Hewlett Packard Enterprise Development LP

Naveena Kedlaya

Sharath Karkada Srinivasa

Bindu Loganathan

Maneesh Keshavan Bendiganavale

Umesh Markandaya Lakshminarasimha

Vinay Sahadevappa Banakar

Pavan Belur Gopalakrishna Upadhya

Rekha G

Varsha Anandani

Geoffery Schunicht

Tushar Bajpai

Nagaraj P Hegde

Vijay Suryanarayana

Mahesh Ramenahalli Mayanna

Techniques for performing operation-based event suppression are described. In an example, a determination may be performed as to whether an event is to be suppressed if the event is received in response to performance of an operation. The determination may be performed based on at least one of number of actions triggered by the event, frequency of occurrence of the event in an event stream in response to performance of the operation, and frequency of occurrence of the event in the event stream without performance of the first operation.

Operation-based event suppression

Some examples relate to identifying a security vulnerability in a computer system. In an example, via a NAND flash memory, a computer system may be scanned to obtain information related to a software program, based on a rule set defined in a management controller (e.g., baseboard management controller (BMC)) on the computer system. The NAND flash memory may obtain metrics related to the software program via the BMC. The NAND flash memory may analyze the information related to the software program along with the metrics related to the software program to identify a security vulnerability in the computer system. The NAND flash memory may provide the information related to the security vulnerability in the computer system to the BMC.

Identifying a security vulnerability in a computer system

Example implementations relate to method and controller for secure management of a rack. The method includes generating a first unique identifier corresponding to a rack profile of the rack hosting rack devices including physical devices and logical devices, in accordance with a rack topology, wherein the rack profile is based on configuration of the rack devices and the rack topology. Further, the method includes receiving information corresponding to the rack profile of the rack from peripheral devices disposed in the rack, wherein the information is based on monitored condition of the rack devices and the rack topology. The method further includes generating a second unique identifier based on the information, and determining variation in the rack profile based on comparison of the first and second unique identifiers. Further, the method includes generating an alert signal in the rack, in response to determination of the variation in the rack profile.

System and method for secure management of a rack

Example implementations relate to method and system for securing a workload from a security vulnerability based on management of critical patches for the workload. The method includes obtaining information of existing patches for each of a plurality of infrastructure resources that are required to execute the workload, where the infrastructure resources are segregated as multiple layers. The method further includes determining dependency of the infrastructure resources across the multiple layers and identifying the security vulnerability related to the infrastructure resources. The method further includes evaluating perceived criticalities of first and second new patches for the security vulnerability based a workload weightage, a resource age of the infrastructure resources, and an actual criticality of the first and second new patches. Further, the method includes installing the first new patch followed by the second new patch on the infrastructure resources based on the perceived criticalities, in an order of the determined dependency.

Workload aware security patch management

A system to facilitate data center security is described. The system includes a processor and a machine readable medium storing instructions that, when executed, cause the processor to receive a plurality of resources that are to be provided to process a workload, receive one or more characteristics associated with each of the plurality of resources, generate a resource signature for each of the plurality of resources using the one or more characteristics associated with each resource and generate an aggregated signature using the resource signatures generated for each of the plurality of resources.

Data center security mechanism

In an example, a first number of events associated with a first event type that are received in the first time window is compared against a first threshold. The first event type is one of a plurality of event types, and each event type corresponds to an amount of resource consumed by an event associated with the event type. It is detected whether events associated with the first event type received in the first time window are part of an event storm based on the first number of events and the first threshold.

Detection of event storms

Example techniques for obtaining data for identifying a fault are described. In response to receiving a fault message corresponding to a first device, a computing device determines a first set of data to be obtained for identifying the fault. The first set of data to be obtained is determined based on a workload of the computing device. The first set of data is then obtained.

Obtaining data for fault identification

Examples described herein relate to method and system for managing events received from network devices. A management station may receive events from the network devices. Further, the management station may determine a delay based at least on a rate at which the events are received at the management station. Moreover, the management station may schedule processing of the events based on the delay.

Management of events received from network devices

In an example, a first graph representing a first set of combinations of computing elements and logical elements used in a computing environment is compared with a second set of combinations of computing elements and logical elements. The first set of combinations includes a plurality of element combinations. The comparison may be performed to identify a potentially faulty element combination among the first set of combinations.

Computing element failure identification mechanism

Example approaches for remote deployment of an operating system (OS) in an electronic device are described. In an example, a Baseboard Management Controller (BMC) of the electronic device is set as a first bootable component in an order of initialization of hardware components of the electronic device during a boot operation. The BMC is initialized during the boot operation. A remote server information indicative of a network address of a remote server and a path directed to boot files of the OS stored in the remote server is received. The boot files are for deployment of the OS in the electronic device. The boot files from the remote server are downloaded over a dedicated communication channel associated with the BMC, based on the remote server information. The boot files are executed to deploy the OS in the electronic device.

Remote deployment of operating systems

In an example, suspect scores for impacting elements that can cause an error state of a first element are computed. The computation is performed based on states of each element for which the impacting element can cause the error state.

Determination of cause of error state of elements in a computing environment based on an element's number of impacted elements and the number in an error state

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Bengaluru, India

Naveena Kedlaya