微服务组件---- Spring Cloud Alibaba 链路追踪 skywalking 详解 - ToB企服应用市场:ToB评测及商务社交产业平台

#!/bin/sh
# SkyWalking Agent配置
export SW_AGENT_NAME=springboot-skywalking-demo #Agent名字,一般使用`spring.application.name`
export SW_AGENT_COLLECTOR_BACKEND_SERVICES=127.0.0.1:11800 #配置 Collector 地址。
export SW_AGENT_SPAN_LIMIT=2000 #配置链路的最大Span数量，默认为 300。
export JAVA_AGENT=-javaagent:/root/skywalking-agent/skywalking-agent.jar
java $JAVA_AGENT -jar springboot-skywalking-demo-0.0.1-SNAPSHOT.jar #jar启动

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java -javaagent:/root/skywalking-agent/skywalking-agent.jar
-DSW_AGENT_COLLECTOR_BACKEND_SERVICES=127.0.0.1:11800
-DSW_AGENT_NAME=springboot-skywalking-demo -jar springboot-skywalking-demo-0.0.1-SNAPSHOT.jar

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在运行的程序配置jvm参数
-javaagent:E:\SpringCloudAlibaba\apache-skywalking-apm-bin-es7\agent\skywalking-agent.jar
-DSW_AGENT_NAME=springboot-skywalking-demo
-DSW_AGENT_COLLECTOR_BACKEND_SERVICES=127.0.0.1:11800

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<dependency>
<groupId>org.apache.skywalking</groupId>
<artifactId>apm-toolkit-trace</artifactId>
<version>8.11.0</version>
</dependency>

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@RequestMapping("/list")
public List<User> list(){
//TraceContext可以绑定key-value
TraceContext.putCorrelation("name", "fox");
Optional<String> op = TraceContext.getCorrelation("name");
log.info("name = {} ", op.get());
//获取追踪的traceId
String traceId = TraceContext.traceId();
log.info("traceId = {} ", traceId);
return userService.list();
}

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@Trace
@Tag(key = "list", value = "returnedObj")
public List<User> list(){
return userMapper.list();
}
@Trace
@Tags({@Tag(key = "param", value = "arg[0]"),
@Tag(key = "user", value = "returnedObj")})
public User getById(Integer id){
return userMapper.getById(id);
}

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storage:
#选择使用mysql 默认使用h2，不会持久化，重启skyWalking之前的数据会丢失
selector: ${SW_STORAGE:mysql}
#使用mysql作为持久化存储的仓库
mysql:
properties:
#数据库连接地址创建swtest数据库
jdbcUrl: ${SW_JDBC_URL:"jdbc:mysql://1ocalhost:3306/swtest"}
#用户名
dataSource.user: ${SW_DATA_SOURCE_USER:root}
#密码
dataSource.password: ${SW_DATA_SOURCE_PASSWORD:root}

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storage:
selector: ${SW_STORAGE:elasticsearch} //指定ES作为存储
elasticsearch:
nameSpace: ${SW_NAMESPACE:"myProject-"} //指定命名空间，用于生成索引前缀
clusterNodes: ${SW_STORAGE_ES_CLUSTER_NODES:localhost:9200} //配置集群节点，当然可以采用负载均衡【然后把负载均衡的服务器ip与端口写入】，但也可以把节点都写进去
user: ${SW_ES_USER:"myes"} //es的用户名
password: ${SW_ES_PASSWORD:"123456"} //es的密码

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1.告警规则：它们定义了应该如何触发度量警报，应该考虑什么条件；
2.网络钩子(Webhook}：当警告触发时，哪些服务终端需要被通知；
3.gRPC钩子：远程gRPC方法的主机和端口，告警触发后调用；

