Many customers are unaware of the opportunities that exist to improve levels of service and overall delivery, and reliably increase the percentage of applications being deployed.
This cannot typically be revealed through a short consulting engagement. Diverse performance and configuration data must be collected and analysed in order to draw any reasonable conclusions.
Coming up with the best set of recommendations to optimise the performance and efficiency of a virtual infrastructure for now and in the future is complex. Virtualised applications share servers and storage, and each virtualised app has different resource consumption characteristics as well as configuration constraints.
Where there are even just a few virtual machines (VMs), thousands of data points must be analysed to make meaningful decisions. And this challenge cannot reliably or solely be addressed using manual techniques.
A far better way to approach this is using intelligent workload management software that incorporates a mathematical approach, designed for evaluating the broad set of performance and configuration constraints that will help resource allocation decisions.
The actions that result from this constraints-based analysis should enable you to determine the right size of the physical server and storage infrastructure, as well as locate workloads optimally across server and storage resources and identify VM configuration issues, such as incorrect provisioning.
Intelligent workload management products can be deployed quickly even in complex environments, enabling users to highlight any issues constraining workloads or applications as well as recommend solutions within hours.
As more data is collected, users will see ways to improve the overall efficiency of their environment through waste reduction and better VM management and utilisation. Specific reports can highlight dormant VMs, VMs where vMem, vCPU or storage allocation can be reduced, and files that no longer need to be associated with a VM.
Workload management apps may also provide simulation capabilities that help users model changes to client environments. They can determine the impact of migrating to new or higher-performance hardware, changes in existing workload characteristics, adding new applications or workloads, or simulate disaster or failure situations.
The outcome of these scenarios is a precise picture of how much server and storage capacity is required to meet the workload demand. Goals can be set for the analysis, and a plan made for server and storage optimisation.
This can unlock new project revenue. Examples might include further investments in infrastructure, software licences, consultancy, or delivery-based services.
Andrew Mallaband is business development director at VMTurbo
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