System and method for structuring self-provisioning workloads deployed in virtualized data centers

a workload and workload technology, applied in the field of system and method for structuring self-provisioning workloads deployed in virtualized data centers, can solve the problems of insufficiently addressing the concerns relating to managing or controlling workloads and storage in such environments, the inability to compute and finance the cost of any particular service, and the inability to adequately address the concerns relating to performance, latency, reliability, security, etc., to achieve the effect of enhancing portability of managed workloads

Active Publication Date: 2012-03-01
SUSE LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The present invention provides a way to manage large amounts of computing power at different levels in a virtualized data center by adding intelligence and embedding policies into these worksheets. This helps improve their flexibility and mobility across multiple locations. It also includes a mechanism where each job on an individual's own machine has its own set of rules or settings. Overall, this technology allows for efficient use of computer hardware and software resources while ensuring they are properly configured and controlled.

Problems solved by technology

This patent describes a problem where managing large amounts of workloads distributed across different types of computer networks requires careful consideration by both the data center manager and the virtual machine manager. These issues involve the difficulty of effectively assigning and adjusting resources based on their respective needs, particularly when migrated between different locations due to changes in availabilities or costs. Existing solutions like traditional methods rely heavily on manual input and monitoring, but they suffer from limitations such as limited scalability and lack of visibility into the underlying infrastructure.

Method used

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  • System and method for structuring self-provisioning workloads deployed in virtualized data centers
  • System and method for structuring self-provisioning workloads deployed in virtualized data centers
  • System and method for structuring self-provisioning workloads deployed in virtualized data centers

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Embodiment Construction

[0017]According to one aspect of the invention, FIG. 2 illustrates an exemplary system 200 that can be used to structure a self-provisioning workload 240 deployed in virtualized data centers. In particular, the system 200 illustrated in FIG. 2 may provide a scalable architecture that can inject intelligence and embed policies into the self-provisioning workload 240, whereby the system 200 may generally be used to provision and tune physical hardware and hypervisor resources 230 allocated to the workload 240 in the cloud and virtualized data centers. As such, the scalable architecture provided in the system 200 may enhance portability for the managed workload 240 across various cloud and virtualized data centers. In one implementation, the self-provisioning workload 240 may be structured for management in various dimensions to provide “intelligent workload management” over various attributes associated with the self-provisioning workload 240.

[0018]For example, to provide the “intelligen

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Abstract

The system and method for structuring self-provisioning workloads deployed in virtualized data centers described herein may provide a scalable architecture that can inject intelligence and embed policies into managed workloads to provision and tune resources allocated to the managed workloads, thereby enhancing workload portability across various cloud and virtualized data centers. In particular, the self-provisioning workloads may have a packaged software stack that includes resource utilization instrumentation to collect utilization metrics from physical resources that a virtualization host allocates to the workload, a resource management policy engine to communicate with the virtualization host to effect tuning the physical resources allocated to the workload, and a mapping that the resource management policy engine references to request tuning the physical resources allocated to the workload from a management domain associated with the virtualization host.

Description

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Claims

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Application Information

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Owner SUSE LLC
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