网站建设管理与维护ppt,淘宝网页版官网入口,自己怎么自学软件开发,人才网招聘官方网一、前言
Apache SkyWalking 是一个开源的分布式跟踪、监控和诊断系统#xff0c;旨在帮助用户监控和诊断分布式应用程序、微服务架构和云原生应用的性能和健康状况。它提供了可视化的分析工具#xff0c;帮助开发人员和运维团队深入了解应用程序的性能、调用链和异常情况
…一、前言
Apache SkyWalking 是一个开源的分布式跟踪、监控和诊断系统旨在帮助用户监控和诊断分布式应用程序、微服务架构和云原生应用的性能和健康状况。它提供了可视化的分析工具帮助开发人员和运维团队深入了解应用程序的性能、调用链和异常情况
功能特点
分布式跟踪 SkyWalking 能够追踪分布式应用程序的请求调用链显示每个请求从发起到结束的完整流程包括各个组件和服务之间的调用关系。这有助于定位性能瓶颈和延迟问题
性能监控 SkyWalking 收集并展示应用程序的性能指标如响应时间、吞吐量、错误率等以图表和图形的形式呈现帮助用户监控应用程序的健康状况
实时告警 SkyWalking 具备实时告警功能可以根据用户定义的条件和阈值生成警报。当应用程序出现性能问题或异常时系统会发送通知让团队能够及时采取行动
多语言支持 SkyWalking 支持多种编程语言和技术栈包括 Java、Python、Go、.NET 等。这使得它适用于各种类型的应用程序
可视化界面 SkyWalking 提供了直观的 Web 界面用户可以通过图表、仪表盘和可视化的调用链图来查看和分析应用程序的性能数据
二、部署
部署skywalking之前需要先部署java环境我用的是skywalking的9.4.0版本所有需要使用jdk11本版的java环境
部署java参考jdk1.8环境配置_Apex Predator的博客-CSDN博客 部署skywalking服务需要先下载安装包我这边使用的是9.4.0版本
下载路径参考Downloads | Apache SkyWalking 创建skywalking存放目录并将安装包放到该目录下解压
mkdir /opt/skywalking cd /opt/skywalking
tar -zxvf apache-skywalking-apm-9.4.0.tar.gz mv apache-skywalking-apm-9.4.0 skywalking
编辑skywalking配置文件主要是配置数据存放的选择默认使用自带的h2存储我们这边改成使用elasticsearch作为存储
vi skywalking/config/application.yml
storage:selector: ${SW_STORAGE:elasticsearch} #配置为以下elasticsearch配置的名称elasticsearch: #将此项名称填入上面的配置中namespace: ${SW_NAMESPACE:}clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:10.1.60.114:9200,10.1.60.115:9200} #配置elasticsearch集群的地址protocol: ${SW_STORAGE_ES_HTTP_PROTOCOL:http}connectTimeout: ${SW_STORAGE_ES_CONNECT_TIMEOUT:3000}socketTimeout: ${SW_STORAGE_ES_SOCKET_TIMEOUT:30000}responseTimeout: ${SW_STORAGE_ES_RESPONSE_TIMEOUT:15000}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 indexesindexReplicasNumber: ${SW_STORAGE_ES_INDEX_REPLICAS_NUMBER:1} # Replicas number of new indexes# Specify the settings for each index individually.# If configured, this setting has the highest priority and overrides the generic settings.specificIndexSettings: ${SW_STORAGE_ES_SPECIFIC_INDEX_SETTINGS:}# 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_STORAGE_ES_SUPER_DATASET_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 0superDatasetIndexShardsFactor: ${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 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 templatebulkActions: ${SW_STORAGE_ES_BULK_ACTIONS:5000} # Execute the async bulk record data every ${SW_STORAGE_ES_BULK_ACTIONS} requestsbatchOfBytes: ${SW_STORAGE_ES_BATCH_OF_BYTES:10485760} # A threshold to control the max body size of ElasticSearch Bulk flush.# flush the bulk every 5 seconds whatever the number of requestsflushInterval: ${SW_STORAGE_ES_FLUSH_INTERVAL:5}concurrentRequests: ${SW_STORAGE_ES_CONCURRENT_REQUESTS:2} # the number of concurrent requestsresultWindowMaxSize: ${SW_STORAGE_ES_QUERY_MAX_WINDOW_SIZE:10000}metadataQueryMaxSize: ${SW_STORAGE_ES_QUERY_MAX_SIZE:10000}scrollingBatchSize: ${SW_STORAGE_ES_SCROLLING_BATCH_SIZE:5000}segmentQueryMaxSize: ${SW_STORAGE_ES_QUERY_SEGMENT_SIZE:200}profileTaskQueryMaxSize: ${SW_STORAGE_ES_QUERY_PROFILE_TASK_SIZE:200}profileDataQueryBatchSize: ${SW_STORAGE_ES_QUERY_PROFILE_DATA_BATCH_SIZE:100}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:}# Enable shard metrics and records indices into multi-physical indices, one index template per metric/meter aggregation function or record.logicSharding: ${SW_STORAGE_ES_LOGIC_SHARDING:false}# Custom routing can reduce the impact of searches. Instead of having to fan out a search request to all the shards in an index, the request can be sent to just the shard that matches the specific routing value (or values).enableCustomRouting: ${SW_STORAGE_ES_ENABLE_CUSTOM_ROUTING:false}h2:properties:jdbcUrl: ${SW_STORAGE_H2_URL:jdbc:h2:mem:skywalking-oap-db;DB_CLOSE_DELAY-1}dataSource.user: ${SW_STORAGE_H2_USER:sa}metadataQueryMaxSize: ${SW_STORAGE_H2_QUERY_MAX_SIZE:5000}maxSizeOfBatchSql: ${SW_STORAGE_MAX_SIZE_OF_BATCH_SQL:100}asyncBatchPersistentPoolSize: ${SW_STORAGE_ASYNC_BATCH_PERSISTENT_POOL_SIZE:1}
配置skywalking web服务
vi skywalking/webapp/application.yml
serverPort: ${SW_SERVER_PORT:-18080} #默认端口为8080避免冲突改为18080# Comma seperated list of OAP addresses.
oapServices: ${SW_OAP_ADDRESS:-http://localhost:12800} #这些配置保持默认即可zipkinServices: ${SW_ZIPKIN_ADDRESS:-http://localhost:9412} 启动skywalking服务
./skywalking/bin/startup.sh 可以看到oap服务和web服务都启动成功了
查看skywalking的端口
netstat -tlpn 以上五个端口都是skywalking使用的服务端口如果有端口被占用服务就会起不来
访问skywalking web服务
http://10.1.60.115:18080 我这边是已经配置了agent监控java服务所以会有服务信息配置agent监控java服务会在下一篇讲解
