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Set screen Forms/Types of Performance Testing/Engineering

09/12/2005 "Approaches to Performance Testing" by Matt Maccaux

Set screen Accomplishments

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A. Speed Tests
(for Responsiveness)

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During speed testing, the user response time (latency) of each user actionon this page is measured.

The script for each action will look for some text on each resulting page to confirm that the intended result appears as designed.

Since speed testing is usually the first performance test to be performed, issues from installation and configuration are identified during this step.

Because this form of performance testing is performed for a single user (under no other load), this form of testing exposes issues with the adequacy of CPU, disk I/O access and data transfer speeds, and database access optimizations.

The performance speed profile go to another page on this site of an application obtained during speed testing include the time to manually start-up and stop the application on its servers.

  1. Identified the business processes under test.
  2. Documented each user actionon this page to be measured.
  3. Documented production installation configuration instructions and settings.
  4. Quantified the start-up, shut-down, and user GUI transaction response (latency) times when the system is servicing only a single user at a time (under no other load) in order to determine whether they are acceptable.
  5. Ensured CPU, disk access, data transfer speeds, and database access optimizations are adequate.
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B. ContentionTests (for Robustness)

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This form of performance test aims to find performance bottlenecks (such as lock-outs, memory leaks, and thrashing) caused by a small number of Vusers contending for the same resources.

Each run identifies the minimum, average, median, and maximum times for each action. This is done to make sure that data and processing of multiple users are appropriately segregated.

Such tests identify the largest burst (spike) of transactions and requests that the application can handle without failing. Such loads are more like the arrival rate to web servers than constant loads.

  1. Identified performance bottlenecks (such as lock-outs, memory leaks, and thrashing) caused by a small number of Vusers contending for the same resources.
  2. Ensured that data and processing of multiple users are appropriately segregated.
  3. Identified the largest burst (spike) of transactions and requests that the application can handle without failing. Such loads are more like the arrival rate to web servers than constant loads.
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C. Volume Tests (for Extendability)

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This form of performance testing makes sure that the system can handle the maximum size of data values expected.

These test runs measure the pattern of response time as more data is added.

These tests make sure there is enough disk space and provisions for handling that much data, such as backup and restore.

  1. Quantified the degradation in response time and resource consumption at various levels of simultaneous users. This is done by gradually ramping-up the number of Vusers until the system "chokes" at a breakpoint (when the number of connections flatten out, response time degrades or times out, and errors appear).
  2. Determined how well the number of users anticipated can be supported by the hardware budgeted for the application.
  3. Quantified the "Job flow balance" achieved when application servers can complete transactions at the same rate new requests arrive.
  4. Ensured that there is enough transient memory space and memory management techniques.
  5. Make sure that admission control techniques limiting incoming work perform as intended. This may include extent of response to Denial of Service (DoA) attacks.
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D. Stress / Overload
Tests (for Sustainability)

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This form of performance testing determines how well the number of users anticipated can be supported by the hardware budgeted for the application.

This is done by gradually ramping-up the number of Vusers until the system "chokes" at a breakpoint (when the number of connections flatten out, response time degrades or times out, and errors appear).

During tests, the resources used by each server are measured to make sure there is enough transient memory space and adequate memory management techniques.

This effort makes sure that admission control techniques limiting incoming work perform as intended. This includes detection of and response to Denial of Service (DoA) attacks.

  1. Quantified the degradation in response time and resource consumption at various levels of simultaneous users.
  2. Determined how well the number of users anticipated can be supported by the hardware budgeted for the application.
  3. Quantified the "Job flow balance" achieved when application servers can complete transactions at the same rate new requests arrive.
  4. Ensured that there is enough transient memory space and memory management techniques.
  5. Make sure that admission control techniques limiting incoming work perform as intended. This may include extent of response to Denial of Service (DoA) attacks.
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E. Fail-Over
Tests (for Resilience & Recoverability)

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This form of performance testing determines how well (how quickly) the application recovers from overload conditions.

For example, this form of performance testing ensures that when one computer of a cluster fails or is taken offline, other machines in the cluster are able to quickly and reliably take over the work being performed by the downed machine.

This means this form of performance testing requires multiple identical servers to be configured and using Virtual IP addresses accessed through a load balancer device.

  1. Determined whether the application can recover after overload failure.
  2. Measured the time the application needs to recover after overload failure.
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F. Spike
"Peak-Rest" or
"Daily" Tests

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This form of performance testing involves suddenly adding the maximum sustainable load and then returning to a lower level of load to determine whether the app can obtain memory quickly, and then release that memory when no longer needed.

Such runs can involve a "rendevous point" where all users line up to make a specific request at a single moment in time.

Such runs enable the analysis of "wave" effects through all aspects of the system.

Most importantly, these runs expose the efficacy of load balancing.

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  1. Determined — through suddenly adding and then completing transactions — that the app releases memory.
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F. Endurance
"Soak"
"Longevity"
Tests (for Reliability)

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This form of performance testing makes sure that the system can sustain -- over at least a 24 hour period -- a consistent number of concurrent Vusers executing transactions using near peak capacity.

Because longer tests usually involve use of more disk space, these test runs also measure the pattern of build-up in "cruft" (obsolete logs, intermediate data structures, and statistical data that need to be periodically pruned).

Longer runs allow for the detection and measurement of the impact of occasional events (such as Java Full GC and log truncations) and anomalies that occur infrequently.

These tests verifies provisions for managing space, such as log truncation "cron" jobs that normally sleeps, but awake at predetermined intervals (such as in the middle of the night).

  1. Ensured that the system can sustain over at least a 24 hour period a consistent number of concurrent Vusers executing transactions using near peak capacity.
  2. Measured the pattern of build-up in cruft (logs, data structures, and statistics that need to be periodically pruned).
  3. Detected the impact of occasional events (such as automatic cache flushes, Java Full GC and log truncations) and anomalies that occur infrequently.
  4. Make sure there is enough disk space and provisions for managing space, such as log truncation jobs that only occur automatically in the middle of the night.
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H. Scalability
(Efficiency) or
Reconfiguration
Tests

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This form of performance testing involves repeating tests above on different server/network hardware configurations to determine the most cost-effective option to support targeted load levels (one aspect of Capacity Planning).

The outcome of scalability efforts feeds a spreadsheet to calculate how many servers the application will need based on assumptions about demand.

  1. Determined — through repeated tests on different server/network hardware configurations — the most cost-effective option to support targeted load levels (one aspect of Capacity Planning).
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I. Availability
(Schedulability)

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This form of performance testing provides a continuous assessment of the availability and speed of key user actions.

These are run on applications in production mode.

This provides alerts when thresholds are reached and trends to guage the average and variability of response times.

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