automation-suite
2023.4
false
- 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 bucket
- 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
- Pods cannot communicate with FQDN in a proxy environment
- 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
- Exploring Logs
GPU node affected by resource unavailability
Automation Suite on Linux Installation Guide
Last updated Nov 21, 2024
GPU node affected by resource unavailability
When configuring a GPU node in Automation Suite 2023.4.0 or 2023.4.1, you might face issues with resource availability.
To check if the GPU node is affected by this issue, run the following command:
kubectl describe node <GPU>
kubectl describe node <GPU>
If the
Allocatable
resource does not contain nvidia.com/gpu
, as is the case of the following sample, the GPU issue affects you.
Allocatable:
cpu: 5400m
ephemeral-storage: 51938908890
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 113173836Ki
pods: 500
Allocatable:
cpu: 5400m
ephemeral-storage: 51938908890
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 113173836Ki
pods: 500
To fix this issue, run the following command on the GPU node:
awk '1;/plugins."io.containerd.grpc.v1.cri".containerd]/{print " default_runtime_name = \"nvidia\""}' /var/lib/rancher/rke2/agent/etc/containerd/config.toml > /var/lib/rancher/rke2/agent/etc/containerd/config.toml.tmpl
systemctl stop rke2-agent
rke2-killall.sh
systemctl start rke2-agent
awk '1;/plugins."io.containerd.grpc.v1.cri".containerd]/{print " default_runtime_name = \"nvidia\""}' /var/lib/rancher/rke2/agent/etc/containerd/config.toml > /var/lib/rancher/rke2/agent/etc/containerd/config.toml.tmpl
systemctl stop rke2-agent
rke2-killall.sh
systemctl start rke2-agent
To verify if the GPU resource shows up, run the following command:
kubectl describe node <GPU>
kubectl describe node <GPU>
In the following sample, you can see that
nvidia.com/gpu
is present, so the GPU issue no longer occurs.
Allocatable:
cpu: 5400m
ephemeral-storage: 51938908890
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 113173836Ki
nvidia.com/gpu: 1
pods: 500
Allocatable:
cpu: 5400m
ephemeral-storage: 51938908890
hugepages-1Gi: 0
hugepages-2Mi: 0
memory: 113173836Ki
nvidia.com/gpu: 1
pods: 500