Method and apparatus for stress management in a searchable data service. The searchable data service may provide a searchable index to a backend data store, and an interface to build and query the searchable index, that enables client applications to search for and retrieve locators for stored entities in the backend data store. Embodiments of the searchable data service may implement a distributed stress management mechanism that may provide functionality including, but not limited to, the automated monitoring of critical resources, analysis of resource usage, and decisions on and performance of actions to keep resource usage within comfort zones. In one embodiment, in response to usage of a particular resource being detected as out of the comfort zone on a node, an action may be performed to transfer at least part of the resource usage for the local resource to another node that provides a similar resource.

Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

The present disclosure relates to a method and system for optimizing a parameter configuration of a distributed computing job. The method includes: obtaining job programs of different distributed computing jobs, and determining a key parameter configuration set; obtaining a cluster status during execution of the distributed computing job, randomly generating a sample data set based on the key parameter configuration set and the cluster status, and establishing a performance prediction model; correcting the performance prediction model by using a multi-objective genetic algorithm and an optimization module configured with an optimal configuration selection strategy; obtaining a job program of a to-be-optimized distributed computing job and a cluster status during execution of the to-be-optimized distributed computing job, and determining a to-be-optimized key parameter configuration item combination; and inputting, to the performance prediction model, the to-be-optimized key parameter configuration item combination and the cluster status during execution of the to-be-optimized distributed computing job, and outputting a key parameter configuration item combination with a shortest execution time. The present disclosure can rapidly and effectively optimize the key parameter configuration.

A blockchain-based interaction method and system for an edge computing service: using, as a bearing entity of an MECaaS, a device that has an environment for an operating system and that is of a user; registering a computing power device of the user as an edge node by using the MECaaS; uploading or updating registration information of the edge node to a blockchain layer; issuing, by a requesting device as a data producer, a computing task to the MECaaS; invoking, by the MECaaS, the smart contract deployed on the blockchain layer; standardizing a data format of the computing task; matching a target edge node for the requesting device; establishing an M2M communication between the requesting device and the target edge node, so that the requesting device can transmit raw data to the target edge node, and the target edge node can feed back a computing result to the requesting device.

A system of monitoring and optimizing computing resources usage for computing application may include predicting a first performance metric for job load capacity of a computing application for optimal job concurrency and optimal resource utilization. The system may include generating an alerting threshold based on the first performance metric. The system may further include, in response to a difference between the alerting threshold and a job load of the computing application within an interval exceeding a threshold, predicting a second performance metric for job load capacity of the computing application for optimal job concurrency and optimal resource utilization. The system may further include, in response to a difference between the first performance metric and the second performance metric exceeding a difference threshold, updating the alerting threshold with a job load capacity with the optimal resource utilization rate corresponding to the second performance metric.

In one or more embodiments, one or more systems, one or more methods, and/or one or more processes may determine first thermal attribute values associated with multiple information handling systems (IHSs) with respect to a period of time as the IHSs execute a first workload; determine multiple variance ranges respectively associated with the first thermal attributes; periodically determine second thermal attribute values associated with the IHSs as the IHSs execute a second workload; determine that a thermal attribute value of the second thermal attribute values exceeds a respective variance range of the variance ranges as a first information handling system (IHS) of the IHSs executes the second workload; generate an alert based at least on the thermal attribute value exceeding the respective variance range; and in response to the alert, transfer at least a portion of the second workload from the first IHS to a second IHS of the IHSs.

A computer-implemented method, according to one embodiment, includes: receiving, at a computer, a request to facilitate a testing environment, where the request specifies a number and type of resources to be included in the testing environment. A database which lists available resources in systems and/or devices that are in communication with the computer is inspected and the available resources are compared to the number and type of resources specified in the request to be included in the testing environment. In response to determining that a valid combination of the available resources meets the number and type of resources specified in the request to be included in the testing environment, the database is updated to indicate that each of the resources in the valid combination are in use. Moreover, the request is satisfied by returning information about the resources in the valid combination.

Systems and methods for universal auto-scaling are disclosed. In one embodiment, a method may include: (1) monitoring, by an auto-scale computer program executed by a computer processor, a utilization level at each of a plurality of data layers in a data pod, wherein each data layer comprises at least one node; (2) comparing, by the auto-scale computer program, each of the utilization levels to a threshold; (3) identifying, by the auto-scale computer program, that one of the thresholds is met or exceeded; and (4) deploying, by the auto-scale computer program, an additional node to the data layer with the met or exceeded utilization level.

To more properly size resources in a destination to which IT resources will be migrated, a system for appraising a resource configuration estimates a source's load model representing a load of first resources in a first computer system which is the source of migration and estimates a destination's load model representing a load of second resources to be built by migrating the first resources to a second computer system based on the source's load model. The system compares performance requirements of the first resources against the destination's load model and finds the destination's load model that is conformable to the performance requirements. When determining design values of the second resources' configuration, the system corrects those design values based on the destination's load model estimated conformable to the performance requirements to decrease design margins of the resource configuration using a design correction value defined to meet a service level requested.

Disclosed herein are systems and method for gradually updating software object instances on a plurality of computer nodes. In an exemplary aspect, in response to receiving a notification from a software object instance, a system may register the software object instance at an update server. The system may store and deploy a plurality of links, wherein each deployed link uniquely corresponds to a registered software object instance. The system may then associate two or more subsets of the plurality of links with two or more update locations, in accordance with an update policy. The system may place an update to the software object instance at the two or more update locations in accordance with an update policy. In response to receiving an update request via a link from a computing node, the system may further redirect the update request to an update location associated with the link.