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Automation Suite on EKS/AKS Installation Guide
Last updated Feb 28, 2024

Kubernetes cluster and nodes

Dedicated cluster

You can bring your own Kubernetes cluster from Azure or AWS and follow your standard practices to provision and manage it. Automation Suite requires a dedicated cluster with cluster admin privileges because it deploys the entire UiPath business platform, and it comprises many UiPath products that include many micro-services.

Supported EKS/AKS versions

Each Automation Suite Long-Term Support release comes with a compatibility matrix. For compatible EKS or AKS versions, see Compatibility matrix.

Automation Suite supports the following Linux OSes:

Cloud provider



  • Ubuntu 22.04 and 18.04


  • Amazon Linux 2 for all EKS versions

  • RHEL 8.8 for EKS 1.27

Automation Suite on EKS/AKS only supports the x86 EKS/AKS architecture, and does not support ARM64.

Node capacity

To estimate node capacity based on your product and scale requirements, use the UiPath Automation Suite Install Sizing Calculator.

The root volume requirement for both EKS and AKS agent (worker) nodes is 256 GB.

At a minimum, to start with the mandatory platform services (Identity, licensing, and routing) and Orchestrator, you must provision 8 vCPU and 16 GB RAM per node.


We recommend enabling autoscaling on your cluster to ensure high reliability and to avoid business interruptions.

Additional Task Mining requirements

If you install Task Mining, you must provision additional worker node(s) with 20 vCPU and 60 GB RAM. This node must be tainted to ensure only Task Mining workloads run on it. For details, see the Node scheduling section.

Additional Automation Suite Robots requirements

Automation Suite Robots require additional worker node(s).

The hardware requirements for the Automation Suite Robots node depend on the way you plan to use your resources. In addition to the additional agent node requirements, you also need a minimum of 10 GiB to enable package caching.

For details, see Storage documenation.

The following sections describe the factors that impact the amount of hardware the Automation Suite Robots node requires.

Robot size

The following table describes the required CPU, memory, and storage for all robot sizes.







1 GiB

1 GiB



2 GiB

2 GiB



4 GiB

4 GiB



10 GiB

10 GiB

Agent node size

The resources of the Automation Suite Robots agent node have an impact on the number of jobs that can be run concurrently. The reason is that the number of CPU cores and the amount of RAM capacity are divided by the CPU/memory requirements of the job.

For example, a node with 16 CPUs and 32 GiB of RAM would be able to run any of the following:

  • 32 Small jobs
  • 16 Standard jobs
  • 8 Medium jobs
  • 2 Large jobs

Job sizes can be mixed, so at any given moment, the same node could run a combination of jobs, such as the following:

  • 10 Small jobs (consuming 5 CPUs and 10 GiB of memory)
  • 4 Standard jobs (consuming 4 CPUs and 8 GiB of memory)
  • 3 Medium jobs (consuming 6 CPUs and 12 GiB of memory)

Kubernetes resource consumption

Given that the node is part of a Kubernetes cluster, the Kubernetes agent present on the server (kubelet) consumes a small amount of resources. Based on our measurements, the kubelet consumes the following resources:

  • 0.6 CPU
  • 0.4 GiB RAM

A node similar to the one previously described would actually have approximately 15.4 CPUs and 31.6 GiB of RAM.

Automatic machine size selection

All your cross-platform processes have the Automation Suite Robots option set to Automatic by default. This setting selects the appropriate machine size for running the process using serverless robots.

When automatically choosing the size, the criteria listed in the below table are evaluated in order. As soon as one criterion is satisfied, the corresponding machine size is chosen and the remaining criteria are not evaluated.



Machine size


Remote debugging job



Process depends on UI Automation




Other unattended process


Additional Document Understanding recommendations

For increased performance, you can install Document Understanding on an additional agent node with GPU support. Note, however, that Document Understanding is fully functional without the GPU node. Actually, Document Understanding uses CPU VMs for all its extraction and classification tasks, while for OCR we strongly recommend the usage of a GPU VM. Here you can find more information about the CPU/GPU usage within the Document Understanding framework.

If you want to use an additional node with GPU support, you must meet the following requirements:


Minimum requirement


8 (v-)CPU/cores


52 GiB

Cluster binaries and state disk

256 GiB SSD

Min IOPS: 1100

Data disk



11 GiB

When adding the GPU node pool, it is important that you use --node-taints instead of --node-taints sku=gpu:NoSchedule.

Automation Suite supports NVIDIA GPUs. To learn about how to configure NVDIA GPU (such as drivers), please refer to the respective docs from Azure or AWS.

Node scheduling

We recommend enabling node taints on dedicated worker nodes for Task Mining, Automation Suite Robots, and Document Understanding.

AI Center and DU example:

  • For CPU:

kubectl taint node <node_name> taint node <node_name>

For GPU:

kubectl taint node <node_name> taint node <node_name>

Task Mining example:

kubectl taint node <node_name> task.mining/cpu=present:NoSchedulekubectl taint node <node_name> task.mining/cpu=present:NoSchedule

Automation Suite Robots example:

kubectl taint node <node_name> serverless.robot=present:NoSchedulekubectl taint node <node_name> serverless.robot=present:NoSchedule

If you have custom node taints that are enforced by Gatekeeper Policy, such as specific roles for worker nodes or labels, they will not be passed to Automation Suite and may interrupt the installation process.

To learn about taints and tolerations, see Kubernetes documentation.

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