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application might function flawlessly when running with
a few careful testers who exercise it in the intended
manner. However, when a large number of users are introduced,
the application is likely to slow down, encounter functionality
problems or crash altogether. Applications need to be
tested for it s performance in testing conditions.
Performance testing is the process of exercising an
application with multiple users and verifying whether
it functions correctly under anticipated traffic levels,
patterns and combinations. Performance testing helps
organizations understand how the system will fare in
real-life situations in terms of load-related problems
which could be anticipated and mitigated.
Kumaran approach towards performance testing is not
limited to merely stressing the application. We follow
a more comprehensive, end-to-end approach that is targeted
at bottleneck identification and performance fine-tuning.
We are therefore able to detect bottlenecks right down
to the code level and significantly improve an application's
scalability often without any hardware upgrades. We
first identify various parameters that govern the execution
of a test run. The test entry and exit criteria are
identified and documented. Preliminary test runs are
conducted to tune the performance parameters of the
various servers (application server, database server
and web server) in the architecture.
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Kumaran performance
solutions provide intelligent virtual users and sophisticated
ready-to-run load test scenarios that realistically
simulate user requests. Users can select preset or customize
load test scenarios. Preset scenarios include bell curve,
buffer test, linear increase and steady load.
The solutions do not simply look at the response time
and rates delivered for various load scenarios; rather,
they run tests that define and measure what problems,
in addition slow load times and rates, might occur in
different situations. These tests identify load scenarios
that can cause problems such as bottlenecks, transactions
that are slow or do not execute correctly and pages
that are slow or do not load correctly.
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| Approach |
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| Benchmarking |
The key to benchmark
testing is to have consistently reproducible results.
Results that are reproducible allow you to do
two things: reduce the number of times you have
to return those tests; and gain confidence in
the product you are testing and the numbers you
produce. |
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| Capacity Planning |
For capacity-planning type
tests, your goal is to show how far a given application
can scale under a specific set of circumstances.
The goal is to find out how many concurrent users
the system can support below a certain server
response time. |
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| Soak Tests |
A soak test is a straightforward
type of performance test. Soak tests are long-duration
tests with a static number of concurrent users
that test the overall robustness of the system.
These tests will show any performance degradations
over time via memory leaks, increased garbage
collection (GC), or other problems in the system.
The longer the test, the more confidence in the
system you will have.
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| Peak-Rest Tests |
Peak-rest tests determine
how well the system recovers from a high load
(such as one during peak hours of the system),
goes back to near idle, and then goes back up
to peak load and back down again. |
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| Benefits |
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Our performance testing
services will address performance issues in your application,
by testing under simulated, realistic user load conditions
and common project constraints. The benefits of performance
testing services are |
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- Provide confidence in the applications performance
before deployment, with objective data to support
a go/no-go decision (for example the end user response
times)
- Determine the scalability of the application and
the capacity levels that the application can achieve
- Identify performance issues and bottlenecks and
their causes. Where needed, provide detailed evidence
that will speed up the resolution of problems
- Establish performance baseline for service measurement,
provide critical information prior to launch to optimize
infrastructure and support successful service operation
management (for example failure behavior beyond performance
boundaries)
- Monitor critical indicators so you are quickly aware
of any changes to your expected levels of performance.
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