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Removes verbose examples from concepts

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Daniel Bodky 2024-02-04 11:41:29 +01:00
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content/en/docs/concepts/workloads/autoscaling.md
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@ -20,33 +20,16 @@ There are manual and automatic ways to scale your workloads, depending on your u
Kubernetes supports _manual scaling_ of workloads, either by changing the number of
{{< glossary_tooltip text="replicas" term_id="replica">}} defined for an object that manages a set of
{{< glossary_tooltip text="Pods" term_id="pod" >}} (for example a {{< glossary_tooltip text="Deployment" term_id="deployment" >}}),
or by adjusting the provided resources of each Replica (for example CPU or memory).
or by adjusting the resource requests and limits of the replicas managed by the workload
(for example CPU or memory):
### Manual changes to replica count
You can use the `kubectl scale` command to increase or decrease the number of replicas for a workload:
```shell
kubectl scale deployment <deployment-name> --replicas=<desired-count>
```
See also this [example of scaling a Deployment](/docs/concepts/workloads/controllers/deployment/#scaling-a-deployment) in the `Deployment` documentation.
### Resizing workloads in-place
Instead of scaling the number of replicas of a workload, you can also adjust the provided resources
for a particular pod or set of pods, in-place. You do this by patching the entries in one or both of the following
fields of the `Pod` or [pod template](/docs/concepts/workloads/pods/#pod-templates) you want to resize:
- `spec.containers[*].resources.requests`
- `spec.containers[*].resources.limits`
- [Running multiple instances of your app](/docs/tutorials/kubernetes-basics/scale/scale-intro/)
- [Resizing CPU and memory resources assigned to containers](/docs/tasks/configure-pod-container/resize-container-resources)
{{< note >}}
Resizing a workload in-place **without** restarting the Pods or its Containers requires Kubernetes version 1.27 or later.
{{< /note >}}
See also this task about [resizing CPU and memory resources](/docs/tasks/configure-pod-container/resize-container-resources) assigned to Containers.
## Scaling workloads automatically
Kubernetes also supports _automatic scaling_ of workloads, which is the focus of this page.