 Intro to Prometheus - With a dash of operations & observabilityIntroduction Background Operations & observability Outro Main selling points Highly dynamic, built-in service discovery No hierarchical model, n-dimensional label set PromQL: for processing, graphing, alerting Looking at a service from the outside (Does the server answer to HTTP requests?) White-box monitoring: Instrumention code from the inside (How much time does this subroutine take?) Every service should have Outro Toil ”Toil is manual, repeated work with no lasting benefit which scales linearly with your service” If teams are busy firefighting, they don’t have time to engineer Keep legacy systems working,0 码力 | 19 页 | 63.73 KB | 1 年前3 Intro to Prometheus - With a dash of operations & observabilityIntroduction Background Operations & observability Outro Main selling points Highly dynamic, built-in service discovery No hierarchical model, n-dimensional label set PromQL: for processing, graphing, alerting Looking at a service from the outside (Does the server answer to HTTP requests?) White-box monitoring: Instrumention code from the inside (How much time does this subroutine take?) Every service should have Outro Toil ”Toil is manual, repeated work with no lasting benefit which scales linearly with your service” If teams are busy firefighting, they don’t have time to engineer Keep legacy systems working,0 码力 | 19 页 | 63.73 KB | 1 年前3
 Prometheus Deep Dive - Monitoring. At scale.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 set PromQL: for processing, graphing, alerting0 码力 | 34 页 | 370.20 KB | 1 年前3 Prometheus Deep Dive - Monitoring. At scale.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 set PromQL: for processing, graphing, alerting0 码力 | 34 页 | 370.20 KB | 1 年前3
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