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Add explanation for eagerScalingStrategy #1409

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Add explanation for eagerScalingStrategy #1409

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d72e79b
add explanation for eagerScalingStrategy
junekhan Jun 18, 2024
4e974b3
Add illustration
junekhan Jun 27, 2024
1e4ca05
chore: fix typo
junekhan Jun 28, 2024
342a162
Merge branch 'main' into junekhan-patch-2
zroubalik Jul 30, 2024
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7 changes: 6 additions & 1 deletion content/docs/2.15/concepts/scaling-jobs.md
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Expand Up @@ -159,7 +159,7 @@ scalingStrategy:
strategy: "default" # Optional. Default: default. Which Scaling Strategy to use.
```

Select a Scaling Strategy. Possible values are `default`, `custom`, or `accurate`. The default value is `default`.
Select a Scaling Strategy. Possible values are `default`, `custom`, `accurate`, or `eager`. The default value is `default`.

> 💡 **NOTE:**
>
Expand Down Expand Up @@ -230,6 +230,11 @@ if (maxScale + runningJobCount) > maxReplicaCount {
```
For more details, you can refer to [this PR](https://github.com/kedacore/keda/pull/1227).

**eager**
When adopting the **default** strategy, you are likely to come into a subtle case where messages need to be consumed by spawning jobs but remain in the queue, even when there are available slots between `runningJobCount` and `maxReplicaCount`. The **eager** strategy comes to the rescue. It addresses this issue by utilizing all available slots up to the maxReplicaCount, ensuring that waiting messages are processed as quickly as possible.

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To better understand the scenario, you may refer to [this issue](https://github.com/kedacore/keda/issues/5114).

---

```yaml
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