加强服务保障 满足群众急需需求,遵义做网站优化,网站做营销推广公司,毕设做桌面端还是网站参数
全局指标
指标指标名称all_p99所有服务响应时间的 p99 值all_p95所有服务响应时间的 p95 值all_p90所有服务响应时间的 p90 值all_p75所有服务响应时间的 p75 值all_p70所有服务响应时间的 p70 值all_heatmap所有服务响应时间的热点图
服务指标
指标指标名称service_r…参数
全局指标
指标指标名称all_p99所有服务响应时间的 p99 值all_p95所有服务响应时间的 p95 值all_p90所有服务响应时间的 p90 值all_p75所有服务响应时间的 p75 值all_p70所有服务响应时间的 p70 值all_heatmap所有服务响应时间的热点图
服务指标
指标指标名称service_resp_time服务的平均响应时间service_sla服务的成功率service_p99服务响应时间的 p99 值service_p95服务响应时间的 p95 值service_p90服务响应时间的 p90 值service_p75服务响应时间的 p75 值service_p50服务响应时间的 p50 值
服务实例指标
指标指标名称service_instance_sla服务实例的成功率service_instance_resp_time服务实例的平均响应时间service_instance_cpm服务实例每分钟调⽤次数
端点指标
指标指标名称endpoint_cpm端点每分钟调⽤次数endpoint_avg,端点平均响应时间endpoint_sla,端点成功率endpoint_p99端点响应时间的 p99 值endpoint_p95endpoint_p90endpoint_p75endpoint_p50
JVM指标
指标指标名称instance_jvm_cpuinstance_jvm_memory_heapinstance_jvm_memory_noheapinstance_jvm_memory_heap_maxinstance_jvm_memory_noheap_maxinstance_jvm_young_gc_timeinstance_jvm_old_gc_time
服务关系指标
指标指标名称service_relation_client_cpm在客户端每分钟检测到的调⽤次数service_relation_server_cpm在服务端每分钟检测到的调⽤次数service_relation_client_call_sla在客户端检测到的成功率service_relation_server_call_sla在服务端检测到的成功率service_relation_client_resp_time在客户端检测到的平均响应时间service_relation_server_resp_time在服务端检测到的平均响应时间service_relation_client_cpm在客户端每分钟检测到的调⽤次数service_relation_server_cpm在服务端每分钟检测到的调⽤次数
端点关系指标
指标指标名称endpoint_relation_cpmendpoint_relation_resp_time
其他关键指标
指标指标名称CPM每分钟请求调⽤的次数SLA⽹站服务可⽤性主要是通过请求成功与失败次数来计算9越多代表全年服务可⽤时间越长服务更可靠停机 时间越短CLR(公共语⾔运⾏库在运⾏期管理程序的执⾏主要包含内存管理、代码安全验证、代码执⾏、垃圾收集。CLR 有⼀项服务称为GCGarbage Collector垃圾收集它能为你⾃动管理内存。GC⾃动从内存中删除程序不再访问的 对象GC是程序员不再操⼼许多以前必须执⾏的任务⽐如释放内存和检查内存泄漏。百分位数skywalking中有P50P90P95这种统计⼝径就是百分位数的概念
内置方法参数
以下内容都是出自SkyWalking官方git
service_resp_time from(Service.latency).longAvg();
service_sla from(Service.*).percent(status true);
service_cpm from(Service.*).cpm();
service_percentile from(Service.latency).percentile(10); // Multiple values including p50, p75, p90, p95, p99
service_apdex from(Service.latency).apdex(name, status);
service_mq_consume_count from(Service.*).filter(type RequestType.MQ).count();
service_mq_consume_latency from((str-long)Service.tag[transmission.latency]).filter(type RequestType.MQ).filter(tag[transmission.latency] ! null).longAvg();// Service relation scope metrics for topology
service_relation_client_cpm from(ServiceRelation.*).filter(detectPoint DetectPoint.CLIENT).cpm();
service_relation_server_cpm from(ServiceRelation.*).filter(detectPoint DetectPoint.SERVER).cpm();
service_relation_client_call_sla from(ServiceRelation.*).filter(detectPoint DetectPoint.CLIENT).percent(status true);
service_relation_server_call_sla from(ServiceRelation.*).filter(detectPoint DetectPoint.SERVER).percent(status true);
service_relation_client_resp_time from(ServiceRelation.latency).filter(detectPoint DetectPoint.CLIENT).longAvg();
service_relation_server_resp_time from(ServiceRelation.latency).filter(detectPoint DetectPoint.SERVER).longAvg();
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
service_instance_relation_client_cpm from(ServiceInstanceRelation.*).filter(detectPoint DetectPoint.CLIENT).cpm();
service_instance_relation_server_cpm from(ServiceInstanceRelation.*).filter(detectPoint DetectPoint.SERVER).cpm();
service_instance_relation_client_call_sla from(ServiceInstanceRelation.*).filter(detectPoint DetectPoint.CLIENT).percent(status true);
service_instance_relation_server_call_sla from(ServiceInstanceRelation.*).filter(detectPoint DetectPoint.SERVER).percent(status true);
service_instance_relation_client_resp_time from(ServiceInstanceRelation.latency).filter(detectPoint DetectPoint.CLIENT).longAvg();
