Monitoring Concepts: Difference between revisions

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=Internal=
=Internal=
* [[Monitoring#Subjects|Monitoring]]
* [[Monitoring#Subjects|Monitoring]]
* [[Monitoring Tools]]
* [[Monitoring Tools]]
=Pooling=
=Pooling=
=Trapping=
=Trapping=
=Observability=
=Observability=
 
{{Internal|Observability Concepts|Observability Concepts}}
The art of understanding the dynamic state of your systems, service and infrastructure. Observability data consists of metrics, traces, logs, metadata, exceptions and even real-time events. Observability analysis leverages machine learning and heuristic techniques to generate insights from data.
 
<font color=darkkhaki>TO PROCESS:
* https://docs.honeycomb.io/getting-started/learning-about-observability/
* https://www.infoq.com/news/2018/06/observability-microservices
* https://blog.takipi.com/system-observability-making-your-production-environment-great-again/
* [[Tracing]]
 
 
Observability
* metrics-based monitoring
* logging (great for debugging)
* tracing
 
 
* https://github.com/OpenObservability/OpenMetrics
 
* https://opentelemetry.io/
</font>
 
=Golden Signals=
=Golden Signals=
{{External|https://www.infoq.com/articles/monitoring-SRE-golden-signals}}
{{External|https://www.infoq.com/articles/monitoring-SRE-golden-signals}}
Rate, errors, latency, saturation and utilization.
Rate, errors, latency, saturation and utilization.
=Metric=
==Aggregated Metrics==
Not all metrics are stored.
==Raw Metrics==
All metrics are stored, so individual events can be identified.
==Examples==
* [[Prometheus_Concepts#Metrics|Prometheus Metrics]]
==Organizatorium==
* https://www.dropwizard.io/en/latest/
* [[Micrometer]]

Latest revision as of 01:36, 6 September 2023

Internal

Pooling

Trapping

Observability

Observability Concepts

Golden Signals

https://www.infoq.com/articles/monitoring-SRE-golden-signals

Rate, errors, latency, saturation and utilization.