFLUXDB_FETCH_TASK_LOG_MAX_SIZE:5000} # the max number of fetch task log in a request
connectionResponseFormat: ${SW_STORAGE_INFLUXDB_CONNECTION_RESPONSE_FORMAT:MSGPACK} # the response format of connection to influxDB, cannot be anything but MSGPACK or JSON.
postgresql:
properties:
jdbcUrl: ${SW_JDBC_URL:"jdbc:postgresql://localhost:5432/skywalking"}
dataSource.user: ${SW_DATA_SOURCE_USER:postgres}
dataSource.password: ${SW_DATA_SOURCE_PASSWORD:123456}
dataSource.cachePrepStmts: ${SW_DATA_SOURCE_CACHE_PREP_STMTS:true}
dataSource.prepStmtCacheSize: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_SIZE:250}
dataSource.prepStmtCacheSqlLimit: ${SW_DATA_SOURCE_PREP_STMT_CACHE_SQL_LIMIT:2048}
dataSource.useServerPrepStmts: ${SW_DATA_SOURCE_USE_SERVER_PREP_STMTS:true}
metadataQueryMaxSize: ${SW_STORAGE_MYSQL_QUERY_MAX_SIZE:5000}
maxSizeOfArrayColumn: ${SW_STORAGE_MAX_SIZE_OF_ARRAY_COLUMN:20}
numOfSearchableValuesPerTag: ${SW_STORAGE_NUM_OF_SEARCHABLE_VALUES_PER_TAG:2}
maxSizeOfBatchSql: ${SW_STORAGE_MAX_SIZE_OF_BATCH_SQL:2000}
asyncBatchPersistentPoolSize: ${SW_STORAGE_ASYNC_BATCH_PERSISTENT_POOL_SIZE:4}
zipkin-elasticsearch:
namespace: ${SW_NAMESPACE:""}
clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}
trustStorePath: ${SW_STORAGE_ES_SSL_JKS_PATH:""}
trustStorePass: ${SW_STORAGE_ES_SSL_JKS_PASS:""}
dayStep: ${SW_STORAGE_DAY_STEP:1} # Represent the number of days in the one minute/hour/day index.
indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:1} # Shard number of new indexes
indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes
# Super data set has been defined in the codes, such as trace segments.The following 3 config would be improve es performance when storage super size data in es.
superDatasetDayStep: ${SW_SUPERDATASET_STORAGE_DAY_STEP:-1} # Represent the number of days in the super size dataset record index, the default value is the same as dayStep when the value is less than 0
superDatasetIndexShardsFactor: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_SHARDS_FACTOR:5} # This factor provides more shards for the super data set, shards number = indexShardsNumber * superDatasetIndexShardsFactor. Also, this factor effects Zipkin and Jaeger traces.
superDatasetIndexReplicasNumber: ${SW_STORAGE_ES_SUPER_DATASET_INDEX_REPLICAS_NUMBER:0} # Represent the replicas number in the super size dataset record index, the default value is 0.
user: ${SW_ES_USER:""}
password: ${SW_ES_PASSWORD:""}
secretsManagementFile: ${SW_ES_SECRETS_MANAGEMENT_FILE:""} # Secrets management file in the properties format includes the username, password, which are managed by 3rd party tool.
bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requests
# flush the bulk every 10 seconds whatever the number of requests
# INT(flushInterval * 2/3) would be used for index refresh period.
flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:15}
concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
resultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}
metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:5000}
segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}
profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}
oapAnalyzer: ${SW_STORAGE_ES_OAP_ANALYZER:"{"analyzer":{"oap_analyzer":{"type":"stop"}}}"} # the oap analyzer.
oapLogAnalyzer: ${SW_STORAGE_ES_OAP_LOG_ANALYZER:"{"analyzer":{"oap_log_analyzer":{"type":"standard"}}}"} # the oap log analyzer. It could be customized by the ES analyzer configuration to support more language log formats, such as Chinese log, Japanese log and etc.
advanced: ${SW_STORAGE_ES_ADVANCED:""}
iotdb:
host: ${SW_STORAGE_IOTDB_HOST:127.0.0.1}
rpcPort: ${SW_STORAGE_IOTDB_RPC_PORT:6667}
username: ${SW_STORAGE_IOTDB_USERNAME:root}
password: ${SW_STORAGE_IOTDB_PASSWORD:root}
storageGroup: ${SW_STORAGE_IOTDB_STORAGE_GROUP:root.skywalking}
sessionPoolSize: ${SW_STORAGE_IOTDB_SESSIONPOOL_SIZE:16}
fetchTaskLogMaxSize: ${SW_STORAGE_IOTDB_FETCH_TASK_LOG_MAX_SIZE:1000} # the max number of fetch task log in a request

