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skywalking支持的采集指标及告警设置
更新时间 2022-2-20 浏览2564次
Skywalking的oap指标存放在：/apache-skywalking-apm-bin-es78/config/oal/*.oap 目录下
java-agent.oal
// JVM instance metrics instance_jvm_cpu = from(ServiceInstanceJVMCPU.usePercent).doubleAvg();//jvm 平均cpu耗时百分比 instance_jvm_memory_heap = from(ServiceInstanceJVMMemory.used).filter(heapStatus == true).longAvg();//jvm 堆空间的平均使用空间 instance_jvm_memory_noheap = from(ServiceInstanceJVMMemory.used).filter(heapStatus == false).longAvg();//jvm 非堆空间的平均使用空间 instance_jvm_memory_heap_max = from(ServiceInstanceJVMMemory.max).filter(heapStatus == true).longAvg();//jvm 最大堆内存的平均值 instance_jvm_memory_noheap_max = from(ServiceInstanceJVMMemory.max).filter(heapStatus == false).longAvg();//jvm 最大非堆内存的平均值 instance_jvm_young_gc_time = from(ServiceInstanceJVMGC.time).filter(phrase == GCPhrase.NEW).sum();//年轻代gc的耗时 instance_jvm_old_gc_time = from(ServiceInstanceJVMGC.time).filter(phrase == GCPhrase.OLD).sum();//老年代gc的耗时 instance_jvm_young_gc_count = from(ServiceInstanceJVMGC.count).filter(phrase == GCPhrase.NEW).sum();//年轻代gc的次数 instance_jvm_old_gc_count = from(ServiceInstanceJVMGC.count).filter(phrase == GCPhrase.OLD).sum();//老年代gc的次数 instance_jvm_thread_live_count = from(ServiceInstanceJVMThread.liveCount).longAvg();//存活的线程数 instance_jvm_thread_daemon_count = from(ServiceInstanceJVMThread.daemonCount).longAvg();//守护线程数 instance_jvm_thread_peak_count = from(ServiceInstanceJVMThread.peakCount).longAvg();//峰值线程数
core.oal
/ All scope metrics all_percentile = from(All.latency).percentile(10); // Multiple values including p50, p75, p90, p95, p99 all_heatmap = from(All.latency).histogram(100, 20); // // Service scope metrics 服务 service_resp_time = from(Service.latency).longAvg(); // 服务的平均响应时间 service_sla = from(Service.*).percent(status == true); // 服务的请求成功率 service_cpm = from(Service.*).cpm(); //服务的每分钟调用次数 service_percentile = from(Service.latency).percentile(10); // Multiple values including p50, p75, p90, p95, p99 service_apdex = from(Service.latency).apdex(name, status); // 服务的应用性能指标，apdex的衡量的是衡量满意的响应时间与不满意的响应时间的比率，默认的请求满意时间是500ms // Service relation scope metrics for topology 服务与服务间调用的调用度量指标 service_relation_client_cpm = from(ServiceRelation.*).filter(detectPoint == DetectPoint.CLIENT).cpm();//在客户端检测到的每分钟调用次数 service_relation_server_cpm = from(ServiceRelation.*).filter(detectPoint == DetectPoint.SERVER).cpm();//在服务端检测到的每分钟调用的次数 service_relation_client_call_sla = from(ServiceRelation.*).filter(detectPoint == DetectPoint.CLIENT).percent(status == true);//在客户端检测到成功率 service_relation_server_call_sla = from(ServiceRelation.*).filter(detectPoint == DetectPoint.SERVER).percent(status == true);//在服务端检测到的成功率 service_relation_client_resp_time = from(ServiceRelation.latency).filter(detectPoint == DetectPoint.CLIENT).longAvg();//在客户端检测到的平均响应时间 service_relation_server_resp_time = from(ServiceRelation.latency).filter(detectPoint == DetectPoint.SERVER).longAvg();//在服务端检测到的平均响应时间 service_relation_client_percentile = from(ServiceRelation.latency).filter(detectPoint == DetectPoint.CLIENT).percentile(10); // Multiple values including p50, p75, p90, p95, p99 service_relation_server_percentile = from(ServiceRelation.latency).filter(detectPoint == DetectPoint.SERVER).percentile(10); // Multiple values including p50, p75, p90, p95, p99 // Service Instance relation scope metrics for topology 服务实例与服务实例之间的调用度量指标 service_instance_relation_client_cpm = from(ServiceInstanceRelation.