Abstract: Provided is a method of automatically discovering topology of an information technology (IT) infrastructure. Topology relationships amongst configuration items (CI) present in a semi-structured data generated by an information technology component of the IT infrastructure are determined. Topology relationships amongst configuration items (CI) present in a structured data generated by the information technology component of the IT infrastructure are determined. The topology relationships amongst the configuration items (CI) present in the semi-structured data are reconciled with the topology relationships amongst the configuration items (CI) present in the structured data.

Abstract: Examples described relate to identifying a potentially erroneous device in an IoT network. In an example, data from a device in an IoT network. The data may be analyzed against a classification of previous data from the plurality of devices, wherein the classification classifies the previous data as one of an erroneous data, a potentially erroneous data, or a normal data. If the data from the device represents the erroneous data, the device may be included in a set of potentially erroneous devices. A cluster of the device may be determined in a cluster classification. If the device belongs to the erroneous cluster in the cluster classification, associated devices in the erroneous cluster may be added to the set of potentially erroneous devices. If a threshold amount of devices in the set of potentially erroneous devices is higher than a pre-defined value, a notification may be generated.

Abstract: Examples relate to deploying QoS policies in interfaces of network devices of a network. A full traffic matrix of a network is obtained by monitoring network traffic in a set of interfaces of a set of network devices of the network, wherein network traffic is generated by application. A required bandwidth for each application in each interface in the network is determined based on a priority assigned to the applications. A set of interfaces among all the interfaces of the network are identified for deploying a QoS policy. The QoS policy to be deployed in each interface is determined based on an IT policy of the network. Lastly, the determined QoS policies are deployed into the set of interfaces of the network.

Abstract: In one example in accordance with the present disclosure, a priority is determined for each element in a plurality of elements connected to a network. The plurality of elements may include a source element, a destination element and a first element selected for downtime. A reliability index is determined for each element in the plurality of elements and a plurality of alternate paths between the source element and destination element are determined, each alternate path including a corresponding plurality of elements. For each alternate path in the plurality, a total utilization of the corresponding plurality of elements of the alternate path may be determined for each of a plurality of time slots and a best time slot to be used as a time period for the downtime of the first element may be determined based on the total utilizations.

Abstract: Examples described relate to identifying a potentially erroneous device in an IoT network. In an example, data from a device in an IoT network. The data may be analyzed against a classification of previous data from the plurality of devices, wherein the classification classifies the previous data as one of an erroneous data, a potentially erroneous data, or a normal data. If the data from the device represents the erroneous data, the device may be included in a set of potentially erroneous devices. A cluster of the device may be determined in a cluster classification. If the device belongs to the erroneous cluster in the cluster classification, associated devices in the erroneous cluster may be added to the set of potentially erroneous devices. If a threshold amount of devices in the set of potentially erroneous devices is higher than a pre-defined value, a notification may be generated.

Abstract: Provided is a method of automatically discovering topology of an information technology (IT) infrastructure. Topology relationships amongst configuration items (CI) present in a semi-structured data generated by an information technology component of the IT infrastructure are determined. Topology relationships amongst configuration items (CI) present in a structured data generated by the information technology component of the IT infrastructure are determined. The topology relationships amongst the configuration items (CI) present in the semi-structured data are reconciled with the topology relationships amongst the configuration items (CI) present in the structured data.

Abstract: Provided is a method of identifying a virtual machine for placement in a cloud computing environment, wherein the cloud computing environment comprises multiple cloud computing systems. Workload requests of the virtual machine are segregated into fixed workload request and flexible workload request. An optimal cloud computing system is selected in the cloud computing environment to perform fixed workload request and/or flexible workload request of the virtual machine.

Abstract: A proximity table is generated for a first of a group of hosts for one or more computer workloads. Workloads are assigned to the host by applying proximity rules to the proximity table. The generating of proximity tables and the assignment of workloads is iterated for other hosts until all workloads have been assigned.