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分布式应用监控: SkyWalking 快速接入实践

走过路过不要错过


分布式应用,会存在各种问题。而要解决这些难题,除了要应用自己做一些监控埋点外,还应该有一些外围的系统进行主动探测,主动发现。

APM工具就是干这活的,SkyWalking 是国人开源的一款优秀的APM应用,已成为apache的顶级项目。

今天我们就来实践下 SkyWalking 下吧。

实践目标:达到监控现有的几个系统,清楚各调用关系,可以找到出性能问题点。

实践步骤:

  1. SkyWalking 服务端安装运行;
  2. 应用端的接入;
  3. 后台查看效果;
  4. 分析排查问题;
  5. 深入了解(如有心情);



1:SkyWalking 服务端安装

下载应用包:

 # 主下载页 http://skywalking.apache.org/downloads/ # 点开具体下载地址后进行下载,如: wget http://mirrors.tuna.tsinghua.edu.cn/apache/skywalking/6.5.0/apache-skywalking-apm-6.5.0.tar.gz

解压安装包:

 tar -xzvf apache-skywalking-apm-6.5.0.tar.gz

使用默认配置端口,默认存储方式 h2, 直接启动服务:

./bin/startup.sh

好产品就是这么简单!

 

当然,上面是已存在应用的页面。现在你是看不到任何应用的,因为你还没有接入嘛。

2. 应用端的接入

我们只以java应用接入方式实践。

直接使用 javaagent 进行启动即可:

 java -javaagent:/root/skywalking/agent/skywalking-agent.jar -Dskywalking.agent.service_name=app1 -Dskywalking.collector.backend_service=localhost:11800 -jar myapp.jar

参数说明:

 # 参数解释 skywalking.agent.service_name: 本应用在skywalking中的名称 skywalking.collector.backend_service: skywalking 服务端地址,grpc上报地址,默认端口是 11800 # 上面两个参数也可以使用另外的表现形式 SW_AGENT_COLLECTOR_BACKEND_SERVICES: 与 skywalking.collector.backend_service 含义相同 SW_AGENT_NAME: 与 skywalking.agent.service_name 含义相同

随便访问几个接口或页面,使监控抓取到数据。

再回管理页面,已经看到有节点了。截图如上。

现在我们还可以查看各应用之间的关系了!

分布式应用监控: SkyWalking 快速接入实践

关系清晰吧!一目了然,代码再复杂也不怕了。

我们还可以追踪具体链路:

分布式应用监控: SkyWalking 快速接入实践

只要知道问题发生的时间点,即可以很快定位到发生问题的接口、系统,快速解决。

3. SkyWalking 配置文件

如上,我们并没有改任何配置文件,就让系统跑起来了。幸运的同时,我们应该要知道更多!至少配置得知道。

config/application.yml : 收集器服务端配置

webapp/webapp.yml : 配置 Web 的端口及获取数据的 OAP(Collector)的IP和端口

下面是 skywalking 的默认配置,我们可以不用更改就能跑起来一个样例!更改以生产化配置!