*).filter(detectPoint == DetectPoint.CLIENT).cpm();//在客户端实例检测到的每分钟调用次数 service_instance_relation_server_cpm = from(ServiceInstanceRelation.*).filter(detectPoint == DetectPoint.SERVER).cpm();//在服务端实例检测到的每分钟调用次数 service_instance_relation_client_call_sla = from(ServiceInstanceRelation.*).filter(detectPoint == DetectPoint.CLIENT).percent(status == true);//在客户端实例检测到的成功率 service_instance_relation_server_call_sla = from(ServiceInstanceRelation.*).filter(detectPoint == DetectPoint.SERVER).percent(status == true);//在服务端实例检测到的成功率 service_instance_relation_client_resp_time = from(ServiceInstanceRelation.latency).filter(detectPoint == DetectPoint.CLIENT).longAvg();//在客户端实例检测到的平均响应时间 service_instance_relation_server_resp_time = from(ServiceInstanceRelation.latency).filter(detectPoint == DetectPoint.SERVER).longAvg();//在服务端实例检测到的平均响应时间 service_instance_relation_client_percentile = from(ServiceInstanceRelation.latency).filter(detectPoint == DetectPoint.CLIENT).percentile(10); // Multiple values including p50, p75, p90, p95, p99 service_instance_relation_server_percentile = from(ServiceInstanceRelation.latency).filter(detectPoint == DetectPoint.SERVER).percentile(10); // Multiple values including p50, p75, p90, p95, p99 // Service Instance Scope metrics service_instance_sla = from(ServiceInstance.*).percent(status == true);//服务实例的成功率 service_instance_resp_time= from(ServiceInstance.latency).longAvg();//服务实例的平均响应时间 service_instance_cpm = from(ServiceInstance.*).cpm();//服务实例的每分钟调用次数 // Endpoint scope metrics endpoint_cpm = from(Endpoint.*).cpm();//端点的每分钟调用次数 endpoint_avg = from(Endpoint.latency).longAvg();//端口平均响应时间 endpoint_sla = from(Endpoint.*).percent(status == true);//端点的成功率 endpoint_percentile = from(Endpoint.latency).percentile(10); // Multiple values including p50, p75, p90, p95, p99 // Endpoint relation scope metrics endpoint_relation_cpm = from(EndpointRelation.*).filter(detectPoint == DetectPoint.SERVER).cpm();//在服务端端点检测到的每分钟调用次数 endpoint_relation_resp_time = from(EndpointRelation.rpcLatency).filter(detectPoint == DetectPoint.SERVER).longAvg();//在服务端检测到的rpc调用的平均耗时 endpoint_relation_sla = from(EndpointRelation.*).filter(detectPoint == DetectPoint.SERVER).percent(status == true);//在服务端检测到的请求成功率 endpoint_relation_percentile = from(EndpointRelation.rpcLatency).filter(detectPoint == DetectPoint.SERVER).percentile(10); // Multiple values including p50, p75, p90, p95, p99 database_access_resp_time = from(DatabaseAccess.latency).longAvg();//数据库的处理平均响应时间 database_access_sla = from(DatabaseAccess.*).percent(status == true);//数据库的请求成功率 database_access_cpm = from(DatabaseAccess.*).cpm();//数据库的每分钟调用次数 database_access_percentile = from(DatabaseAccess.latency).percentile(10);
指标告警的设置:
在apache-skywalking-apm-bin/config/alarm-settings.yml文件中
rules:
# 告警规则 名称唯一 必须以_rule 结尾
service_resp_time_rule:
# 度量名称，只支持int long double
metrics-name: service_resp_time
# 操作符
op: ">"
# 阈值 ms
threshold: 1000
# 评估度量的时间长度
period: 10
# 度量有多少次符合告警条件后，才会触发告警
count: 2
# 静默时间 默认情况下，它和周期一样，在同一个周期内只会触发一次。
silence-period: 10
message: 服务【{name}】的平均响应时间在最近10分钟内有2分钟超过1秒
service_sla_rule:
metrics-name: service_sla
op: "<"
threshold: 8000
period: 10
count: 2
silence-period: 10
message: 服务【{name}】的成功率在最近10分钟内有2分钟低于80％
composite-rules:
# 规则名称：在告警信息中显示的唯一名称，必须以_rule结尾
comp_rule:
# 指定如何组成规则，支持&&, ||, ()操作符
expression: service_resp_time_rule && service_sla_rule
message: 服务【{name}】在最近10分钟内有2分钟平均响应时间超过1秒并且成功率低于80％
webhooks:
# - http://127.0.0.1/notify/
# - http://127.0.0.1/go-wechat/