Recently there passed across my desk a white paper sponsored
by Parasoft about the idea of applying what they called “service
virtualization” to software testing.
Ordinarily, I find that “we’ve been there and done that” for much of the
material in most of the white papers like this that I see. In this case, however, I think that the idea
Parasoft describes is (a) pretty new, (b) applicable to many
software-development situations, and (c) quite valuable if effectively done.
The Problem
The problem to be solved, as I understand it – and my own
experience and conversations with development folks suggests that it does
indeed happen frequently these days – is that in the later stages of software
testing, of dependency and volume testing shortly before version or product
deployment, one or more key applications not involved in the software
development or upgrade but with “interaction effects” is effectively
unavailable for testing in a timely fashion. It may be a run-the-business ERP
application for which stress testing crowds out the needed customer-transaction
processing. It may be a poorly
documented mission-critical legacy application for which creating a “sandbox”
is impractical. You can probably think of many other cases.
In fact, I think I ran across an example recently. It went like this: a software company selling a customer-facing
application started up about five years ago.
Over five years of success, they ran that customer-facing application
24x7, with weekly maintenance halts for a couple of hours and 4-6-hour halts
for major upgrades. All very nice, all
very successful, as revenue ramped up nicely.
Then (reading between the lines), recently they realized
that they had not upgraded their back-end billing and accounting systems that
fed off the application, and these were increasingly inefficient and causing
problems with customer satisfaction. So
they tested the new solutions in isolation in a “sandbox”, and then scheduled a
full 12 hours of downtime on the app to install the new solutions – without
“sandboxing” the back-end and front-end solutions working together first.
Everything apparently went fine until they started up a
“test run” of the back-end and front-end solutions working in sync. At that point, not only did the test fail,
but it also created problems with the “snapshot” of front-end data that they
had started from. So they had to
repeatedly reload the start point and do incremental testing on the back-end
systems. In the end, they took more than two days (complete with anguished
screams from customers) to add some changes to back-end systems and make the
customer-facing application available again; and it took several more days
before the rest of the back-end systems were available in the new form. As the
white paper notes, in planning final testing of new software, companies can
often be willing to skip integration testing involving interdependent unchanged
software; and the consequences can be quite serious.
The Idea
Probably to cash in on the popularity of “virtualization”,
the white paper calls the idea proposed to deal with this problem “service virtualization.” To my eyes, the best description is
“script-based dependent software emulation.” In other words, to partially
replace the foregone testing, service virtualization would allow you to create
a “veneer” that would, whenever you invoke the dependent software during your
integration testing, spit back the response that the dependent software should give. This particular solution
provides two ways of creating the necessary “scripts” (my categorization, not
Parasoft’s):
1.
Build a model of how the dependent software
runs, and invoke the model to generate the responses; and
2.
Take a log of the actions of the dependent
software during some recent period, and use that information to drive the
responses.
Before I analyze what this does and does not do, let me note
that I believe Approach #2 is typically the way to go. The bias of an IT
department considering skipping the dependent-software integration testing step
is towards assuming that there will be no problems. The person building the model will therefore often
implicitly build it the way the dependent software would work if there really
were no problems – and response times are often guesstimates. The log of actual actions introduces a needed
additional note of realism into the testing.
However, the time period being logged almost inevitably does
not capture all cases – end-of-year closing, for example. The person creating the “virtualized service”
should have a model in mind that allows him or her to add the necessary cases
not covered by the log.
Gains and Limits
The “service virtualization” idea is, I believe, a major
advance over the previous choice between a major disruption of online systems
and a risk of catastrophic downtime during deployment. If one takes Approach #2
as described above, “service virtualization” will add very little on to testing
time and preparation, while in the vast majority of cases it will detect those
integration-test problems that represent the final barrier to effective testing
before deployment. In other words, you
should be able to decrease the risk of software introduction crashes tenfold or
a hundredfold.
The example I cited above is a case in point. It would have taken fairly little effort to
use a log of customer-facing app interactions in a sandbox integration test
with the new back-end systems. This
would also have speeded up the process of incremental testing of the new
software once a problem was detected.
There are limits to the gains from the new testing approach
– although, let’s note up front that these do not detract in the slightest from
the advantages of “service virtualization”.
First, even if you take Approach #2, you are effectively doing
integration testing, not
volume/stress testing. If you think
about it, what you are mimicking is the behavior of the “dependent” software
before the new systems are introduced.
It is possible, nay, likely, that the new software will add volume/stress to the other software
in your data center that it interacts with.
And so, if the added stress does cause problems, you won’t find out
about it until you’re operating online and your mission-critical software slows
to a crawl or crashes. Not very likely;
but still possible.
Second, it is very possible that there will be a lag time
between the time when you capture the behavior of the “dependent” software and
the time that you run the tests. It is
fairly simple to ensure that you have the latest and greatest version of
“dependent” software with the latest bug fixes, and to keep track of whatever
changes happen online during sandbox testing offline. If you are just
periodically refreshing the log “snapshot” as in Approach #2, or even operating
from a model written a year ago, as happens all too often, then there is a real
possibility that you have missed crucial changes to the “dependent” software
that will cause your integration testing to succeed and then your deployment to
crash. Luckily, ex-post analysis of dependent-software changes makes fixing
this problem much easier – but it should be minimized by straightforward monitoring
of operational-dependent-software mods during testing.
The Bottom Line for Parasoft and “Service Virtualization” Testing: Worth Looking At Right Now
The Parasoft solution appears to apply especially to IT
shops with significant experience with “skipping” integration testing due to
“dependent software”, and with a reasonably sophisticated test harness. Of course, if you don’t have a reasonably
sophisticated test harness that can do integration testing of new software and
other operational systems in your environments, perhaps you should consider
acquiring one. I suspect that the case I
cited earlier not only failed to sandbox integration testing, but didn’t have
the test harness to do so even had they wanted to.
For those IT shops fitting my criteria, there seems no real
reason to wait to kick the tires of, and probably buy, additional “service
virtualization” features. As I said, the
downside in terms of added test time and effort in these cases appears minimal,
and the gains from the additional software robustness clear, and potentially
company-reputation-saving.
I will, however, add one note of caution, not about the
solution, but about your strategy in using it.
Practically speaking, “service virtualization” is rarely if ever to be
preferred to full integration testing, if you can do it. It would be a very bad idea to use the new
tools to move the boundary between what is fully tested, because you can manage
it in a reasonable time, and what is quicker and easier but risks
disaster. Do use “service virtualization” to replace naked “close your eyes
and hope” deployment; don’t use
“service virtualization” to replace an existing thorough integration test.
Kudos to Parasoft for marketing such a good idea. Check it out.
3 comments:
This was a great read.
Its really informative, highlighted point and other facts given here are quite considerable and to the point as well, would be better to look for more of these kind for efficient results.
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