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-javaagent:D:ideaObjectreactBootspringboot-fullsrcmainskywalking-agentskywalking-agent.jar
-Dskywalking.agent.service_name=woqu-ndy
-Dskywalking.collector.backend_service=127.0.0.1:11800

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java -javaagent:D:ideaObjectreactBootspringboot-fullsrcmainskywalking-agentskywalking-agent.jar=-Dskywalking.agent.service_name=service-myapp,-Dskywalking.collector.backend_service=localhost:11800 -jar service-myapp.jar

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#!/bin/bash
# 设置 SkyWalking Agent 的路径
AGENT_PATH="/home/yourusername/Desktop/apache-skywalking-apm-6.6.0/apache-skywalking-apm-bin/agent"
# 设置 Java 应用的 JAR 文件路径
JAR_PATH="/path/to/your/service-myapp.jar"
# 设置 SkyWalking 服务名称和 Collector 后端服务地址
SERVICE_NAME="service-myapp"
COLLECTOR_BACKEND_SERVICE="localhost:11800"
# 构造 Java Agent 参数
JAVA_AGENT="-javaagent:$AGENT_PATH/skywalking-agent.jar
-Dskywalking.agent.service_name=$SERVICE_NAME
-Dskywalking.collector.backend_service=$COLLECTOR_BACKEND_SERVICE"
# 启动 Java 应用
java $JAVA_AGENT -jar $JAR_PATH

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<dependency>
<groupId>org.apache.skywalking</groupId>
<artifactId>apm-toolkit-logback-1.x</artifactId>
<version>9.0.0</version>
</dependency>

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<?xml version="1.0" encoding="UTF-8"?>
<configuration debug="false">
<property name="LOG_HOME" value="D:/logs/" ></property>
<conversionRule conversionWord="clr" converterClass="org.springframework.boot.logging.logback.ColorConverter" />
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender">
<encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
<layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.mdc.TraceIdMDCPatternLogbackLayout">
<pattern>%clr(%d{yyyy-MM-dd HH:mm:ss.SSS}){faint} [%X{tid}] %clr([%-10.10thread]){faint} %clr(%-5level) %clr(%-50.50logger{50}:%-3L){cyan} %clr(-){faint} %msg%n</pattern>
</layout>
</encoder>
</appender>
<appender name="FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
<rollingPolicy class="ch.qos.logback.core.rolling.TimeBasedRollingPolicy">
<FileNamePattern>${LOG_HOME}/%d{yyyy-MM-dd}/pro.log</FileNamePattern>
<MaxHistory>30</MaxHistory>
</rollingPolicy>
<encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
<layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.mdc.TraceIdMDCPatternLogbackLayout">
<pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%-10.10thread] %-5level %-50.50logger{50}:%-3L - %msg%n</pattern>
</layout>
</encoder>
<triggeringPolicy class="ch.qos.logback.core.rolling.SizeBasedTriggeringPolicy">
<MaxFileSize>10MB</MaxFileSize>
</triggeringPolicy>
</appender>
<appender name="grpc" class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.log.GRPCLogClientAppender">
<encoder class="ch.qos.logback.core.encoder.LayoutWrappingEncoder">
<layout class="org.apache.skywalking.apm.toolkit.log.logback.v1.x.mdc.TraceIdMDCPatternLogbackLayout">
<Pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} [%X{tid}] [%thread] %-5level %logger{36} -%msg%n</Pattern>
</layout>
</encoder>
</appender>
<root level="INFO">
<appender-ref ref="STDOUT" ></appender-ref>
<appender-ref ref="FILE" ></appender-ref>
<appender-ref ref="grpc"/>
</root>
</configuration>

