automation-suite
2024.10
true
- Overview
- Requirements
- Pre-installation
- Installation
- Post-installation
- Migration and upgrade
- Upgrading Automation Suite
- Migrating standalone products to Automation Suite
- Step 1: Restoring the standalone product database
- Step 2: Updating the schema of the restored product database
- Step 3: Moving the Identity organization data from standalone to Automation Suite
- Step 4: Backing up the platform database in Automation Suite
- Step 5: Merging organizations in Automation Suite
- Step 6: Updating the migrated product connection strings
- Step 7: Migrating standalone Orchestrator
- Step 8: Migrating standalone Insights
- Step 9: Deleting the default tenant
- Performing a single tenant migration
- Migrating between Automation Suite clusters
- Migrating from Automation Suite on EKS/AKS to Automation Suite on OpenShift
- Monitoring and alerting
- Cluster administration
- Product-specific configuration
- Troubleshooting
- Unable to access Automation Hub following upgrade to Automation Suite 2024.10.0
- AI Center provisioning failure after upgrading to 2023.10 or later
- Insights volumes created in two different zones following migration
- Upgrade fails due to overridden Insights PVC sizes
- The backup setup does not work due to a failure to connect to Azure Government
- Pods in the uipath namespace stuck when enabling custom node taints
- Unable to launch Automation Hub and Apps with proxy setup
- Robot cannot connect to an Automation Suite Orchestrator instance
- Log streaming does not work in proxy setups

Automation Suite on EKS/AKS installation guide
Last updated Sep 2, 2025
AI Center provisioning failure after upgrading to 2023.10 or later
linkDescription
linkWhen upgrading from 2023.4.3 to 2023.10 or later, you might run into issues when provisioning AI Center.
The system shows the following exception, and the tenant creation fails:
"exception":"sun.security.pkcs11.wrapper.PKCS11Exception: CKR_KEY_SIZE_RANGE
Solution
linkTo resolve this issue, you must perform a rollout restart of the
ai-trainer
deployment by running the following command:
kubectl -n <uipath> rollout restart deploy ai-trainer-deployment
kubectl -n <uipath> rollout restart deploy ai-trainer-deployment