下载最新的6.0windows版本
http://skywalking.apache.org/downloads/
解压后在config目录下修改相关文件配置
application.yml配置如下:
cluster:
standalone:
# Please check your ZooKeeper is 3.5+, However, it is also compatible with ZooKeeper 3.4.x. Replace the ZooKeeper 3.5+
# library the oap-libs folder with your ZooKeeper 3.4.x library.
# zookeeper:
# nameSpace: ${SW_NAMESPACE:""}
# hostPort: ${SW_CLUSTER_ZK_HOST_PORT:localhost:2181}
# #Retry Policy
# baseSleepTimeMs: ${SW_CLUSTER_ZK_SLEEP_TIME:1000} # initial amount of time to wait between retries
# maxRetries: ${SW_CLUSTER_ZK_MAX_RETRIES:3} # max number of times to retry
# kubernetes:
# watchTimeoutSeconds: ${SW_CLUSTER_K8S_WATCH_TIMEOUT:60}
# namespace: ${SW_CLUSTER_K8S_NAMESPACE:default}
# labelSelector: ${SW_CLUSTER_K8S_LABEL:app=collector,release=skywalking}
# uidEnvName: ${SW_CLUSTER_K8S_UID:SKYWALKING_COLLECTOR_UID}
# consul:
# serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}
# Consul cluster nodes, example: 10.0.0.1:8500,10.0.0.2:8500,10.0.0.3:8500
# hostPort: ${SW_CLUSTER_CONSUL_HOST_PORT:localhost:8500}
core:
default:
restHost: 127.0.0.1
restPort: 12800
restContextPath: /
gRPCHost: 127.0.0.1
gRPCPort: 11800
downsampling:
- Hour
- Day
- Month
# Set a timeout on metric data. After the timeout has expired, the metric data will automatically be deleted.
recordDataTTL: ${SW_CORE_RECORD_DATA_TTL:90} # Unit is minute
minuteMetricsDataTTL: ${SW_CORE_MINUTE_METRIC_DATA_TTL:90} # Unit is minute
hourMetricsDataTTL: ${SW_CORE_HOUR_METRIC_DATA_TTL:36} # Unit is hour
dayMetricsDataTTL: ${SW_CORE_DAY_METRIC_DATA_TTL:45} # Unit is day
monthMetricsDataTTL: ${SW_CORE_MONTH_METRIC_DATA_TTL:18} # Unit is month
storage:
# h2:
# driver: ${SW_STORAGE_H2_DRIVER:org.h2.jdbcx.JdbcDataSource}
# url: ${SW_STORAGE_H2_URL:jdbc:h2:mem:skywalking-oap-db}
# user: ${SW_STORAGE_H2_USER:sa}
# elasticsearch:
# # nameSpace: ${SW_NAMESPACE:""}
# clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}
# indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:2}
# indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:0}
# # Batch process setting, refer to https://www.elastic.co/guide/en/elasticsearch/client/java-api/5.5/java-docs-bulk-processor.html
# bulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:2000} # Execute the bulk every 2000 requests
# bulkSize: ${SW_STORAGE_ES_BULK_SIZE:20} # flush the bulk every 20mb
# flushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:10} # flush the bulk every 10 seconds whatever the number of requests
# concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requests
mysql:
receiver-register:
default:
receiver-trace:
default:
bufferPath: ${SW_RECEIVER_BUFFER_PATH:../trace-buffer/} # Path to trace buffer files, suggest to use absolute path
bufferOffsetMaxFileSize: ${SW_RECEIVER_BUFFER_OFFSET_MAX_FILE_SIZE:100} # Unit is MB
bufferDataMaxFileSize: ${SW_RECEIVER_BUFFER_DATA_MAX_FILE_SIZE:500} # Unit is MB
bufferFileCleanWhenRestart: ${SW_RECEIVER_BUFFER_FILE_CLEAN_WHEN_RESTART:false}
sampleRate: ${SW_TRACE_SAMPLE_RATE:10000} # The sample rate precision is 1/10000. 10000 means 100% sample in default.