config/application.yml

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# # Enable ACL# enableACL: ${SW_ZK_ENABLE_ACL:false} # disable ACL in default# schema: ${SW_ZK_SCHEMA:digest} # only support digest schema# expression: ${SW_ZK_EXPRESSION:skywalking:skywalking}# 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}# nacos:# serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}# hostPort: ${SW_CLUSTER_NACOS_HOST_PORT:localhost:8848}# # Nacos Configuration namespace# namespace: 'public'# etcd:# serviceName: ${SW_SERVICE_NAME:"SkyWalking_OAP_Cluster"}# etcd cluster nodes, example: 10.0.0.1:2379,10.0.0.2:2379,10.0.0.3:2379# hostPort: ${SW_CLUSTER_ETCD_HOST_PORT:localhost:2379}core: default: # Mixed: Receive agent data, Level 1 aggregate, Level 2 aggregate # Receiver: Receive agent data, Level 1 aggregate # Aggregator: Level 2 aggregate role: ${SW_CORE_ROLE:Mixed} # Mixed/Receiver/Aggregator restHost: ${SW_CORE_REST_HOST:0.0.0.0} restPort: ${SW_CORE_REST_PORT:12800} restContextPath: ${SW_CORE_REST_CONTEXT_PATH:/} gRPCHost: ${SW_CORE_GRPC_HOST:0.0.0.0} gRPCPort: ${SW_CORE_GRPC_PORT:11800} downsampling: - Hour - Day - Month # Set a timeout on metrics data. After the timeout has expired, the metrics data will automatically be deleted. enableDataKeeperExecutor: ${SW_CORE_ENABLE_DATA_KEEPER_EXECUTOR:true} # Turn it off then automatically metrics data delete will be close. dataKeeperExecutePeriod: ${SW_CORE_DATA_KEEPER_EXECUTE_PERIOD:5} # How often the data keeper executor runs periodically, unit is minute 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 # Cache metric data for 1 minute to reduce database queries, and if the OAP cluster changes within that minute, # the metrics may not be accurate within that minute. enableDatabaseSession: ${SW_CORE_ENABLE_DATABASE_SESSION:true}storage:# elasticsearch:# nameSpace: ${SW_NAMESPACE:""}# clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200}# protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:"http"}# trustStorePath: ${SW_SW_STORAGE_ES_SSL_JKS_PATH:"../es_keystore.jks"}# trustStorePass: ${SW_SW_STORAGE_ES_SSL_JKS_PASS:""}# user: ${SW_ES_USER:""}# password: ${SW_ES_PASSWORD:""}# indexShardsNumber: ${SW_STORAGE_ES_INDEX_SHARDS_NUMBER:2}# indexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:0}# # Those data TTL settings will override the same settings in core module.# recordDataTTL: ${SW_STORAGE_ES_RECORD_DATA_TTL:7} # Unit is day# otherMetricsDataTTL: ${SW_STORAGE_ES_OTHER_METRIC_DATA_TTL:45} # Unit is day# monthMetricsDataTTL: ${SW_STORAGE_ES_MONTH_METRIC_DATA_TTL:18} # Unit is month# # 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:1000} # Execute the bulk every 1000 requests# 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# 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} 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} metadataQueryMaxSize: ${SW_STORAGE_H2_QUERY_MAX_SIZE:5000}# mysql:# properties:# jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://localhost:3306/swtest"}# 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}receiver-sharing-server: default: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. slowDBAccessThreshold: ${SW_SLOW_DB_THRESHOLD:default:200,mongodb:100} # The slow database access thresholds. Unit ms.receiver-jvm: default:receiver-clr: 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:envoy-metric: default:# alsHTTPAnalysis: ${SW_ENVOY_METRIC_ALS_HTTP_ANALYSIS:k8s-mesh}#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:configuration: none:# apollo:# apolloMeta: http://106.12.25.204:8080# apolloCluster: default# # apolloEnv: # defaults to null# appId: skywalking# period: 5# nacos:# # Nacos Server Host# serverAddr: 127.0.0.1# # Nacos Server Port# port: 8848# # Nacos Configuration Group# group: 'skywalking'# # Nacos Configuration namespace# namespace: ''# # Unit seconds, sync period. Default fetch every 60 seconds.# period : 60# # the name of current cluster, set the name if you want to upstream system known.# clusterName: "default"# zookeeper:# period : 60 # Unit seconds, sync period. Default fetch every 60 seconds.# nameSpace: /default# hostPort: localhost:2181# #Retry Policy# baseSleepTimeMs: 1000 # initial amount of time to wait between retries# maxRetries: 3 # max number of times to retry# etcd:# period : 60 # Unit seconds, sync period. Default fetch every 60 seconds.# group : 'skywalking'# serverAddr: localhost:2379# clusterName: "default"# consul:# # Consul host and ports, separated by comma, e.g. 1.2.3.4:8500,2.3.4.5:8500# hostAndPorts: ${consul.address}# # Sync period in seconds. Defaults to 60 seconds.# period: 1
#exporter:# grpc:# targetHost: ${SW_EXPORTER_GRPC_HOST:127.0.0.1}# targetPort: ${SW_EXPORTER_GRPC_PORT:9870}

