Vmware, Inc.

Samuel P McBride

Somik Behera

Justin Pearson Smith

Rachil Chandran

Gurudutt Maiya Belur

A method includes determining a capacity model that configures computing resource capacity for a capacity container. The method also includes estimating an available capacity in a capacity container based on a capacity of host devices in the capacity container. The method also includes generating, based on a selection of a visualization method, a visualization of a trend curve and a forecast curve, the trend curve representing historical capacity usage of the host devices. Implementations may include selecting an average virtual machine unit display or a raw units display and determining an average virtual machine based on averaging an attribute of one or more virtual machines.

Capacity and load analysis using storage attributes

A capacity-analysis tool (CAT) provides a model framework for creating a model of a capacity-planning-target (CPT) system, e.g., a data center. The tool includes a model framework that, in turn, includes a closed-system template for creating CSMs, i.e., models of capacity-limited systems. A user uses the CAT to create CPT models using the CSMs as building blocks. A machine-learning engine is used to train the CPT model, converting parameter time-series data to functions of time. The trained CPT models are then used to make capacity-planning estimates, e.g., time remaining on a system before usage matches capacity. The CAT makes it easy to extend a model, e.g., by adding new dimensions (new factors of interest) in the form of new CSMs to which the new dimensions have been assigned.

Capacity analysis using closed-system modules

A method includes determining a capacity model that configures computing resource capacity for a capacity container. The computing resource capacity includes a first storage attribute for an amount of storage in a storage component. A load model is determined that configures load for the capacity container. The load includes a second storage attribute for a storage requirement for a virtual machine. A profile of a virtual machine unit is determined for estimating available capacity in a capacity container. The profile is determined using virtual machine attributes for a set of virtual machines, wherein the virtual machine unit includes a storage requirement based on storage requirements for the set of virtual machines. The profile of the virtual machine unit is fit into available capacity. A number of virtual machine units is determined based on the fitting, the number of virtual machine units being a measure of available capacity.

One or more embodiments provide methods of creating datacenter capacity and/or load models for a datacenter in a virtualized environment; methods of simulating the capacity and/or load models ('What-if' simulations); and methods of visualizing simulation results for assessing the impact of the capacity and/or load models on the datacenter capacity.

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San Jose, CA, United States of America

Samuel P McBride