receiver-jvm:
default:
#service-mesh:
# default:
# bufferPath: ${SW_SERVICE_MESH_BUFFER_PATH:../mesh-buffer/} # Path to trace buffer files, suggest to use absolute path
# bufferOffsetMaxFileSize: ${SW_SERVICE_MESH_OFFSET_MAX_FILE_SIZE:100} # Unit is MB
# bufferDataMaxFileSize: ${SW_SERVICE_MESH_BUFFER_DATA_MAX_FILE_SIZE:500} # Unit is MB
# bufferFileCleanWhenRestart: ${SW_SERVICE_MESH_BUFFER_FILE_CLEAN_WHEN_RESTART:false}
#istio-telemetry:
# default:
#receiver_zipkin:
# default:
# host: ${SW_RECEIVER_ZIPKIN_HOST:0.0.0.0}
# port: ${SW_RECEIVER_ZIPKIN_PORT:9411}
# contextPath: ${SW_RECEIVER_ZIPKIN_CONTEXT_PATH:/}
query:
graphql:
path: ${SW_QUERY_GRAPHQL_PATH:/graphql}
alarm:
default:
telemetry:
none:
datasource-settings.properties配置如下:
jdbcUrl=jdbc:mysql://192.168.1.100:3306/swtest
dataSource.user=root
dataSource.password=MyNewPass4!
dataSource.cachePrepStmts=true
dataSource.prepStmtCacheSize=250
dataSource.prepStmtCacheSqlLimit=2048
dataSource.useServerPrepStmts=true
dataSource.useLocalSessionState=true
dataSource.rewriteBatchedStatements=true
dataSource.cacheResultSetMetadata=true
dataSource.cacheServerConfiguration=true
dataSource.elideSetAutoCommits=true
dataSource.maintainTimeStats=false
在bin目录下执行startup.bat
在log目录下查看两个日志文件
skywalking-oap-server.log
webapp.log
没报错打开http://localhost:8080查看
拷贝三个agent并修改文件名
分别修改这三个agent的agent.config配置文件
agent.service_name=gz-auth
collector.backend_service=127.0.0.1:11800
logging.level=debug
agent.service_name=gz-gate
collector.backend_service=127.0.0.1:11800
logging.level=debug
agent.service_name=gz-admin
collector.backend_service=127.0.0.1:11800
logging.level=debug
分别用这三个agent启动,在vm启动参数配置agent
参考配置
-javaagent:D:\Workspace\Others\hello-spring-cloud-alibaba\hello-spring-cloud-external-skywalking\agent\skywalking-agent.jar
-Dskywalking.agent.service_name=nacos-provider -
查看agent目录下的log
启动成功
在web端查看三个应用的调用情况
SkyWalking 通过业务调用监控进行依赖分析,提供给我们了服务之间的服务调用拓扑关系、以及针对每个 Endpoint 的 Trace 记录。
点击 Trace
菜单,进入追踪页
点击 Trace ID
展开详细信息
上图展示了一次正常的响应,总响应时间为 185ms
共有一个 Span(基本工作单元,表示一次完整的请求,包含响应,即请求并响应)
Span /echo/{message}
说明如下:
Duration:响应时间 185 毫秒
component:组件类型为 SpringMVC
url:请求地址
http.method:请求类型
点击 Service
菜单,进入服务性能指标监控页
选择希望监控的服务
Avg SLA: 服务可用性(主要是通过请求成功与失败次数来计算)
CPM: 每分钟调用次数
Avg Response Time: 平均响应时间
点击 More Server Details...
还可以查看详细信息
上图中展示了服务在一定时间范围内的相关数据,包括:
服务可用性指标 SLA
每分钟平均响应数
平均响应时间
服务进程 PID
服务所在物理机的 IP、Host、OS
运行时 CPU 使用率
运行时堆内存使用率
运行时非堆内存使用率
GC 情况
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