Abstract: In one aspect, an example methodology implementing the disclosed techniques includes receiving, by a systems management console, a network address of a device in a virtual environment, and determining a network address associated with a virtual environment management console based on the received network address of the device in the virtual environment. The method also includes sending, by the systems management console via a systems management agent to the virtual environment management console using the determined network address associated with the virtual environment management console, a request for network addresses of virtual machine (VM) host servers and VMs in the virtual environment. The method also includes receiving, by the systems management console via the systems management agent from the virtual environment management console, the network addresses of the VM host servers and the VMs in the virtual environment and providing a notification of the discovered VM host servers and VMs.

Abstract: An apparatus comprises a processing device configured to monitor a health status of storage devices that are part of a virtual disk and to identify a first subset of the storage devices that have a first health status and a second subset of the storage devices that have a second health status. The processing device is also configured, responsive to determining that there is sufficient available storage capacity on the second subset of the storage devices to copy data from used storage capacity on the first subset of the storage devices, to resize the virtual disk to a storage capacity determined as a function of storage capacities of the second subset of the storage devices allocated to the virtual disk and to copy data from the used storage capacity on the first subset of the storage devices to the available storage capacity on the second subset of the storage devices.

Abstract: An apparatus comprises a processing device configured to identify, for a modular server, blade servers installed in a first subset of slots of a chassis of the modular server and storage servers installed in a second subset of the slots. The processing device is also configured to determine, for the modular server, assignment of storage devices of the storage servers installed in the second subset of the slots to respective ones of the first subset of the slots in which the blade servers are installed. The processing device is further configured to detect movement of a given blade server from a first to a second slot in the first subset of the slots, and to dynamically reassign at least a subset of the storage devices from the first to the second slot responsive to validating a configuration of the given blade server moved from the first to the second slot.

Abstract: A modular server chassis enclosure controller (EC) on-premises keyboard video and mouse module has an EC frame buffer memory and an EC virtual network computing (libvnc) client process. The libvnc fetches an EC frame buffer memory address, displays an on-screen display (OSD) screen to a user and accepts user selection of a blade server deployed in the modular server chassis from the OSD. The libvnc receives a virtual network computing (VNC) streaming session over transport layer security, from a VNC computing server process of the selected blade server. The libvnc determines whether the VNC server process has data to send and, if it does, reads graphics data from the virtual network computing server process and writes the graphics data from the VNC server to the EC frame buffer memory address. The graphics data is displayed on an on-premises monitor coupled to the modular server chassis from the EC frame buffer.

Abstract: An apparatus comprises a processing device configured to identify, for a modular server, blade servers installed in a first subset of slots of a chassis of the modular server and storage servers installed in a second subset of the slots. The processing device is also configured to determine, for the modular server, assignment of storage devices of the storage servers installed in the second subset of the slots to respective ones of the first subset of the slots in which the blade servers are installed. The processing device is further configured to detect movement of a given blade server from a first to a second slot in the first subset of the slots, and to dynamically reassign at least a subset of the storage devices from the first to the second slot responsive to validating a configuration of the given blade server moved from the first to the second slot.

Abstract: An information handling system may include a processor and non-transitory computer-readable media communicatively coupled to the processor and having stored thereon a program of instructions configured to, when read and executed by the processor, perform data collection to retrieve hardware information regarding a second information handling system and analyze the hardware information to determine one or more recommended purposes for the second information handling system.

Abstract: An apparatus comprises a processing device configured to monitor a health status of storage devices that are part of a virtual disk and to identify a first subset of the storage devices that have a first health status and a second subset of the storage devices that have a second health status. The processing device is also configured, responsive to determining that there is sufficient available storage capacity on the second subset of the storage devices to copy data from used storage capacity on the first subset of the storage devices, to resize the virtual disk to a storage capacity determined as a function of storage capacities of the second subset of the storage devices allocated to the virtual disk and to copy data from the used storage capacity on the first subset of the storage devices to the available storage capacity on the second subset of the storage devices.

Abstract: A method comprises collecting data from a computing environment comprising one or more storage devices, wherein the data comprises information identifying assignments of the one or more storage devices to one or more servers in the computing environment. In the method, the data is analyzed using one or more machine learning algorithms, wherein the analyzing comprises predicting whether a given configuration of the one or more storage devices in combination with the one or more servers is a specified configuration. The method also includes generating a storage configuration recommendation for a user based on the analysis, and transmitting the storage configuration recommendation to the user.

Abstract: One example method includes receiving data from a container data collector (CDC), and the data concerns a container, analyzing the data and, based on the analyzing, identifying a security tool needed to scan the container, drawing the security tool from a knowledge lake, executing the security tool to perform a vulnerability scan of the container, based on the executing of the security tool, generating and analyzing a report concerning the vulnerability scan, and transmitting the report, and results of the analyzing, to an alert and action stage.

Abstract: An information handling system includes processing modules and an I/O module. The processing modules each have one of a high or low priority level. The I/O module is coupled to a network device and includes network ports coupled to the processing modules. A port bandwidth control engine (PBCE) determines that the network device is providing a maximum bandwidth to the I/O module, and in response, allocates the maximum bandwidth equally to the processing modules. The PBCE further determines that the network device is providing a reduced bandwidth to the I/O module, and, in response, allocates to each high priority level processing module a first bandwidth on the associated network port and allocates to each low priority level processing module a second bandwidth on the associated network port.

