Measuring Service Saturation

Saturation is a representation of how full your service is, and is one of The Four Golden Signals of MonitoringThe Four Golden Signals of Monitoring
The four golden signals of [[Monitoring]] are:

Measuring Request LatencyMeasuring Request Latency
Latency is the time taken to serve a request, and is one of [[The Four Golden Signals of Monitoring]].

The most common metric looked at here is usually the [[Mean]] latency, but this can easily be...

[[Measuring Traffic]]
[[Measuring Error Rate]]
[[Measuring Service Saturation]]




Status: #🌲

References:

...
.

When thinking about saturation, it's useful to put the emphasis on the most constrained resource for your application – If memory is our biggest constraint, our dashboards should show our service's memory usage.

Saturation is useful because performance degradation often starts before saturation reaches 100%, so it's important to define a utilization target which you'd like to follow.

Increases in Measuring Request LatencyMeasuring Request Latency
Latency is the time taken to serve a request, and is one of [[The Four Golden Signals of Monitoring]].

The most common metric looked at here is usually the [[Mean]] latency, but this can easily be...
are frequently leading indicators of high saturation, so it's good to supplement Saturation metrics with high-level latency metrics.

Saturation also cares about things like "your hard drive will be full in 4h".

It's critical to note that Saturation almost always falls under Cause Based MonitoringCause Based Monitoring
Cause Based [[Monitoring]] points us to a cause of an existing issue, but don't imply that issue exists in the first place. Some examples of Cause Metrics are:

CPU utilization
Free disk space
...
, so make sure not to rely on it too hard when setting up Alerting.


Status: #💡

References: