BACKGROUND

The present disclosure relates generally to information handling systems, and more particularly to reserving resources for workloads provided in information handling systems based on performance capabilities of media module partitions provided in a media module that includes a plurality of media devices.

As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.

Information handling systems are sometimes provided in a Hyper-Converged Infrastructure (HCl) systems that may be provided by a software-defined Information Technology (IT) infrastructure that virtualizes the elements of “hardware-defined” systems using, for example, virtualized computing subsystems (e.g., a hypervisor subsystem), a virtualized Storage Area Network (SAN) (e.g., “software-defined storage”), and virtualized networking (e.g., “software-defined networking”) provided on one or more server devices. HCl systems have evolved from conventional discrete, hardware-defined systems that are connected and packaged together to a software-defined environment in which the functional elements are provided via server device(s) and converged via a hypervisor.

In some situations, HCl systems may implement a composable computing architecture (e.g., the Gen-Z composable computing architecture) that includes compute modules that each include various processing systems, media modules that each include one or more memory and/or storage devices, and a switch that provides communications between the compute modules and the media modules. It is often desirable to utilize the shared operating environment provided in HCl systems implementing a composable computing architecture in order to perform multiple workloads, but doing so raises a number of issues.

For example, a media module may include a plurality of storage devices that may be provided by one or more different types of storage devices such as, Hard Disk Drives (HDD), Solid State Drives (SSD), Non-Volatile Memory express (NVMe), Persistent MEMory (PMEM), Storage Class Memory (SCM), or other storage devices that one of skill in the art will recognize exhibit performance variations relative to each other. Furthermore, even storage devices of the same storage device type can exhibit performance variation relative to each other. Such storage performance variations can cause issues due to the fact that HCl systems do not guaranteed media module performance, which tends to result in workloads with storage requirements being provided on dedicated server devices/systems, rather than having those workloads performed/provided using HCl systems implementing a composable computing architecture that also operates to provide other workloads (i.e., because the HCl system cannot guarantee storage reserved to a workload will meet workload performance requirements for that workload. Thus, when aggregated payloads are provided from workload(s) to an HCl storage system (e.g., via the media module), the HCl storage system may drop the session associated with those payloads, fail to perform the payload transaction, and/or operate in some other manners that can results in a failure to satisfy resource requirements/performance for those workloads. As would be appreciated by one of skill in the art in possession of the present disclosure, the inability to guarantee workload performance requirements by HCl systems limits their utilization in situations where the HCl system is fully capable of providing the workload.

Accordingly, it would be desirable to provide an improved workload/resource reservation system.

SUMMARY

According to one embodiment, an Information Handling System (IHS) includes a processing system; and a memory system that is coupled to the processing system and that includes instructions that, when executed by the processing system, cause the processing system to provide a media controller engine that is configured to: retrieve performance attributes from each of a plurality of media devices in a media module; determine one or more media module partitions that are included in the media module and that have been guaranteed a respective performance level, wherein each of the one or more of media module partitions are provided by a subset of the plurality of media devices; determine, for each of the one or more media module partitions, a minimum partition performance for that media module partition based the performance attributes for the subset of the plurality of media devices that provide that media module partition; and provide the minimum partition performance for each of the plurality of media module partitions to a Hyper-Converged Infrastructure (HCl) resource reservation system.

