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docs: explain autoscaler target-value strategy (#14951) 

Provide more technical details about how the `target-value` strategy
calculates new scaling actions.
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Luiz Aoqui 2022-10-19 14:16:17 -04:00 committed by GitHub
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website/content/tools/autoscaling/plugins/strategy/target-value.mdx
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@ -6,9 +6,36 @@ description: The "target-value" strategy plugin tracks a target metric value.
# Target Value Strategy Plugin
The `target-value` strategy plugin will perform count calculations in order to
The `target-value` strategy plugin performs count calculations in order to
keep the value resulting from the APM query at or around a specified target.
It accomplishes this by extrapolating the current metric value and used
capacity linearly to determine if a scaling action is required and how many
instances need to be added or removed. More specify, the new scaling value is
calculated as:
```
new_count = (current_metric_value / target) * current_count
```
As an example, a policy that tracks memory usage with target defined as `70`
(representing 70% of memory usage) and there are `10` instances running will
generate a scaling action to add `2` new instances when the metric reaches `80`
(80% of memory usage) because:
```
new_count = (80/70) * 10 = 11.43 ~= 12
```
In other words, if with 10 instances the memory usage in 80%, it's expected
that with 12 instances the memory usage is lower and closer to the target value
of 70%.
~> **Note:** In some situations this inverse relationship may not be true,
meaning that _more_ instances causes the metric value to _grow_. Make sure
you have a good grasp of your query result dynamic when the number of
instances changes.
## Agent Configuration Options
```hcl