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plugin.tomcat.collect_http_params=${SW_PLUGIN_TOMCAT_COLLECT_HTTP_PARAMS:true}
plugin.springmvc.collect_http_params=${SW_PLUGIN_SPRINGMVC_COLLECT_HTTP_PARAMS:true}
plugin.httpclient.collect_http_params=${SW_PLUGIN_HTTPCLIENT_COLLECT_HTTP_PARAMS:true}

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<dependency>
<groupId>org.apache.skywalking</groupId>
<artifactId>apm-toolkit-trace</artifactId>
<version>9.0.0</version>
</dependency>

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package com.example.springbootfull.quartztest.Filter;
import lombok.extern.slf4j.Slf4j;
import org.apache.skywalking.apm.toolkit.trace.ActiveSpan;
import org.springframework.stereotype.Component;
import org.springframework.util.StringUtils;
import org.springframework.web.util.ContentCachingRequestWrapper;
import org.springframework.web.util.ContentCachingResponseWrapper;
import javax.servlet.FilterChain;
import javax.servlet.ServletException;
import javax.servlet.http.HttpFilter;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.util.Enumeration;
import java.util.HashSet;
import java.util.Set;
import java.util.stream.Collectors;
@Slf4j
@Component
public class ApmHttpInfo extends HttpFilter {
//被忽略的头部信息
private static final Set<String> IGNORED_HEADERS;
static {
Set<String> ignoredHeaders = new HashSet<>();
ignoredHeaders.addAll(
java.util.Arrays.asList(
"Content-Type",
"User-Agent",
"Accept",
"Cache-Control",
"Postman-Token",
"Host",
"Accept-Encoding",
"Connection",
"Content-Length"
).stream()
.map(String::toUpperCase)
.collect(Collectors.toList())
);
IGNORED_HEADERS = ignoredHeaders;
}
@Override
public void doFilter(HttpServletRequest request, HttpServletResponse response, FilterChain filterChain) throws IOException, ServletException {
ContentCachingRequestWrapper requestWrapper = new ContentCachingRequestWrapper(request);
ContentCachingResponseWrapper responseWrapper = new ContentCachingResponseWrapper(response);
try {
filterChain.doFilter(requestWrapper, responseWrapper);
} finally {
try {
//构造请求信息: 比如 curl -X GET http://localhost:18080/getPerson?id=1 -H 'token: me-token' -d '{ "name": "hello" }'
//构造请求的方法&URL&参数
StringBuilder sb = new StringBuilder("curl")
.append(" -X ").append(request.getMethod())
.append(" ").append(request.getRequestURL().toString());
if (StringUtils.hasLength(request.getQueryString())) {
sb.append("?").append(request.getQueryString());
}
//构造header
Enumeration<String> headerNames = request.getHeaderNames();
while (headerNames.hasMoreElements()) {
String headerName = headerNames.nextElement();
if (!IGNORED_HEADERS.contains(headerName.toUpperCase())) {
sb.append(" -H '").append(headerName).append(": ").append(request.getHeader(headerName)).append("'");
}
}
//获取body
String body = new String(requestWrapper.getContentAsByteArray(), StandardCharsets.UTF_8);
if (StringUtils.hasLength(body)) {
sb.append(" -d '").append(body).append("'");
}
//输出到input
ActiveSpan.tag("input", sb.toString());
//获取返回值body
String responseBody = new String(responseWrapper.getContentAsByteArray(), StandardCharsets.UTF_8);
//输出到output
ActiveSpan.tag("output", responseBody);
} catch (Exception e) {
log.warn("fail to build http log", e);
} finally {
//这一行必须添加，否则就一直不返回
responseWrapper.copyBodyToResponse();
}
}
}
}

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