Monitoring Concepts: Difference between revisions
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=Observability= | =Observability= | ||
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: | <font color=darkkhaki>TO PROCESS: |
Revision as of 18:13, 17 August 2023
Internal
Pooling
Trapping
Observability
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.
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
Golden Signals
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.