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Cloud Computing and SOA Convergence in Your Enterprise: A Step ...

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Analyze <strong>and</strong> Test C<strong>and</strong>idate Platforms 209<br />

both on-premise systems, which most do, <strong>and</strong> cloud comput<strong>in</strong>g–based systems,<br />

which only a few do well. Moreover, you should check whether the cloud<br />

provider has an <strong>in</strong>terface on their software that allows management technology<br />

to talk to it.<br />

The core idea is to provide a management platform that sees all onpremise<br />

<strong>and</strong> cloud comput<strong>in</strong>g–based systems at the “work<strong>in</strong>g or not work<strong>in</strong>g”<br />

level, at the very least, mean<strong>in</strong>g we can see whether a system is down<br />

<strong>and</strong> how that status will affect other systems <strong>in</strong> the architecture. However, it<br />

is preferable to have a management system that can see systems such as services,<br />

processes, data, storage at more granular levels, which makes it much<br />

easier to diagnose issues <strong>and</strong> spot troubles before they happen.<br />

Management <strong>and</strong> governance are clearly l<strong>in</strong>ked <strong>and</strong> have very similar<br />

patterns.<br />

Analyze <strong>and</strong> Test C<strong>and</strong>idate Platforms<br />

Once you select the c<strong>and</strong>idate cloud comput<strong>in</strong>g platforms, you need to make<br />

sure they live up to the requirements we established. You do this through<br />

some deep dives <strong>in</strong>to each c<strong>and</strong>idate platform you selected <strong>and</strong> then through<br />

test<strong>in</strong>g.<br />

We covered test<strong>in</strong>g extensively <strong>in</strong> Chapter 9, “Test<strong>in</strong>g from <strong>SOA</strong> to the<br />

<strong>Cloud</strong>s,” so we do not go too deep <strong>in</strong>to it here. However, this test<strong>in</strong>g is a bit<br />

different <strong>in</strong> that you are actually test<strong>in</strong>g the generic capabilities of the cloud<br />

comput<strong>in</strong>g platform. Specifically, you look at how that cloud comput<strong>in</strong>g<br />

platform will support the requirements of the architectural components, <strong>in</strong>clud<strong>in</strong>g<br />

services, data, <strong>and</strong> processes, but you are not yet deploy<strong>in</strong>g on those<br />

platforms. They could be the wrong choices, which is why we do the test<strong>in</strong>g.<br />

The only th<strong>in</strong>g to add from Chapter 9 is the use of performance model<strong>in</strong>g<br />

<strong>and</strong> performance test<strong>in</strong>g. Model<strong>in</strong>g creates a simulation of how the system<br />

should perform under different types of loads, typically light, medium,<br />

<strong>and</strong> heavy. Performance test<strong>in</strong>g determ<strong>in</strong>es how the architecture performs<br />

under stress. It <strong>in</strong>volves model<strong>in</strong>g the architecture, <strong>in</strong>clud<strong>in</strong>g how the <strong>in</strong>formation<br />

will flow <strong>and</strong> the services will be <strong>in</strong>voked, <strong>and</strong> how flow <strong>and</strong> <strong>in</strong>vocation<br />

affect the different comput<strong>in</strong>g resources, both on-premise <strong>and</strong> cloudbased.<br />

You should have a general idea as to what performance you can expect<br />

from the cloud comput<strong>in</strong>g platforms <strong>and</strong> how th<strong>in</strong>gs such as decreas<strong>in</strong>g process<strong>in</strong>g<br />

power or exp<strong>and</strong><strong>in</strong>g b<strong>and</strong>width should affect overall performance.

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