A publish and subscribe architecture can be utilized to manage records, which can be used to accomplish the various functional goals. At least one template having definitions for managing production and consumption of data within an unconfigured group of computing resources is maintained. Records organized by topic collected from multiple disparate previously configured producers are utilized to initiate configuration of the unconfigured group of computing resources. Records within a topic are organized by a corresponding topic sequence. A first portion of the computing resources are configured as consumers based on the at least one template. The consumers to consume records at a pace independent of record production. A second portion of the computing resources are configured as producers based on the at least one template. The producers to produce records at a pace independent of record consumption.

A request manager analyzes API calls from a client to a host application for state and performance information. If current utilization of host application processing or memory footprint resources exceed predetermined levels, then the incoming API call is not forwarded to the application. If current utilization of the host application processing and memory resources do not exceed the predetermined levels, then the request manager quantifies the processing or memory resources required to report the requested information and determines whether projected utilization of the host application processing or memory resources inclusive of the resources required to report the requested information exceed predetermined levels. If the predetermined levels are not exceeded, then the request manager forwards the API call to the application for processing.

A method for performance tuning in Automated Machine Learning (Auto ML) includes obtaining preset application program interface and system resources of the automatic machine learning system. Performance index measurement values are obtained according to the preset application program interface when the system pre-trains deep learning training model candidates. A distribution strategy and a resource allocation strategy are determined according to the performance index measurement values and the system resources and computing resources of the system are allocated according to the distribution strategy and the resource allocation strategy. The disclosure also provides an electronic device and a non-transitory storage medium.

A method for performance tuning in Automated Machine Learning (Auto ML) includes obtaining preset application program interface and system resources of the automatic machine learning system. Performance index measurement values are obtained according to the preset application program interface when the system pre-trains deep learning training model candidates. A distribution strategy and a resource allocation strategy are determined according to the performance index measurement values and the system resources and computing resources of the system are allocated according to the distribution strategy and the resource allocation strategy. The disclosure also provides an electronic device and a non-transitory storage medium.

Systems described herein may allow for the intelligent configuration of containers onto virtualized resources. As described, systems described herein may generate configurations based on received parameters for utilization to configure (e.g., install, instantiate, etc.) virtualized resources. Once generated, a configuration may be selected according to determined selection parameters and/or intelligent selection techniques.

The disclosure herein describes managing multiple clusters within a container environment using a control cluster. The control cluster includes a single deployment model that manages deployment of cluster components to a plurality of clusters at the cluster level. Changes or updates made to one cluster are automatically propagated to other clusters in the same environment, reducing system update time across clusters. The control cluster aggregates and/or stores monitoring data for the plurality of clusters creating a centralized data store for metrics data, log data and other systems data. The monitoring data and/or alerts are displayed on a unified dashboard via a user interface. The unified dashboard creates a single representation of clusters and monitor data in a single location providing system health data and unified alerts notifying a user as to issues detected across multiple clusters.

Disclosed are various examples for platform independent graphics processing unit (GPU) profiles for more efficient utilization of GPU resources. A virtual machine configuration can be identified to include a platform independent graphics computing requirement. Hosts can be identified as available in a computing environment based on the platform independent graphics computing requirement. The virtual machine can be placed on a host based on a consideration of host priority.

A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

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.

An electronic device including an application processor and a communication processor. The communication processor including a resource memory, the communication processor configured to monitor an occupancy rate of the resource memory, determine whether the electronic device is in an idle state, forcibly release a network connection, clear the resource memory, and reconnect the network connection.