Information Technology Reference
In-Depth Information
A significant strength of OSV is its efficient use of resources. This efficiency
applies to the use of CPU time, RAM, and virtual memory.
When implemented correctly, OSV will not add any CPU overhead compared
to a consolidated but non-virtualized system. The OS must still perform the same
operations for that set of running applications. However, to perform well with
more than three or four VEs, the OS must be scalable —that is, able to switch
the CPU(s) among the dozens or hundreds of processes in the VEs. It must also
be able to efficiently manage the many gigabytes of RAM and swap space used by
those processes.
Because OSV VEs do not have a separate OS instance, they do not consume
hundreds of megabytes of RAM per VE for each OS kernel. Instead, the amount of
RAM needed for multiple VEs typically is limited to the memory footprint of the
underlying OS plus the amount of RAM used by each of the consolidated applica-
tions. In some implementations, operating systems that reuse a program's text
pages can reduce the memory footprint of a VE even further by sharing those text
pages across VEs.
Because of the single OS instance of OSV, a centralized point exists for security
controls. This arrangement also creates the possibility of per-VE configurable se-
curity and centralized auditing, a topic discussed in Chapter 6.
OSV implementations have a primary goal of minimizing the effort needed to
maintain many operating systems in a data center environment. Put simply, fewer
OS instances means less activity installing, configuring, and updating operating
systems. Because the OS is already installed before a VE is created, provisioning
VEs is usually very rapid, taking anywhere from a few seconds to a few minutes.
The minimalist nature of OSV also reduces the time to boot a VE—if that step is
even needed—to a few seconds.
1.2.3.9 Industry Examples
Early examples of OS virtualization include Oracle Solaris Containers, HP-UX
Secure Resource Partitions, Linux VServers, and AIX Workload Partitions. Each
of these products follows the model described earlier, with differences reflecting
their use of network and storage I/O, security methods and granularity, and re-
source controls and their granularity.
Server consolidation improves data center operations by reducing the number of
servers, which in turn reduces hardware acquisition costs, hardware and software
support costs, power consumption, and cooling needs. Virtualization enables con-
solidation of workloads that might interfere with one another, and of workloads
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