Abstract: Systems and methods of managing an optimal port setup for workspaces are described. In an illustrative, non-limiting embodiment, an Information Handling System (IHS) may include: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: obtain information for a plurality of peripheral devices coupled to at least some of a plurality of ports of the IHS in a first configuration; and recommend a second configuration for connecting one or more of the plurality of peripheral devices to one or more of the plurality of ports of the IHS based, at least in part, on the information.

Abstract: Intelligent recovery of managed devices can be provided in a multi-tenant cloud environment. A recovery service can be employed to maintain management server details and device details for managed devices across multiple tenants. When a managed device loses connectivity to its management server, an agent on the managed device can access the recovery server to obtain management server details which have been associated with device details of the managed device. The agent can then use the management server details to regain connectivity to the management server.

Abstract: Systems and methods for managing workspaces using productivity profiles are described. In an embodiment, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: send a user's productivity profile to a remote service, where the productivity profile is created based, at least in part, upon a utilization of a peripheral device when the IHS is deployed in a first workspace; and receive, from the remote service, a recommendation to deploy the IHS in a selected workspace, where the recommendation is produced based, at least in part, upon a comparison between the user's productivity profile and a set of capabilities of the selected workspace.

Abstract: Proactive auto scaling can be implemented in a scaled multi-tenant cloud environment. For a particular update window, a management server can obtain tenant details for each tenant whose endpoints are to be updated during the update window using a file server. The management server can use the tenant details to calculate a total update time for deploying a respective update to each of the endpoints. If the total update time will exceed the update window, the management server can create one or more additional file servers and cause some of the endpoints to obtain their respective update from the one or more additional file servers to thereby ensure that all the endpoints can complete the update during the update window.

Abstract: Intelligent recovery of managed devices can be provided in a multi-tenant cloud environment. A recovery service can be employed to maintain management server details and device details for managed devices across multiple tenants. When a managed device loses connectivity to its management server, an agent on the managed device can access the recovery server to obtain management server details which have been associated with device details of the managed device. The agent can then use the management server details to regain connectivity to the management server.

Abstract: Proactive auto scaling can be implemented in a scaled multi-tenant cloud environment. For a particular update window, a management server can obtain tenant details for each tenant whose endpoints are to be updated during the update window using a file server. The management server can use the tenant details to calculate a total update time for deploying a respective update to each of the endpoints. If the total update time will exceed the update window, the management server can create one or more additional file servers and cause some of the endpoints to obtain their respective update from the one or more additional file servers to thereby ensure that all the endpoints can complete the update during the update window.

Abstract: Self-learning based dynamic staged deployment of updates is provided. When an administrator desires to deploy an update to endpoints, the administrator can specify whether the deployment should be performed using static waves or dynamic waves. When static waves are selected, the administrator can also specify a number or percentage of the endpoints that should be part of the first wave and a multiplication factor to be used for selecting endpoints for the subsequent waves. When dynamic waves are selected, the administrator can also specify a wave attribute and a maximum first wave percentage, and such input can be used as part of various dynamic selections and calculations to deploy the update in waves.

Abstract: An express update deployment system can enable a larger number of computing devices to be updated during a time window. When an update is to be deployed to computing devices, a management server can select a set of the computing devices to function as proxy file repositories. The management server can select the set of computing devices based on hardware details of the computing devices that are to be updated. The management server can prioritize the deployment of the update to the selected set of computing devices. Once the update has been deployed on the selected set of computing devices, the computing devices can commence functioning as proxy file repositories. The management server can then instruct other computing devices to obtain parts of the update from the computing devices that are functioning as proxy file repositories. The management server can also instruct other computing devices to concurrently obtain the update from the file repository.

Abstract: An express update deployment system can enable a larger number of computing devices to be updated during a time window. When an update is to be deployed to computing devices, a management server can select a set of the computing devices to function as proxy file repositories. The management server can select the set of computing devices based on hardware details of the computing devices that are to be updated. The management server can prioritize the deployment of the update to the selected set of computing devices. Once the update has been deployed on the selected set of computing devices, the computing devices can commence functioning as proxy file repositories. The management server can then instruct other computing devices to obtain parts of the update from the computing devices that are functioning as proxy file repositories. The management server can also instruct other computing devices to concurrently obtain the update from the file repository.

Abstract: Applications can be selectively offloaded to ensure that thin clients will have sufficient disk space to install an update. To enable this offloading, a service can be employed to track how long each application is used on the thin client during a particular time period. Based on this usage of each application, the service can assign a rank to each application. The service can also monitor the amount of free space on the disk to determine whether it has fallen below a threshold. If so, the service can employ the ranks to identify applications to be offloaded them by copying an install location folder for each application to a remote repository and then deleting each copied install location folder. When the thin client includes a write filter, the service can commit the deletes of the install location folders so that the applications will remain offloaded after reboot.

