This article describes the options and features provided for self-managed Lilt deployments.
Lilt application features
The features listed below can be enabled/disabled during the Lilt installation process.
|Lilt Application Feature||Functionality|
|Audit logging||Logs database and access events received by the Lilt application. Users can perform an audit of the application by querying the logs for events of interest, such as database access or API access.|
|Custom UI banners||The following aspects of the Lilt application UI header and footer can be changed:
Custom UI banners can be updated at any time.
|Document security scan||All files uploaded into Lilt are scanned for malicious threats. The scan is performed against the Clam AntiVirus image. Document security scanning is not supported for files uploaded into Lilt via API.|
|Hard delete||When deleting documents and projects, segment information is permanently removed from the system.|
|Instant translate documents and Instant translate text||Users can utilize the organization’s Lilt Memories to quickly translate documents and text blocks outside the Lilt Translate.|
|Single sign-on (SSO)||Users can authenticate to the Lilt platform using an identity provider other than Lilt.|
|Segment logging||Segment information is logged in the application’s backend logs.
Admin can enable/disable this feature at any time.
Super admin user
Functionality: The super admin user is the initial app user with administrative privileges. It has admin privileges only inside its own organization.
Configuration: By default, the super admin user is set to firstname.lastname@example.org, but can be changed during the initial Lilt installation process.
GPU batch worker count
Functionality: GPU batch workers are used for parallel batch processing. GPU batch workers speed up document processing by providing quicker translations and memory updates.
Configuration: The following GPU batch worker settings can be set for the cluster:
- maximum number of GPU batch workers
- number of standby GPU batch workers
The optimal number of GPU batch workers is dependent on the available resources and the organization’s translation workflow. Optimal configuration will speed up parallel batch processing operations.
Minimum segments count for GPU batch workers
Functionality: Each document must meet or exceed a minimum segment count before a GPU batch worker will process the document.
Configuration: Batch-related custom configurations are available to set the minimum segment count. Since GPU resources are limited in availability, care should be taken when setting the minimum segment count so that GPU usage benefits your workflow and is not just a resource drain.
Persistent data location
Functionality: The persistent data location is used to store persistent data for Lilt and the applications listed below in the Infrastructure applications section. Data is stored and retrieved from this location during application usage. Data is not removed if the applications are deleted.
Configuration: The admin can configure the persistent data location during the Lilt application installation. The volume should be attached to the Kubernetes worker nodes. The volume cannot be updated without destroying the cluster.
Functionality: The host name is used to access the Lilt application. Customizing the host name allows for each organization to create a host name that can be easily remembered by the organization’s members.
Configuration: The host name can be specified during the Lilt application installation and can be updated at any time after installation. When configuring the host name, failure to provide a valid SSL certificate and key for the host name will result in SSL error and inability to access the Lilt application.
For self-managed installation of Lilt, the applications below are also installed to enable Lilt to function:
- MinIO: object storage server
- OpenEBS: object storage solution
- Docker-registry: Docker container storage
- MySQL: database
- Redis: data structure caching
- RabbitMQ: queue management
- Nginx-ingress: Ingress controller
- ElasticSearch: indexing
- Grafana: monitoring dashboard
- Prometheus: app metrics
- Nvidia-device-plugin: GPU management in Kubernetes