SkyWalking系列（一）：初探

SkyWalking已經再微服務商城系列裏使用了，本篇將介紹如何再Windows系統下安裝並簡單使用。

1.下載SkyWaling

本篇測試使用6.0版本：http://skywalking.apache.org/downloads/

若是隻是簡單測試咱們無需任何修改，直接啓用bin文件夾裏的startup.bat，默認使用內存H2存儲，等會換成ES，而後直接防衛localhost:8080：

 

安裝 SkyAPM.DotNet.CLI：

dotnet tool install -g SkyAPM.DotNet.CLI

 

2.在.net core中使用SkyWalking：

建立.net core API項目SkyWalking_Practice，經過NuGet引用SkyAPM.Agent.AspNetCore（最新版SkyWalking已更名SkyAPM）。

右鍵屬性，在調試中添加環境變量：

ASPNETCORE_HOSTINGSTARTUPASSEMBLIES：SkyAPM.Agent.AspNetCore

SKYWALKING__SERVICENAME：SkyWalking_Practice（這裏配置項目程序集名稱）

 

 而後咱們就須要配置SkyWalking了，配置方式有兩種，一種是在Startup.cs的ConfigureServices中配置相關信息，另外一種是經過配置文件的方式，本篇將經過配置文件的方式來實現：

在CMD命令行中cd到項目文件根目錄，使用以下命令自動生成Json配置文件（11800端口是其數據採上報端口）：

dotnet skyapm config SkyWalking_Practice localhost:11800

 

命令執行成功後會自動生成：skyapm.json，能夠根據實際狀況進行更改調整。

 

 到這裏配置環節就算完成了，咱們能夠直接運行當前項目，多訪問幾回後查看SkyWalking的UI，會看到對應訪問數據：

 

 

 

配置ElasticSearch做爲存儲程序

 

Skying的不一樣版本對於ES的版本是有要求的，6.X的SkyWalking要求使用6.X的ES，首先咱們須要下載ES：https://www.elastic.co/cn/downloads/elasticsearch

 

下載完成後修改config文件夾下的elasticsearch.yml配置文件：

cluster.name: mi bootstrap.memory_lock: false network.host: localhost http.port: 9200

cluster.Name須要小寫，以前大寫報錯。cluster.name須要和SkyWalking中的保持一致，默認CollectorDBCluster，你們能夠自行修改。

 

貼一下完整配置當記錄：

# ======================== Elasticsearch Configuration ========================= # # NOTE: Elasticsearch comes with reasonable defaults for most settings. # Before you set out to tweak and tune the configuration, make sure you # understand what are you trying to accomplish and the consequences. # # The primary way of configuring a node is via this file. This template lists # the most important settings you may want to configure for a production cluster. # # Please consult the documentation for further information on configuration options: # https://www.elastic.co/guide/en/elasticsearch/reference/index.html
# # ---------------------------------- Cluster ----------------------------------- # # Use a descriptive name for your cluster: # cluster.name: mi # # ------------------------------------ Node ------------------------------------ # # Use a descriptive name for the node: # #node.name: node-1 # # Add custom attributes to the node: # #node.attr.rack: r1 # # ----------------------------------- Paths ------------------------------------ # # Path to directory where to store the data (separate multiple locations by comma): # #path.data: /path/to/data # # Path to log files: # #path.logs: /path/to/logs # # ----------------------------------- Memory ----------------------------------- # # Lock the memory on startup: # bootstrap.memory_lock: false # # Make sure that the heap size is set to about half the memory available # on the system and that the owner of the process is allowed to use this # limit. # # Elasticsearch performs poorly when the system is swapping the memory. # # ---------------------------------- Network ----------------------------------- # # Set the bind address to a specific IP (IPv4 or IPv6): # network.host: localhost # # Set a custom port for HTTP: # http.port: 9200 # # For more information, consult the network module documentation. # # --------------------------------- Discovery ---------------------------------- # # Pass an initial list of hosts to perform discovery when new node is started: # The default list of hosts is ["127.0.0.1", "[::1]"] # #discovery.zen.ping.unicast.hosts: ["host1", "host2"] # # Prevent the "split brain" by configuring the majority of nodes (total number of master-eligible nodes / 2 + 1): # #discovery.zen.minimum_master_nodes: # # For more information, consult the zen discovery module documentation. # # ---------------------------------- Gateway ----------------------------------- # # Block initial recovery after a full cluster restart until N nodes are started: # #gateway.recover_after_nodes: 3 # # For more information, consult the gateway module documentation. # # ---------------------------------- Various ----------------------------------- # # Require explicit names when deleting indices: # #action.destructive_requires_name: true

 

完成後啓動ES，經過bin文件下的elasticsearch.bat啓動，啓動後訪問 http://localhost:9200/：

ES啓動以後咱們須要修改下SkyWalking的配置以支持ES：

須要將nameSpace改爲和ES中一致，這裏也貼一下完整配置作個記錄：

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0
# # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. 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: ${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 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:"mi"} 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:

而後經過bin文件夾下的startup.bat批處理命令啓動SkyWalking，而後訪問http://localhost:8080可以出現UI界面則正常，而後啓動咱們的.net core API項目，出現數據：

 

 OK，到此完成。