- Overview
- Requirements
- Installation
- Post-installation
- Cluster administration
- Monitoring and alerting
- Migration and upgrade
- Product-specific configuration
- Best practices and maintenance
- Troubleshooting
- How to Troubleshoot Services During Installation
- How to Uninstall the Cluster
- How to clean up offline artifacts to improve disk space
- How to disable TLS 1.0 and 1.1
- How to enable Istio logging
- How to manually clean up logs
- How to clean up old logs stored in the sf-logs bundle
- How to debug failed Automation Suite installations
- How to disable TX checksum offloading
- Unable to run an offline installation on RHEL 8.4 OS
- Error in Downloading the Bundle
- Offline installation fails because of missing binary
- Certificate issue in offline installation
- SQL connection string validation error
- Failure After Certificate Update
- Automation Suite Requires Backlog_wait_time to Be Set 1
- Cannot Log in After Migration
- Setting a timeout interval for the management portals
- Update the underlying directory connections
- Kinit: Cannot Find KDC for Realm <AD Domain> While Getting Initial Credentials
- Kinit: Keytab Contains No Suitable Keys for *** While Getting Initial Credentials
- GSSAPI Operation Failed With Error: An Invalid Status Code Was Supplied (Client's Credentials Have Been Revoked).
- Login Failed for User <ADDOMAIN><aduser>. Reason: The Account Is Disabled.
- Alarm Received for Failed Kerberos-tgt-update Job
- SSPI Provider: Server Not Found in Kerberos Database
- Failure to get the sandbox image
- Pods not showing in ArgoCD UI
- Redis Probe Failure
- RKE2 Server Fails to Start
- Secret Not Found in UiPath Namespace
- ArgoCD goes into progressing state after first installation
- Unexpected Inconsistency; Run Fsck Manually
- Missing Self-heal-operator and Sf-k8-utils Repo
- Degraded MongoDB or Business Applications After Cluster Restore
- Unhealthy Services After Cluster Restore or Rollback
- Using the Automation Suite Diagnostics Tool
- Using the Automation Suite Support Bundle Tool
- Exploring Logs
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.
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 (GiB) |
GPU |
Disk (GiB) |
|---|---|---|---|---|
|
Minimum for serving (ML Skill, one replica) |
0.6 |
2 |
0 |
|
|
Minimum for Training (Pipeline) |
1 |
4 |
0 |
|
|
DU model Serving (ML Skill, one replica) |
1 |
4 |
0 |
|
|
DU model Training |
2 |
24 |
Strongly recommended |
|
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 (GiB) |
GPU |
Disk (GiB) |
|---|---|---|---|---|
|
Small implementation:
|
4 |
32 |
0 |
|
|
Average implementation:
|
8 |
52 |
Strongly recommended |
|
rancher partition = 80 GiB on the rancher partition
2 1 pipeline * 105GB = 105 Data disk
rancher partition = 160 GiB on the rancher partition
4 (2 pipeline + 1 DU pipeline) * 105GB = 315 Data disk
