Whats New 2022
April 2022 Run:ai Version 2.4 (Controlled Release only)¶
Important Upgrade Note¶
This version contains a significant change in the way that Run:ai uses and installs NVIDIA pre-requisites. Prior to this version, Run:ai has installed its own variants of two NVIDIA components: NVIDIA device plugin and NVIDIA DCGM Exporter.
As these two variants are no longer needed, Run:ai now uses the standard NVIDIA installation which makes the Run:ai installation experience simpler. It does however require non-trivial changes when upgrading from older versions of Run:ai.
Going forward, we also mandate the usage of the NVIDIA GPU Operator version 1.9. The Operator easies the installation of all NVIDIA software. Drivers and Kubernetes components alike.
Dynamic MIG Support¶
- Run:ai now support fractions on GKE. GKE has a different software stack for NVIDIA. To install Run:ai on GKE please contact Run:ai customer support.
March 2022 Run:ai Version 2.3¶
Important Upgrade Note¶
To upgrade to version 2.3 cluster from earlier versions, you must uninstall version 2.2 or earlier and only then install version 2.3. For detailed information see cluster upgrade.
Unified User Interface¶
The Researcher user interface and the Administrator user interface have been unified into a single unified Run:ai user interface. The new user interface is served from
https://<company-name>.run.ai. The user interface capabilities are subject to the role of the individual user.
- See instructions on how to set up the unified user interface.
- See user interface Jobs area for a description on how to submit, view and delete Jobs from the unified user interface.
- Additional information about scheduler decisions can now be found as part of the Job's status. View the Job status by running runai describe job or selecting a Job in the user interface and clicking
- Run:ai now support Charmed Kubernetes.
- Run:ai now supports orchastraction of containerized virtual machines via Kubevirt. For more information see kubevirt support.
- Run:ai now supports Openshift 4.9, Kubernetes 1.22 and 1.23.
February 2022 Run:ai Version 2.2¶
- When enabling Single-Sign, you can now use role groups. With groups, you no longer need to provide roles to individuals. Rather, you can create a group in the organization's directory and assign its members with specific Run:ai Roles such as Administrator, Researcher, and the like. For more information see single-sign on.
- REST API has changed. The new API relies on
Applications. See Calling REST APIs for more information.
- Added a new user role
Research Manager. The role automatically assigns the user as a Researcher to all projects, including future projects.
January 2022 Run:ai Version 2.0¶
We have now stabilized on a single version numbering system for all Run:ai artifacts:
- Run:ai Control plane (also called Backend).
- Run:ai Cluster.
- Run:ai Command-line interface.
- Run:ai Administrator Command-line interface.
Future versions will be numbered using 2 digits (2.0, 2.1, 2.2, etc.). Numbering for the different artifacts will vary at the third digit as we provide patches to customers. As such, in the future, the control plane can be tagged as 2.1.0 while the cluster tagged as 2.1.1.
- To allow for better control over resource allocation, the Run:ai platform now provides the ability to define different over-quota priorities for projects. For full details see Controlling over-quota behavior.
- To help review and track resource consumption per department, the Department object was added to multiple dashboard metrics.
- A new tool was added, to allow IT administrators to validate cluster and control-plane installation pre-requisites. For full details see cluster installation prerequisites, Kubernetes self-hosted prerequisites or Openshift self-hosted prerequisites.
- To better analyze scheduling issues, node name was added to multiple scheduler log events.