Abstract: An information handling system includes an add-in slot and a baseboard management controller (BMC). The add-in slot receives components of a particular type. The BMC receives an identifier from a particular component installed into the add-in slot. The identifier uniquely identifies the component from any other component of the same type. The BMC further determines whether or not a first entry in an encoded component table includes the first identifier, determines an action to perform for the component in response to determining that the entry includes the identifier, and performs the action for the component. The first entry is associated with the first add-in slot.

Abstract: One example method includes collecting container information concerning a container, analyzing the container information to identify a security tool needed to perform a vulnerability scan of the container, accessing the security tool from a knowledge lake, running the security tool on the container information to identify a security vulnerability of the container, based on the running of the security tool, generating an alert indicating that the container has the security vulnerability, capturing the security vulnerability and, based on the captured security vulnerability, updating a container image that was used to spawn the container.

Abstract: Systems that search databases of videos or images to identify similar products in a given video or image of a product are disclosed. The content of the given video is represented by a feature vector used to measure the given video's similarity to either a video or an image. When the system is deployed to recognize particular fashion items in videos, some such videos are taken in uncontrolled settings, and as a result, may have low resolution, poor contrast, minimal focus, motion blur, or low lighting. By recognizing and removing poor quality video frames from the image recognition pipeline, associating products across video frames to form tracklets of each product, and enriching the feature representation of each item for best retrieval result by fusing information from multiple video frames depicting the item, the system addresses the aforementioned shortcomings.

Abstract: Disclosed methods maintain security key information, including a unique security key, for one or more blade servers inserted in slots of one or more modular chassis. Following an indication of a logical trusted group comprising a plurality of slots, a trusted group database, including the security key information for each blade server in a slot of the trusted group, is maintained. Responsive to detecting movement of a blade server between two slots of the trusted group, a pre boot process of the server blade in the second slot is automatically authenticated via the security key information in the trusted group database. If a blade server not associated with the trusted group is inserted into a trusted group slot, automatic authentication is blocked and the user is prompted to manually authenticate the new blade server. If manual authentication is successful, security key information for the new blade is added to the database.

Abstract: A modular server chassis enclosure controller (EC) on-premises keyboard video and mouse module has an EC frame buffer memory and an EC virtual network computing (libvnc) client process. The libvnc fetches an EC frame buffer memory address, displays an on-screen display (OSD) screen to a user and accepts user selection of a blade server deployed in the modular server chassis from the OSD. The libvnc receives a virtual network computing (VNC) streaming session over transport layer security, from a VNC computing server process of the selected blade server. The libvnc determines whether the VNC server process has data to send and, if it does, reads graphics data from the virtual network computing server process and writes the graphics data from the VNC server to the EC frame buffer memory address. The graphics data is displayed on an on-premises monitor coupled to the modular server chassis from the EC frame buffer.

Abstract: Embodiments for providing end-to-end automated contextual and differentiated application level replication by dynamically creating replication profiles for asynchronous or synchronous replication at runtime to maintain any relevant service level agreement requirements. Based on relevant operating information, data sources are identified as critical and non-critical servers and their data is tagged accordingly in the replication application by using an analytics engine. The information and tags are used to produce a trained model for machine learning processes that can generated predictions for future replication operations. An error handler identifies erroneous predictions and provides a fallback mechanism to avoid any customer replication service level agreement breach at any given time.

Abstract: Code files for performing test cases on information handling systems may be generated from pre-existing test cases using natural language processing and/or machine learning algorithms. For example, a method may include receiving a test case comprising a plurality of tasks; identifying, by inputting the test case into a machine learning algorithm, a subset of code segments from code segments of at least one pre-existing test case in a code library matching at least one task of the plurality of tasks in the test case; and generating an indication of the subset of code segments for re-use from the at least one pre-existing test case for the test case.

Abstract: Technology described herein is generally directed towards an efficient process to selectively boot (e.g., initialize, re-boot, re-initialize and/or the like) one or more nodes of a server node system based on contextual information that can be automatically acquired. In an embodiment, a system can comprise a processor, and a memory that stores executable instructions that, when executed by the processor, can facilitate performance of operations. The operations can comprise monitoring operational activity of a node of a software-defined object storage system. The operations can comprise, in response to occurrence of a negative activity event determined based on a result of the monitoring, determining whether a node reboot of the node is to be implemented. The operations can comprise, based on the operational activity analyzed, setting a reboot flag indicating that the node reboot is to comprise a reboot of less than all components of the node.

Abstract: An apparatus comprises a processing device configured to receive, at a host operating system of a virtual machine host, a request to execute a virtual machine and to obtain, from a virtual trusted platform module running on the virtual machine host, credentials for logging in to a guest operating system of the virtual machine. The processing device is further configured to provide, to pre-boot authentication software associated with the virtual machine, the credentials obtained from the virtual trusted platform module, and to automatically log in to the guest operating system of the virtual machine utilizing the pre-boot authentication software and the provided credentials.

Abstract: Embodiments of systems and methods for exothermic event prediction engine are described. In an embodiment, an Information Handling System (IHS) may include: a processor, a Remote Access Controller (RAC) coupled to the processor, and a memory coupled to the RAC, the memory having program instructions stored thereon that, upon execution by the RAC, cause the RAC to collect telemetry data from the IHS and predict an exothermic failure in the IHS based, at least in part, upon the telemetry data.