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Incorporate quick wins from first review

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Daniel Bodky 2024-01-31 20:43:29 +01:00
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content/en/docs/concepts/workloads/autoscaling.md
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---
reviewers: []
title: Autoscaling Workloads
description: >-
With Autoscaling, you can automatically update your workloads or infrastructure in one way or another. This allows your cluster to react to changes in resource demand more elastically and efficiently.
With autoscaling, you can automatically update your workloads in one way or another. This allows your cluster to react to changes in resource demand more elastically and efficiently.
content_type: concept
weight: 40
hide_summary: true # Listed separately in section index
---
<!-- overview -->
@ -25,22 +23,20 @@ The first option is referred to as _horizontal scaling_, while the second is ref
<!-- body -->
## Scaling Workloads Horizontally
## Scaling workloads horizontally
In Kubernetes, you can scale a workload horizontally using a _HorizontalPodAutoscaler_ (HPA).
It is implemented as a Kubernetes API resource and a {{< glossary_tooltip text="controller" term_id="controller" >}}
and periodically adjusts the number of {{< glossary_tooltip text="replicas" term_id="replica" >}}
in a workload to match observed resource utilization such as CPU or memory usage.
There is a [walkthrough example](../../../tasks/run-application/horizontal-pod-autoscale-walkthrough.md) of configuring a HorizontalPodAutoscaler for a Deployment.
There is a [walkthrough example](/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough) of configuring a HorizontalPodAutoscaler for a Deployment.
## Scaling Workloads Vertically
## Scaling workloads vertically
_tba_ about VerticalPodAutoscaler
## Scaling the Cluster
_tba_ about Cluster Autoscaler and Karpenter
##
## Advanced Scenarios