- 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
Evaluating your storage needs
An Automation Suite cluster uses the objectstore disks attached to its server nodes as storage resources available to all the products enabled on your cluster. Each product uses these resources differently.
To understand your storage needs and plan for them accordingly, refer to the following terminology and guidelines.
-
Server node disk size – The size of all individual disks attached to each server node.
- Disks on each server may have different sizes as long as the sum of all the disk sizes is identical on all servers.
- Total cluster disk size – Server node disk size multiplied by the number of server nodes.
-
Application available storage – The amount of storage available for applications to consume.
- Application available storage is lower than the total storage attached. This is to ensure we have a higher resiliency to fault tolerance and high availability.
The following table describes the multi-node HA-ready hardware requirements for the Complete product selection in the context of the previously introduced terms.
|
Number of server nodes |
Server node disk size |
Total cluster disk size |
Application available storage |
|---|---|---|---|
|
3 |
512 GiB |
1.5 TiB |
512 GiB |
As you enable and use products on the cluster, they consume some storage from the application available storage. Products usually have a small enablement footprint as well as some usage-dependent footprint that varies depending on the use case, scale of use, and project. The storage consumption is evenly distributed across all the storage resources (data disks), and you can monitor the levels of storage utilization using the Automation Suite monitoring stack.
You will receive an alert with a warning when the storage consumption exceeds 75%. You will receive another critical alert when the storage consumption exceeds 85%; in this case, the storage will be read-only.
If your evaluated needs do not meet the recommended hardware requirements, you can add more storage capacity using either one or both of the following methods:
- You have to add a new disk on all the server nodes of same size.
- To configure the disk, see our docs.
You can estimate your storage consumption using the product-specific metric in the following tables. These tables describe how much content you can place on your cluster out of the box. For reference, they include the storage footprint of a typical usage scenario of each product.
|
Product |
Storage-driving metric |
Storage per metric |
Typical use case |
|---|---|---|---|
|
Shared suite capabilities |
|
N/A |
Typically, 7 days of application logs is around 25 GiB. |
|
Orchestrator |
|
|
Typically, a package is 5 MiB, and buckets, if any, are less than 1 MiB. A mature enterprise has 5 GiB of packages and 6 GiB of buckets deployed. |
|
Action Center |
|
|
Typically, a document takes 0.15 MiB, and the forms to fill take an additional 0.15 KiB. In a mature enterprise this can roll up to 4 GiB in total. |
|
Test Manager |
|
|
Typically, all files and attachments add up to approximately 5 GiB. |
|
Insights |
|
|
2 GiB are required for enablement, with the storage footprint growing with the number. A well-established enterprise-scale deployment requires another few GiB for all the dashboards. |
|
Automation Hub |
N/A |
N/A |
2 GiB fixed footprint |
|
Automation Ops |
N/A |
N/A |
No storage footprint |
|
Apps |
|
|
Typically, the database takes approximately 5 GiB, and a typical complex app consumes approximately 15 MiB. |
|
AI Center |
|
|
A typical and established installation will consume 8 GiB for 5 packages and an additional 1GiB for the datasets. A pipeline may consume an additional 50 GiB, but only when actively running. |
|
Document Understanding |
|
|
In a mature deployment, 12GiB will go to ML model, 17GiB to the OCR, and 50GiB to all documents stored. |
|
Task Mining |
|
|
Typically, about 200GiB of activity log data should be analyzed to suggest meaningful automations. Highly repetitive tasks however, may require much less data. |
|
Process Mining |
|
|
Minimal footprint only used by users uploading data via the Process Mining portal. Approximately 10 GiB of storage should be enough in the beginning. |