service_instance_relation_server_resp_time from(ServiceInstanceRelation.latency).filter(detectPoint DetectPoint.SERVER).longAvg();
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);
service_instance_resp_time from(ServiceInstance.latency).longAvg();
service_instance_cpm from(ServiceInstance.*).cpm();// Endpoint scope metrics
endpoint_cpm from(Endpoint.*).cpm();
endpoint_resp_time from(Endpoint.latency).longAvg();
endpoint_sla from(Endpoint.*).percent(status true);
endpoint_percentile from(Endpoint.latency).percentile(10); // Multiple values including p50, p75, p90, p95, p99
endpoint_mq_consume_latency from((str-long)Endpoint.tag[transmission.latency]).filter(type RequestType.MQ).filter(tag[transmission.latency] ! null).longAvg();// Endpoint relation scope metrics
endpoint_relation_cpm from(EndpointRelation.*).filter(detectPoint DetectPoint.SERVER).cpm();
endpoint_relation_resp_time from(EndpointRelation.rpcLatency).filter(detectPoint DetectPoint.SERVER).longAvg();
endpoint_relation_sla from(EndpointRelation.*).filter(detectPoint DetectPoint.SERVER).percent(status true);
endpoint_relation_percentile from(EndpointRelation.rpcLatency).filter(detectPoint DetectPoint.SERVER).percentile(10); // Multiple values including p50, p75, p90, p95, p99database_access_resp_time from(DatabaseAccess.latency).longAvg();
database_access_sla from(DatabaseAccess.*).percent(status true);
database_access_cpm from(DatabaseAccess.*).cpm();
database_access_percentile from(DatabaseAccess.latency).percentile(10);cache_read_resp_time from(CacheAccess.latency).filter(operation VirtualCacheOperation.Read).longAvg();
cache_read_sla from(CacheAccess.*).filter(operation VirtualCacheOperation.Read).percent(status true);
cache_read_cpm from(CacheAccess.*).filter(operation VirtualCacheOperation.Read).cpm();
cache_read_percentile from(CacheAccess.latency).filter(operation VirtualCacheOperation.Read).percentile(10);cache_write_resp_time from(CacheAccess.latency).filter(operation VirtualCacheOperation.Write).longAvg();
cache_write_sla from(CacheAccess.*).filter(operation VirtualCacheOperation.Write).percent(status true);
cache_write_cpm from(CacheAccess.*).filter(operation VirtualCacheOperation.Write).cpm();
cache_write_percentile from(CacheAccess.latency).filter(operation VirtualCacheOperation.Write).percentile(10);cache_access_resp_time from(CacheAccess.latency).longAvg();
cache_access_sla from(CacheAccess.*).percent(status true);
cache_access_cpm from(CacheAccess.*).cpm();
cache_access_percentile from(CacheAccess.latency).percentile(10);mq_service_consume_cpm from(MQAccess.*).filter(operation MQOperation.Consume).cpm();
mq_service_consume_sla from(MQAccess.*).filter(operation MQOperation.Consume).percent(status true);
mq_service_consume_latency from(MQAccess.transmissionLatency).filter(operation MQOperation.Consume).longAvg();
mq_service_consume_percentile from(MQAccess.transmissionLatency).filter(operation MQOperation.Consume).percentile(10);
mq_service_produce_cpm from(MQAccess.*).filter(operation MQOperation.Produce).cpm();
mq_service_produce_sla from(MQAccess.*).filter(operation MQOperation.Produce).percent(status true);mq_endpoint_consume_cpm from(MQEndpointAccess.*).filter(operation MQOperation.Consume).cpm();
mq_endpoint_consume_latency from(MQEndpointAccess.transmissionLatency).filter(operation MQOperation.Consume).longAvg();
mq_endpoint_consume_percentile from(MQEndpointAccess.transmissionLatency).filter(operation MQOperation.Consume).percentile(10);
mq_endpoint_consume_sla from(MQEndpointAccess.*).filter(operation MQOperation.Consume).percent(status true);
mq_endpoint_produce_cpm from(MQEndpointAccess.*).filter(operation MQOperation.Produce).cpm();
