This Fling connects to and monitors multiple vCenter instances simultaneously, providing detailed information about detected alarms.

This Fling is a collection of ESXi Native Drivers which enables ESXi to recognize and consume various NVMe-based storage devices. These devices are not officially on the VMware HCL and have been developed to enable and support the VMware Community.

The Virtual Machine Computer Optimizer (VMCO) is a Powershell script that captures information about the hosts and VMS running in your vSphere environment, and reports back on whether the VMs are configured optimally based on the Host CPU and memory.

Resource-Efficient Supervised Anomaly Detection Classifier is a scikit-learn classifier for resource-efficient anomaly detection that augments either Random-Forest or XGBoost classifiers to perform well in a resource-constrained setting.

The Workspace ONE macOS App Analyzer will determine any Privacy Permissions, Kernel Extensions, or System Extensions needed by an installed macOS application, and can be used to automatically create profiles in Workspace ONE UEM to whitelist those same settings when deploying apps to managed devices.To connect to your
Workspace ONE UEM environment:

The Workspace ONE mobileconfig Importer gives you the ability to import existing mobileconfig files directly into a Workspace ONE UEM environment as a Custom Settings profile, import app preference plist files in order to created managed preference profiles, and to create new Custom Settings profiles from scratch.

This toolkit is intended to facilitate managing the lifecycle of these special configurations by leveraging vSphere APIs.

This Fling provides a platform for Data Scientists to quickly setup a virtualized cloud infrastructure to conduct data science experiments.

Desktop Container Tools is a free tool that allows you to do basic management of vctl (a CLI tool shipped with VMware Fusion) container engine on macOS for running containers and Kubernetes clusters.

Project Supernova is to build a common machine learning inference service framework by enabling machine learning inference accelerators across edge endpoint devices, edge systems and cloud, with or without hardware accelerators.

FATE is an opensource project hosted by Linux Foundation to provide a federated learning framework. FATE has been used to increase the performance of predictions in credit reporting, insurance and other financial areas, as well as surveillance and visual detection projects. It helps organizations to comply with strict privacy regulations and laws such as GRDP and CCPA.