- Overview
- Requirements
- Installation
- Q&A: Deployment templates
- Configuring the machines
- Configuring the external objectstore
- Configuring an external Docker registry
- Configuring the load balancer
- Configuring the DNS
- Configuring Microsoft SQL Server
- Configuring the certificates
- Online multi-node HA-ready production installation
- Offline multi-node HA-ready production installation
- Disaster recovery - Installing the secondary cluster
- Downloading the installation packages
- install-uipath.sh parameters
- Enabling Redis High Availability Add-On for the cluster
- Document Understanding configuration file
- Adding a dedicated agent node with GPU support
- Adding a dedicated agent Node for Task Mining
- Connecting Task Mining application
- Adding a Dedicated Agent Node for Automation Suite Robots
- Post-installation
- Cluster administration
- Monitoring and alerting
- Migration and upgrade
- Migration options
- Step 1: Moving the Identity organization data from standalone to Automation Suite
- Step 2: Restoring the standalone product database
- Step 3: Backing up the platform database in Automation Suite
- Step 4: Merging organizations in Automation Suite
- Step 5: Updating the migrated product connection strings
- Step 6: Migrating standalone Insights
- Step 7: Deleting the default tenant
- B) Single tenant migration
- 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 clear Redis data
- 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 disable streaming logs for AI Center
- How to debug failed Automation Suite installations
- How to delete images from the old installer after upgrade
- How to automatically clean up Longhorn snapshots
- How to disable TX checksum offloading
- How to manually set the ArgoCD log level to Info
- How to generate the encoded pull_secret_value for external registries
- How to address weak ciphers in TLS 1.2
- 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
- First installation fails during Longhorn setup
- SQL connection string validation error
- Prerequisite check for selinux iscsid module fails
- Azure disk not marked as SSD
- Failure after certificate update
- Antivirus causes installation issues
- Automation Suite not working after OS upgrade
- Automation Suite requires backlog_wait_time to be set to 0
- GPU node affected by resource unavailability
- Volume unable to mount due to not being ready for workloads
- Support bundle log collection failure
- Failure to upload or download data in objectstore
- PVC resize does not heal Ceph
- Failure to resize PVC
- Failure to resize objectstore PVC
- Rook Ceph or Looker pod stuck in Init state
- StatefulSet volume attachment error
- Failure to create persistent volumes
- Storage reclamation patch
- Backup failed due to TooManySnapshots error
- All Longhorn replicas are faulted
- Setting a timeout interval for the management portals
- Update the underlying directory connections
- Authentication not working after migration
- 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 due to invalid status code
- Alarm received for failed Kerberos-tgt-update job
- SSPI provider: Server not found in Kerberos database
- Login failed for AD user due to disabled account
- ArgoCD login failed
- 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
- Issues accessing the ArgoCD read-only account
- MongoDB pods in CrashLoopBackOff or pending PVC provisioning after deletion
- Unhealthy services after cluster restore or rollback
- Pods stuck in Init:0/X
- Prometheus in CrashloopBackoff state with out-of-memory (OOM) error
- Missing Ceph-rook metrics from monitoring dashboards
- Running High Availability with Process Mining
- Process Mining ingestion failed when logged in using Kerberos
- Unable to connect to AutomationSuite_ProcessMining_Warehouse database using a pyodbc format connection string
- Airflow installation fails with sqlalchemy.exc.ArgumentError: Could not parse rfc1738 URL from string ''
- How to add an IP table rule to use SQL Server port 1433
- Using the Automation Suite Diagnostics Tool
- Using the Automation Suite Support Bundle Tool
- Exploring Logs
Removing a node from the cluster
After installing Automation Suite, you can remove any node from the cluster for machine maintenance purposes or to release unused resources. You can remove server, agent, Task Mining, and GPU nodes from the cluster.
Removing a node from the cluster is possible only on multi-node HA-ready production setups.
Removing nodes from the cluster does not cause any downtime. However, it can still affect the internal caching component if HAA is not configured.
The removal of the Task Mining or GPU node will not wait for already scheduled jobs, such as training pipeline or analysis. If these jobs are deleted in the process of node removal, you need to start afresh. Make sure that no processes are running on the nodes you plan to remove.
Performing the following steps would only result in the nodes being removed from the cluster. The machine will not be wiped completely, and some residues could render it unusable for further installation.
Make sure you format the machine and prepare it for installation or for adding it to an existing cluster by following the instructions in Configuring the machines.
To successfully remove a node from the cluster, you must meet the following requirements:
- The capacity of the resultant cluster must match the total required capacity to run the workloads scheduled before the node removal. For example, if total workloads require 32 vCPU and 64 GiB memory, then after the node removal, the remaining nodes in the cluster should have at least the same amount of resources. Otherwise, you will not be allowed to remove the nodes.
- The resultant cluster must have a minimum of 3 server nodes; an odd number of server nodes is also required.
- If the setup is multizonal, the resultant cluster must have server nodes in each of the 3 zones.
- The cluster must be in a healthy state, i.e., all the nodes or pods are healthy. Pods are unhealthy when they are in any of
the following states:
Pending
,Error
,Init
,Crashloopbackoff
,Terminating
. - You cannot remove Task Mining and GPU nodes unless additional corresponding Task Mining and GPU nodes are available.
To remove a node from the cluster, take the following steps:
The script warns you to shut down or terminate the node; it does not delete the node from the cluster until you shut down the node. The script waits for 5 minutes for the node to be shut down before timing out. The script provides instructions on which node to shut down and in what order. You can also rerun the script if you have not shut down the node in the requested time.
To automate the entire node removal process, take the following steps:
- Add the
--skip-node-deletion
flag at the end of the script in step 3. - Once the script is succeeded, shut down the first target node and then rerun the script, this time without
--skip-node-deletion
. If you have not shut down the node in the order provided to the script, then it will fail. You can always rerun the script, once the expected node is shut down. - Repeat the previous step until all the nodes are removed successfully.
To get the name of the nodes to remove, see How to get the node name.