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Automation Suite on Linux installation guide

Last updated Apr 29, 2025

AI Center considerations

On top of the core service requirements that are part of full platform requirements, AI Center requires additional resources, depending on the models that you want to run or train. For more details about the required GPU hardware generations and compatible NVIDIA drivers, refer to Compatibility Matrix.

Note: The following table describes the additional resources AI Center needs.

In this table, Data Disk is needed on all server nodes. This is not needed on agent nodes.

Use

CPU

RAM (GB)

GPU

Disk (GB)

Minimum for serving (ML Skill, one replica)

0.6

2

0

  • 20 GB on the rancher partition

Minimum for Training (Pipeline)

1

4

0

  • 20 GB on the rancher partition
  • Minimum 51 GB AI Center disk partition(recommended 105 GB)

DU model Serving (ML Skill, one replica)

1

4

0

  • 20 GB on the rancher partition

DU model Training

2

24

Strongly recommended

  • 20 GB on the rancher partition
  • Minimum 51 GB Data Disk (recommended 105 GB)
Note: The following table describes the required resources for small and average AI Center implementations. Note that these numbers are general guidance.

In this table, Data Disk is needed on all server nodes. This is not needed on agent nodes.

Use

CPU

RAM (GB)

GPU

Disk (GB)

Small implementation:

  • 3 models served
  • 1 concurrent pipelines

4

32

0

  • 80 GB on the rancher partition1
  • 105 Data Disk 2

Average implementation:

  • 5 models served
  • 2 concurrent pipelines
  • DU model training

8

52

Strongly recommended

  • 160 GB on the rancher partition3
  • 315 Data Disk 4
1 (3 skills +1 pipeline) * 20 GB on the rancher partition = 80 GB on the rancher partition

2 1 pipeline * 105GB = 105 Data disk

3 (5 skills + 2 pipeline + 1 DU pipeline) * 20 GB on the rancher partition = 160 GB on the rancher partition

4 (2 pipeline + 1 DU pipeline) * 105GB = 315 Data disk

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