Abstract: Methods, systems, and techniques for metadata determination and storage. A large language model that is implemented using at least one artificial neural network receives an initial prompt that includes a query related to the metadata. The metadata is in respect of data that is part of a dataset, and the initial prompt includes context for the query. The large language model determines the metadata in response to the query using the context. Once determined, the metadata is stored in the dataset such that the metadata is associated with the data to which it relates.

Abstract: Systems, methods, and other embodiments associated with placing a virtual machine or workload on one of a plurality of hosts are described. In one embodiment, a method includes analyzing the hosts to identify a set of candidate hosts. Each candidate host is analyzed and a threat score is calculated for each candidate host that is indicative of a degree of vulnerability of the candidate host to information-security threats. The corresponding threat scores from the candidate hosts are compared and a host with a lowest threat score is selected, and the virtual machine is placed on the selected host. Thereafter, the selected host is reanalyzed to calculate an updated threat score based at least in part upon the placement of the virtual machine, and in response to determining that the updated threat score exceeds a threshold, the virtual machine is moved to a different host.

Abstract: Systems, methods, and other embodiments associated with placing a workload on one of a plurality of hosts are described. In one embodiment, a method includes analyzing hosts to identify a first host and a second host determined to meet resource requirements of the workload. The example method may also include analyzing the first host to calculate a first threat score, and analyzing the second host to calculate a second threat score. The example method may also include selecting a host with a lowest threat score and placing the workload on the selected host. The example method may also include reanalyzing the selected host to calculate an updated threat score. The example method may also include in response to determining that the updated threat score exceeds a threshold threat score, moving the workload to a third host.

Abstract: In a general aspect, a computer-implemented method can include provisioning a virtual network on a hypervisor server. The method can also include querying the hypervisor server to determine an allowable range for a number of virtual ports of a first port group of a virtual switch implemented on the hypervisor server, the first port group being associated with the virtual network. The method can further include provisioning at least one virtual machine on the virtual network including assigning a respective virtual port of the first port group to the virtual machine. The method can still further include monitoring usage of the virtual ports of the first port group and, in response to the usage of the virtual ports of the first port group exceeding a threshold, instructing the hypervisor server to provision a second port group on the virtual switch, the second port group being associated with the virtual network.