webapp/webapp.yml

server: port: 8080
collector: path: /graphql ribbon: ReadTimeout: 10000 # Point to all backend's restHost:restPort, split by , listOfServers: 127.0.0.1:12800

agent/config/agent.config

# The agent namespace# agent.namespace=${SW_AGENT_NAMESPACE:default-namespace}
# The service name in UIagent.service_name=${SW_AGENT_NAME:Your_ApplicationName}
# The number of sampled traces per 3 seconds# Negative number means sample traces as many as possible, most likely 100%# agent.sample_n_per_3_secs=${SW_AGENT_SAMPLE:-1}
# Authentication active is based on backend setting, see application.yml for more details.# agent.authentication = ${SW_AGENT_AUTHENTICATION:xxxx}
# The max amount of spans in a single segment.# Through this config item, skywalking keep your application memory cost estimated.# agent.span_limit_per_segment=${SW_AGENT_SPAN_LIMIT:300}
# Ignore the segments if their operation names end with these suffix.# agent.ignore_suffix=${SW_AGENT_IGNORE_SUFFIX:.jpg,.jpeg,.js,.css,.png,.bmp,.gif,.ico,.mp3,.mp4,.html,.svg}
# If true, skywalking agent will save all instrumented classes files in `/debugging` folder.# Skywalking team may ask for these files in order to resolve compatible problem.# agent.is_open_debugging_class = ${SW_AGENT_OPEN_DEBUG:true}
# The operationName max length# agent.operation_name_threshold=${SW_AGENT_OPERATION_NAME_THRESHOLD:500}
# Backend service addresses.collector.backend_service=${SW_AGENT_COLLECTOR_BACKEND_SERVICES:127.0.0.1:11800}
# Logging file_namelogging.file_name=${SW_LOGGING_FILE_NAME:skywalking-api.log}
# Logging levellogging.level=${SW_LOGGING_LEVEL:DEBUG}
# Logging dir# logging.dir=${SW_LOGGING_DIR:""}
# Logging max_file_size, default: 300 * 1024 * 1024 = 314572800# logging.max_file_size=${SW_LOGGING_MAX_FILE_SIZE:314572800}
# The max history log files. When rollover happened, if log files exceed this number,# then the oldest file will be delete. Negative or zero means off, by default.# logging.max_history_files=${SW_LOGGING_MAX_HISTORY_FILES:-1}
# mysql plugin configuration# plugin.mysql.trace_sql_parameters=${SW_MYSQL_TRACE_SQL_PARAMETERS:false}

4. SkyWalking 架构

来自官网的图片,感受一下!无须细说,大概原理就是:针对各种不同客户端实现不同的指标采集,统一通过grpc/http发送到apm服务端,然后经过分析引擎后存储到es/h2/mysql等等存储系统,最后由前端通过查询引擎进行展现。

分布式应用监控: SkyWalking 快速接入实践

5. 可以用来干啥

发现系统耗时或者说瓶颈在哪里。

发现各系统之间的调用关系。

监控服务异常。

排查系统故障。

6. 其他存储系统接入

h2只是一个内存存储系统,其目的是为了让你能够快速验证快速响应,它还没有强大到足以支撑线上系统运行。

所以,线上一定得选用某个更可靠存储。

一般地,ES会是个不错的选择,一来它以搜索速度著称而这正好符合后台查询的需求,二来es是分布式存储,可以避免一定的大数据量问题。

mysql: 一般地对普通开发同学友好,且单机mysql容易搭建。

tidb: 与mysql协议完全兼容,分布式存储。

配置方法如demo所示。。。




分布式应用监控: SkyWalking 快速接入实践
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分布式应用监控: SkyWalking 快速接入实践
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分布式应用监控: SkyWalking 快速接入实践

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出处:https://www.cnblogs.com/yougewe/p/11973117.html