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Traditional computing systems mostly follow static resource provisioning approach. But, it is
very difficult to correctly predict the future demand of any application (and hence the resource
requirement for the application) despite rigorous planning and efforts. This naturally results in
under-provision or over-provision of resources in traditional environment.
When demand for computing resources crosses the limit of available resources, then a
shortage of resource is created. This scenario is known as under-provision of resource. A simple
solution to this problem is to reserve sufficient volume of resources for an application so that
resource shortage can never happen. But this introduces a new problem. In such case, most
of the resources will remain unutilized for majority of time. This scenario is known as over
provision of the resources.
Under-provisioning problem occurs when the reserved resources are unable to fully meet the
demand.
Figure 8.9 shows the under-provision scenario. Here, the allotted and defined volume of resource
is represented by the dashed line. Under-provisioning problem occurs when resource demand
of application is higher than this allotted volume. Under-provisioning causes application
performance degradation.
The over-provisioning problem appears when the reserved volume of resource for an
application never falls below the estimated highest-required amount of resource for the
application considering the varying demand. In such case, since for most of the time, the
actual resource demand remains quite lesser than the reserved amount it ultimately turns into
un-utilization of valuable resource. This not only causes wastage of resource but also increases
the cost of computation. Figure 8.10 represents the scenario.
Resource over-provisioning problem occurs when the reserved resources remain unused for
most of the time.
Figures 8.9 and 8.10 exhibit the problem of the traditional fixed-size resource allocation
approach. It tends to increase cost or provides poor performance outcomes. In cloud computing,
the fine-tuned dynamic or hybrid resource provisioning approaches are used to deliver high
performance at low cost.
While over-provisioning wastes costly resources, under-provisioning degrades application
performance and causes business loss.
The static provisioning approach causes the trouble for vendors also. Vendors meet consumer’s
SLA requirements through resource over-provisioning in order to meet worst case demands.
However, since application demand remains low most of the time resource utilization rate
also remains low. This restricts the vendors to deliver services at lower cost. Cloud computing
addresses this issue by dynamic provisioning of resources using virtualization.
Traditional computing systems mostly follow static resource provisioning approach. But, it is
very difficult to correctly predict the future demand of any application (and hence the resource
requirement for the application) despite rigorous planning and efforts. This naturally results in
under-provision or over-provision of resources in traditional environment.
When demand for computing resources crosses the limit of available resources, then a
shortage of resource is created. This scenario is known as under-provision of resource. A simple
solution to this problem is to reserve sufficient volume of resources for an application so that
resource shortage can never happen. But this introduces a new problem. In such case, most
of the resources will remain unutilized for majority of time. This scenario is known as over
provision of the resources.
Under-provisioning problem occurs when the reserved resources are unable to fully meet the
demand.
Figure 8.9 shows the under-provision scenario. Here, the allotted and defined volume of resource
is represented by the dashed line. Under-provisioning problem occurs when resource demand
of application is higher than this allotted volume. Under-provisioning causes application
performance degradation.
The over-provisioning problem appears when the reserved volume of resource for an
application never falls below the estimated highest-required amount of resource for the
application considering the varying demand. In such case, since for most of the time, the
actual resource demand remains quite lesser than the reserved amount it ultimately turns into
un-utilization of valuable resource. This not only causes wastage of resource but also increases
the cost of computation. Figure 8.10 represents the scenario.
Resource over-provisioning problem occurs when the reserved resources remain unused for
most of the time.
Figures 8.9 and 8.10 exhibit the problem of the traditional fixed-size resource allocation
approach. It tends to increase cost or provides poor performance outcomes. In cloud computing,
the fine-tuned dynamic or hybrid resource provisioning approaches are used to deliver high
performance at low cost.
While over-provisioning wastes costly resources, under-provisioning degrades application
performance and causes business loss.
The static provisioning approach causes the trouble for vendors also. Vendors meet consumer’s
SLA requirements through resource over-provisioning in order to meet worst case demands.
However, since application demand remains low most of the time resource utilization rate
also remains low. This restricts the vendors to deliver services at lower cost. Cloud computing
addresses this issue by dynamic provisioning of resources using virtualization.