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# Sample alarm rules.
rules:
# Rule unique name, must be ended with `_rule`.
service_resp_time_rule:
metrics-name: service_resp_time
op: ">"
threshold: 1000
period: 10
count: 3
silence-period: 5
#在最近10分钟的3分钟内服务平均响应时间超过1000ms
message: Response time of service {name} is more than 1000ms in 3 minutes of last 10 minutes.
service_sla_rule:
# Metrics value need to be long, double or int
metrics-name: service_sla
op: "<"
threshold: 8000
# The length of time to evaluate the metrics
period: 10
# How many times after the metrics match the condition, will trigger alarm
count: 2
# How many times of checks, the alarm keeps silence after alarm triggered, default as same as period.
silence-period: 3
#最近10分钟内，服务成功率在2分钟内低于80%
message: Successful rate of service {name} is lower than 80% in 2 minutes of last 10 minutes
service_resp_time_percentile_rule:
# Metrics value need to be long, double or int
metrics-name: service_percentile
op: ">"
threshold: 1000,1000,1000,1000,1000
period: 10
count: 3
silence-period: 5
message: Percentile response time of service {name} alarm in 3 minutes of last 10 minutes, due to more than one condition of p50 > 1000, p75 > 1000, p90 > 1000, p95 > 1000, p99 > 1000
service_instance_resp_time_rule:
metrics-name: service_instance_resp_time
op: ">"
threshold: 1000
period: 10
count: 2
silence-period: 5
#服务实例的响应时间在过去10分钟的2分钟内超过1000ms
message: Response time of service instance {name} is more than 1000ms in 2 minutes of last 10 minutes
database_access_resp_time_rule:
metrics-name: database_access_resp_time
threshold: 1000
op: ">"
period: 10
count: 2
#数据库访问{name}的响应时间在过去10分钟的2分钟内超过1000ms
message: Response time of database access {name} is more than 1000ms in 2 minutes of last 10 minutes
endpoint_relation_resp_time_rule:
metrics-name: endpoint_relation_resp_time
threshold: 1000
op: ">"
period: 10
count: 2
#端点关系{name}的响应时间在过去10分钟的2分钟内超过1000ms
message: Response time of endpoint relation {name} is more than 1000ms in 2 minutes of last 10 minutes
# Active endpoint related metrics alarm will cost more memory than service and service instance metrics alarm.
# Because the number of endpoint is much more than service and instance.
#
# endpoint_avg_rule:
# metrics-name: endpoint_avg
# op: ">"
# threshold: 1000
# period: 10
# count: 2
# silence-period: 5
# message: Response time of endpoint {name} is more than 1000ms in 2 minutes of last 10 minutes
#需要自己手动打开
webhooks:
- http://127.0.0.1/notify/
# - http://127.0.0.1/go-wechat/

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metrics-name：度量名称，也是OAL脚本中的度量名。默认配置中可以用于告警的度量有：服务，实例，端点，服务关系，实例关系，端点关系。它只支持long,double和int类型。
op：操作符。
threshold：阈值。
period：多久告警规则需要被检查一下。这是一个时间窗口，与后端部署环境时间相匹配。
count：在一个周期窗口中，如果按op计算超过阈值的次数达到count，则发送告警
silence-period：在时间N中触发报警后，在N -> N + silence-period这段时间内不告警。
message：该规则触发时，发送的通知消息。

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@RequestMapping("/notify")
public String notify(@RequestBody Object obj){
//TODO 告警信息，给技术负责人发短信，钉钉消息，邮件，微信通知等
System.err.println(obj.toString());
return "notify successfully";
}

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dingtalkHooks:
textTemplate: |-
{
"msgtype": "text",
"text": {
"content": "Apache SkyWalking Alarm: \n %s."
}
}
webhooks:
- url: https://oapi.dingtalk.com/robot/send?access_token=dummy_token
secret: dummysecret

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scopeId. 所有可用的Scope，参考：org.apache.skywalking.oap.server.core.source.DefaultScopeDefine；
name. 目标 Scope 的实体名称；
id0. Scope 实体的 ID；
id1. 未使用；
ruleName. 在 alarm-settings.yml 中配置的规则名；
alarmMessage. 报警消息内容；
startTime. 告警时间, 位于当前时间与 UTC 1970/1/1 之间；

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