mq_endpoint_produce_sla from(MQEndpointAccess.*).filter(operation MQOperation.Produce).percent(status true);titles
{// General Servicegeneral_service: 常规服务,general_service_desc: 通过从SkyWalking代理收集的遥测数据来观察服务和相对直接的依赖关系。,general_service_services: 服务,general_service_services_desc: 通过SkyWalking Agent收集的遥测数据观察服务。,general_service_virtual_database: 虚拟数据库,general_service_virtual_database_desc: 观察语言代理通过各种插件推测的虚拟数据库。,general_service_virtual_cache: 虚拟缓存,general_service_virtual_cache_desc: 观察语言代理通过各种插件推测的虚拟缓存服务器。,general_service_virtual_mq: 虚拟消息队列,general_service_virtual_mq_desc: 观察语言代理通过各种插件推测的虚拟消息队列服务器。,// Service Meshservice_mesh: 服务网格,service_mesh_desc: 服务网格Istio通过分布式或微服务架构解决了开发人员和运营商面临的挑战。,service_mesh_service: 服务,service_mesh_service_desc: 通过从Envoy访问日志服务ALS收集的遥测数据观察服务网格。,service_mesh_control_plane: 控制平面,service_mesh_control_plane_desc: 通过Istio的自我监控指标提供对其行为的监控。,service_mesh_data_plane: 数据平面,service_mesh_data_plane_desc: 通过Envoy Metrics Service观察Envoy Proxy。,// Functionsfunctions: Functions,functions_desc:FaaS功能即服务是一种云计算服务允许您在没有通常与构建和启动微服务应用程序相关的复杂基础设施的情况下执行代码以响应事件。,functions_openfunction: OpenFunction,functions_openfunction_desc: OpenFunction作为一个FaaS平台通过SkyWalking集成提供开箱即用的可观察性。,// Kuberneteskubernetes: Kubernetes,kubernetes_desc: Kubernetes是一个开源的容器编排系统用于自动化软件部署、扩展和管理。,kubernetes_cluster: 集群,kubernetes_cluster_desc: 提供对K8S集群的状态和资源的监控。,kubernetes_service: 服务,kubernetes_service_desc: 从Kubernetes中观察服务状态和资源。,// Infrastructureinfrastructure: 基础设施,infrastructure_desc: 操作系统是整个IT系统的基础设施。它的可观察性为所有分布式和现代复杂系统的运行提供了基础。,infrastructure_linux: Linux,infrastructure_linux_desc: 提供Linux操作系统OS监控。,infrastructure_windows: Windows,infrastructure_windows_desc: 提供Windows操作系统OS监控。,// AWS Cloudaws_cloud: AWS云服务,aws_cloud_desc: 亚马逊网络服务AWS提供可靠、可扩展且价格低廉的云计算服务。,aws_cloud_eks: EKS,aws_cloud_eks_desc: 通过AWS Container Insights Receiver提供AWS Cloud EKS监控。,aws_cloud_s3: S3,aws_cloud_s3_desc: 通过AWS FireHose Receiver提供AWS Cloud S3监控,aws_cloud_dynamodb: DynamoDB,aws_cloud_dynamodb_desc: 通过AWS FireHose Receiver提供DynamoDB监控。,aws_cloud_api_gateway: API Gateway,aws_cloud_api_gateway_desc: 通过AWS FireHose Receiver提供AWS Cloud API网关监控。,// Browserbrowser: Browser,browser_desc: 通过Apache SkyWalking Client JS提供Web应用程序、版本和页面的浏览器端监控。,// Gatewaygateway: 网关,gateway_desc: API网关是位于客户端和后端服务集合之间的API管理工具。,gateway_apisix: APISIX,gateway_apisix_desc: 通过OpenTelemetry的Prometheus接收器提供APISIX监控。,gateway_aws_api_gateway: AWS API Gateway,gateway_aws_api_gateway_desc: 通过AWS FireHose Receiver提供AWS Cloud API网关监控。,// Databasedatabase: 数据库,database_desc: 数据库是结构化信息或数据的有组织的集合通常以电子方式存储在计算机系统中。,database_mysql_mariadb: MySQL/MariaDB,database_mysql_mariadb_desc: 通过OpenTelemetry的Prometheus接收器提供MySQL和MariaDB服务器监控。,database_postgresql: PostgreSQL,database_postgresql_desc: 通过OpenTelemetry的Prometheus接收器提供PostgreSQL监控。,database_dynamodb: DynamoDB,database_dynamodb_desc: 通过AWS FireHose Receiver提供DynamoDB监控。,database_redis: Redis,database_redis_desc: 通过OpenTelemetry的Prometheus接收器提供Redis监控。,database_elasticsearch: Elasticsearch,database_elasticsearch_desc: 通过OpenTelemetry的Prometheus接收器提供Elasticsearch服务器监控。,database_mongodb: MongoDB,database_mongodb_desc: 通过OpenTelemetry的Prometheus接收器提供MongoDB监控。,// Message Queuemq: 消息队列,mq_desc: 消息队列是无服务器和微服务架构中使用的异步服务对服务通信的一种形式。,mq_rabbitmq: RabbitMQ,mq_rabbitmq_desc: 通过OpenTelemetry的Prometheus接收器提供RabbitMQ监控。,// self observabilityself_observability: 自监控,self_observability_desc: 自观察性为运行SkyWalking生态系统中的组件和服务器提供了可观察性。,self_observability_oap: SkyWalking服务,self_observability_oap_desc: OAP后端集群本身是一个分布式流处理系统这是对OAP后端本身的监控。,self_observability_satellite: Satellite,self_observability_satellite_desc:Satellite为云原生基础设施设计的开源代理提供了一种低成本、高效、更安全的遥测数据收集方式。它是遥测采集的推荐负载均衡器。,
}
