Prometheus Deep Dive - Monitoring. At scale.@TwitchiH & @fredbrancz Prometheus Deep Dive Introduction Intro 2.0 to 2.2.1 2.4 - 2.6 Beyond Outro Main selling points Highly dynamic, built-in service discovery No hierarchical model, n-dimensional label to 2.2.1 2.4 - 2.6 Beyond Outro Three main features Storage backend Caveat: Prometheus 2.0 comes with storage v3 Staleness handling Remote read & write API is now stable-ish Links to in-depth talks to 2.2.1 2.4 - 2.6 Beyond Outro Remote read API Playing nicely with others We now have a stable-ish remote read/write API Twelve integrations for this API Ongoing work to send write-ahead-log over the0 码力 | 34 页 | 370.20 KB | 1 年前3
Intro to Prometheus - With a dash of operations & observability@TwitchiH & @fredbrancz Intro to Prometheus Introduction Background Operations & observability Outro Main selling points Highly dynamic, built-in service discovery No hierarchical model, n-dimensional label (How much time does this subroutine take?) Every service should have its own metrics endpoint Hard API commitments within major versions No built-in TLS yet, use reverse proxies for now Richard Hartmann0 码力 | 19 页 | 63.73 KB | 1 年前3
B站统⼀监控系统的设计,演进
与实践分享prometheus target target target alert_manager 告警平 服务 cache db平台 rms资 外围系统 监控⽬目 规则⽣生 告警规 api 规则管理理 获取监控⽬目标 IDC_1 agent prometheus target target target IDC_2 获取 监控⽬目标 告警规则 web push rule prometheus target target target alert_manager 告警平 服务 cache db平台 rms资 外围系统 监控⽬目 规则⽣生 告警规 api 规则管理理 获取监控⽬目标 IDC_1 agent prometheus target target target IDC_2 获取 监控⽬目标 告警规则 web push rule prometheus target target target alert_manager 告警平 服务 cache db平台 rms资 外围系统 监控⽬目 规则⽣生 告警规 api 规则管理理 获取监控⽬目标 IDC_1 agent prometheus target target target IDC_2 获取 监控⽬目标 告警规则 web push rule0 码力 | 34 页 | 650.25 KB | 1 年前3
OpenMetrics - Standing on the shoulders of Titansorg, @TwitchiH OpenMetrics Introduction Quick intro OpenMetrics Outro People Acknowledgements Main work has been done by Prometheus team Ben Kochie Brian Brazil myself Google Sumeer Bhola Uber0 码力 | 21 页 | 84.83 KB | 1 年前3
1.6 利用夜莺扩展能力打造全方位监控系统夜莺数据采集 06. Serializer 夜莺数据采集 07. Forwarder 夜莺设计实现 Server 数据处理 第五部分 夜莺Server数据处理 01. 服务器 02. API 夜莺Server数据处理 03. AlarmRule Control 夜莺Server数据处理 04. CollectRule Control 夜莺Server数据处理 04. CollectRule0 码力 | 40 页 | 3.85 MB | 1 年前3
PromQL 从入门到精通histogram_quantile 函数的用法,首先得了解 Histogram 类型的数据。Histogram 翻 译过来是柱状图,设计这个数据类型,是为了描述响应延时的情况。 比如接口:/api/v1/query,如何度量这个接口的健康状况?最核心有两个指标,一个是成功 率,一个是延迟,成功率的计算代价比较小,只需要为每个请求指标打上 statuscode 的标签即 可,然后可以求取非0 码力 | 16 页 | 2.77 MB | 1 年前3
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