Abstract: Applications can be selectively offloaded to ensure that thin clients will have sufficient disk space to install an update. To enable this offloading, a service can be employed to track how long each application is used on the thin client during a particular time period. Based on this usage of each application, the service can assign a rank to each application. The service can also monitor the amount of free space on the disk to determine whether it has fallen below a threshold. If so, the service can employ the ranks to identify applications to be offloaded them by copying an install location folder for each application to a remote repository and then deleting each copied install location folder. When the thin client includes a write filter, the service can commit the deletes of the install location folders so that the applications will remain offloaded after reboot.

Abstract: Techniques for non-disruptive upgrade of a storage appliance may include: restarting a first portion of nodes running a target software version while also running a current software version on a second portion of the nodes, wherein the non-disruptive upgrade is performed to upgrade the nodes of the storage appliance from the current software version to the target software version; performing I/O forwarding where I/Os from the host initiators are serviced using the second portion of the nodes and not serviced using the first portion of the nodes; and determining, in accordance with host initiator login information, whether to continue with the non-disruptive upgrade of the nodes to the target software version. Such techniques may be used, for example, to avoid data unavailability for one or more hosts using the host initiator login information.

Abstract: Cloud based Wake-on-LAN (WoL) for thin clients can be performed to allow a cloud based management server to wake up a thin client prior to an update command (or other communication) being transmitted to the thin client to ensure that the thin client will receive the update command. Cloud based WoL can therefore facilitate the deployment of updates to thin clients by providing a way for the administrator to wake up the thin clients from the cloud.

Abstract: Analytics driven update notifications can be provided. An agent on a managed device can monitor which applications are being used on the managed device and can provide a report of these application usage details along with other details of components on the managed device to a management server. The management server can evaluate reports received from a number of agents to generate rankings of applications and components that are based at least partially on usage. The management server can then identify available updates and present recommendations for deploying the updates based on the rankings.

Abstract: Peer assisted updates can be provided in a device management environment. When it is desired to deploy an update to a group of managed devices, an update command can be sent to a first set of managed devices in the group instructing these managed devices to download the update. Once these managed devices have downloaded and installed the update, they will notify the management server. In response, the management server can instruct these managed devices to remain awake so that they may each function as a master device or repository for deploying the update to other managed devices in the group. The management server can then send update commands to the other managed devices instructing them to download the update from one of the managed devices that is now acting as a master device. This process can be repeated until all managed devices in the group have been updated.

Abstract: Analytics driven update notifications can be provided. An agent on a managed device can monitor which applications are being used on the managed device and can provide a report of these application usage details along with other details of components on the managed device to a management server. The management server can evaluate reports received from a number of agents to generate rankings of applications and components that are based at least partially on usage. The management server can then identify available updates and present recommendations for deploying the updates based on the rankings.

Abstract: Manual discovery of devices in a device management environment can be performed from a management server. The manual discovery process can enable the discovery process to be initiated at the management server and can be performed without requiring an administrator or other user to manually configure each device to initiate and perform the discovery process. To discover devices to be managed, the management server, which can be a cloud based server or Software as a Service based server, can send a registration request to an on-premise server. The on-premise server can then relay this registration request to all devices on the same network infrastructure. The agent on each device can be configured to listen for such registration requests, and in response to receiving a registration request, can automatically register with the management server using information contained in the registration request. In this way, the management server can manually discover devices.

Abstract: The invention provides a method of detecting Clostridium difficile in a sample, comprising detecting the presence in said sample of one or more genes that have been identified as being specific to Clostridium difficile. Also provided is a method of diagnosing a Clostridium difficile infection in a subject, a method of determining the efficacy of a therapeutic regime being used to treat a Clostridium difficile infection and a method of testing for the presence of Clostridium difficile in a sample. Further provided are primer pairs and a kit suitable for use in such methods.

Abstract: A diagnostic service can be provided for devices that include a device agent for allowing the devices to be managed. The diagnostic service can operate on a managed device to monitor and manage the device agent. To facilitate communication between the management server and the diagnostic service, the diagnostic service can obtain connection information and an authentication code from the device agent after the device agent has registered with the management server. The diagnostic service can then employ the connection information and authentication code to register with the management server. Once the diagnostic service is registered, the management server can employ the diagnostic service to monitor and manage the device agent.

Abstract: Cloud based Wake-on-LAN (WoL) for thin clients can be performed to allow a cloud based management server to wake up a thin client prior to an update command (or other communication) being transmitted to the thin client to ensure that the thin client will receive the update command. Cloud based WoL can therefore facilitate the deployment of updates to thin clients by providing a way for the administrator to wake up the thin clients from the cloud.