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= Defining cluster size requirements for an {ServerlessProductName} installation
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To install and use {ServerlessProductName}, the {product-title} cluster must be sized correctly.
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The minimum requirement for {ServerlessProductName} is a cluster with 10 CPUs and 40GB memory.
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The total size requirements to run {ServerlessProductName} are dependent on the applications deployed. By default, each pod requests approximately 400m of CPU, so the minimum requirements are based on this value.
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In the size requirement provided, an application can scale up to 10 replicas. Lowering the actual CPU request of applications can increase the number of possible replicas.
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[NOTE]
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The requirements provided relate only to the pool of worker machines of the {product-title} cluster. Master nodes are not used for general scheduling and are omitted from the requirements.
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[NOTE]
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The following limitations apply to all {ServerlessProductName} deployments:
Copy file name to clipboardExpand all lines: serverless/installing_serverless/installing-openshift-serverless.adoc
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@@ -13,46 +13,27 @@ This guide walks cluster administrators through installing the {ServerlessOperat
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{ServerlessProductName} is supported for installation in a restricted network environment. For more information, see xref:../../operators/admin/olm-restricted-networks.adoc#olm-restricted-networks[Using Operator Lifecycle Manager on restricted networks].
To run {ServerlessProductName}, the {product-title} cluster must be sized correctly.
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The minimum requirement to use {ServerlessProductName} is a cluster with 10 CPUs and 40GB memory.
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The total size requirements to run {ServerlessProductName} are dependent on the applications deployed. By default, each pod requests ~400m of CPU, so the minimum requirements are based on this value.
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In the size requirement provided, an application can scale up to 10 replicas. Lowering the actual CPU request of applications can increase the number of possible replicas.
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You can use the MachineSet API to manually scale your cluster up to the desired size. The minimum requirements usually mean that you must scale up one of the default MachineSets by two additional machines.
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For more information on using the MachineSet API, see the documentation on xref:../../machine_management/creating_machinesets/creating-machineset-aws.adoc#creating-machineset-aws[Creating MachineSets].
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For more information on scaling a MachineSet manually, see the documentation on xref:../../machine_management/manually-scaling-machineset.adoc#manually-scaling-machineset[manually scaling MachineSets].
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[NOTE]
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The requirements provided relate only to the pool of worker machines of the {product-title} cluster. Master nodes are not used for general scheduling and are omitted from the requirements.
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[IMPORTANT]
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[NOTE]
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Before upgrading to the latest Serverless release, you must remove the community Knative Eventing Operator if you have previously installed it. Having the Knative Eventing Operator installed will prevent you from being able to install the latest version of Knative Eventing using the {ServerlessOperatorName}.
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The following limitations apply to all {ServerlessProductName} deployments:
For more advanced use-cases such as logging or metering on {product-title}, you must deploy more resources. Recommended requirements for such use-cases are 24 CPUs and 96GB of memory.
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For more advanced usecases such as logging or metering on {product-title}, you must deploy more resources. Recommended requirements for such usecases are 24 CPUs and 96GB of memory.
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If you have high availability (HA) enabled on your cluster, this requires between 0.5 - 1.5 cores and between 200MB - 2GB of memory for each replica of the Knative Serving control plane.
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HA is enabled for some Knative Serving components by default. You can disable HA by following the documentation on xref:../../serverless/serverless-HA.adoc#serverless-HA[Configuring high availability replicas on {ServerlessProductName}].
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[IMPORTANT]
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Before upgrading to the latest Serverless release, you must remove the community Knative Eventing Operator if you have previously installed it. Having the Knative Eventing Operator installed will prevent you from being able to install the latest version of Knative Eventing using the {ServerlessOperatorName}.
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