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UiPath AI Center

UiPath AI Center

Multi-node requirements and installation

Overview


What you need

Requirements

Configuration

Installation

One Linux machine
(RHEL 8.2 or above)

Multi-node machine requirements

Configuring the machines

Online multi-node installation
Offline multi-node installation

SQL Server
(MS SQL 2016, 2017, 2019 - Enterprise and Standard)

Configuring MS SQL Server

DNS

Configuring the DNS

Load balancer

Configuring the load balancer

Note: If you use a proxy, follow this guide to configure the environment with the proxy: Configuring a proxy server.

Multi-node machine requirements


This is the configuration recommended for production deployments. For multi-node deployments, you need a minimum of three machines and a load balancer.

Bundle

Minimum

Recommended

Node count

At least 3 server nodes. There must be an odd number of server nodes in a cluster to have increased fault tolerance
Any number of agent nodes.

At least 3 server nodes. There must be an odd number of server nodes in a cluster to have increased fault tolerance
Any number of agent nodes.

(v-)CPU total

100 (v-)CPU

104 (v-)CPU

Minimum (v-)CPU per node

12 (v-)CPU

16 (v-)CPU

RAM total

96 GiB

244 GiB

Cluster disk for each node

256 GiB SSD
Min IOPS: 1100

256 GiB SSD
Min IOPS: 1100

Data disk for each server node

2 TiB SSD
Min IOPS 1100

2 TiB SSD
Min IOPS 1100

etcd disk for each server node

16 GiB SSD
Min IOPS: 240

16 GiB SSD
Min IOPS: 240

UiPath Bundle Disk
(For offline installation only, on the first server node)

512 GiB SSD
Min IOPS: 1100

512 GiB SSD
Min IOPS: 1100

Additional agent node with GPU support for Document Understanding

Bundle

Requirement

(v-)CPU

8 (v-)CPU

RAM

52 GiB

Cluster disk

256 GiB SSD
Min IOPS: 1100

Data disk

N/A

GPU RAM

11 GiB

Advanced storage and compute requirements

Use

CPU

RAM (GiB)

GPU

Disk (GiB)

Minimum for serving (ML Skill, one replica)

0.6

2

0

20 OS Disk

Minimum for Training (Pipeline)

1

4

0

20 OS Disk
105 Data Disk

DU model Serving (ML Skill, one replica)

1

4

0

20 OS Disk

DU model Training

2

24

1

20 OS Disk
105 Data Disk

The following table describes the required resources for small and average AI Center implementations. Note that these numbers are general guidance.

Use

CPU

RAM (GiB)

GPU

Disk (GiB)

Small implementation:
3 models served
1 concurrent pipelines

4

32

0

80 OS Disk
200 Data Disk

Average implementation:
5 models served
2 concurrent pipelines
DU model training

8

52

1

150 OS Disk
300 Data Disk

Note: Trainable Document Understanding ML Packages provided by UiPath will work on both CPU or GPU for datasets up to 500 images in size. GPU is strongly recommended to achieve faster training times and better model performance. Validation Station retraining loop is not supported on deployments without a GPU, due to the fact that dataset sizes increase too fast and may hit a compute wall with CPU very quickly. If you run UiPath OCR (non-edge version) on AI Center to process more than 2 million pages of documents a year, GPU is strongly recommended for a better product experience.

Updated 13 days ago

Multi-node requirements and installation


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