JMeter Interview Questions and Answers for 2025

There are two types of processors exist: 

• Pre-process: Before sending a Sampler Request, the Pre-processor takes some action. Here's a simple illustration: Suppose a user wants JMeter to "spider" across a website undergoing a test, parse links (check all the links on the page), and then return the HTL. Before generating an HTTP request, it is required to add an action to the controller, such as an "HTML link parser."

Post-processor: After sending a Sampler Request, the Post-processor takes some action. A simple illustration: JMeter makes an HTTP request to the test web server  (e.g., www.google.com), and it receives a reply. If the server answer contains a mistake, JMeter can be used to terminate the test. To do this:

• Configuration elements: Some of the potential elements in the configuration elements includes CSV Data Set Config, FTP request Defaults, DNS Cache Manager, HTTP Authorization Manager, HTTP Cache Manager, HTTP Cookie Manager, HTTP Request Defaults, HTTP Header Manager, and others.  
• Pre-Processors: Some of the potential elements in the Pre Processors include HTML Link Parser, HTTP URL Re-writing Modifier, User Parameters, BeanShell PreProcessor, JSR223 PreProcessor, JDBC PreProcessor, RegEx User Parameters, and Sample Timeout. 
• Timers: Some of the potential elements in the Timers include Timers, Constant Timer, Gaussian Random Timers, Uniform Random Timer, Constant Throughput Timer, Synchronizing Timer, BeanShell Timers, JSR223 Timer, and Poisson Random Timer.   
• Sampler: Some of the potential elements in the Samples include FTP Request, HTTP Request, JDBC Request, Java Object Request, JMS Request, JUnit Test Request, LDAP Request, Mail Request, OS Process Request, and TCP Request.  
• Post-Processors: Some of the potential elements in the Post-Processors include Regular Expression Extractor, CSS Selector Extractor, XPath2 Extractor, XPath Extractor, JSON JMESPath Extractor, Result Status Action Handler, BeanShell PostProcessor, JSR223 PostProcessor, JDBC PostProcessor, JSON Extractor, and Boundary Extractor.  
• Assertions: Some of the potential elements in the Assertions include Response Assertion, Duration Assertion, Size Assertion, XML Assertion, BeanShell Assertion, MD5Hex Assertion, HTML Assertion, XPath Assertion, and others.  
• Listeners: Some of the potential elements in the Listeners include Simple Data Writer, BeanShell/JSR223 Listener, Mailer Visualizer, Summary Report, Aggregate Report, Aggregate Graph, and others.  

Configuration Elements can be used to specify variables, allowing Samplers to access data via these variables. Configuration element can only be accessed from the tee node where it was defined. A configuration element will also take priority over a similar configuration element declared in a parent node if it is defined inside a tree node.

The process of adding variables in JMeter that will offer a wide variety of configuration choices for a load-testing script is known as parameterization. For instance: 

• Variables for logging into a web service with various credentials. 
• Use distinct environment-specific variables (dev, master, etc.) 
• E-commerce site search criteria for a list of items 

There are four different data parameterization options: 

• Making use of external files: Using a CSV file is one of the popular approaches to parameterize performance scripts in JMeter. For instance, supposing there's a login request that functions for a single user, that request may simply be parameterized and tested with various users. In order to parameterize the script, two variables to store the email and password will be needed. To do this, a CSV file containing a list of usernames and passwords for use during login must be delivered. There are some various parameters that must be understood to properly create a CSV file:  
  • Name: Name of the element as it will appear in the JMeter tree. 
  • Filename: The input file's name. The path of the current test plan is used to resolve relative file names.  
  • File Encoding: Input file encoding, if it's different from the platform's default. 
  • Variable Names: A list of separated variable names that will serve as a holding area for values that have been parsed. If the file's first line is empty, the variable names will be regarded as being on that line.  
  • Ignore First Line: If the variable names are placed in the first line of the CSV file, then it is true that line should be ignored.  
  • Delimiter: A delimiter that will be used to divide the values from the input file that has been parsed. 
  • Allow Quoted Data: True in cases where delimiter should be present in the elements if double quotes are to be disregarded. 
  • Recycle on EOF: True if the file test plan requires repeated iterations on the file. It will inform JMeter to start the file from the beginning.  
  • Stop Thread on EOF: False to loop over the CSV file again, and true to halt the thread after reading the entire file. 
• Sharing Mode: 
  • All threads: The file is shared by every virtual user (default) 
  • Current thread group: Each thread group will receive a single opening of the file.  
  • Current thread: For each of the threads, a separate file will be opened. 
  • Edit: Every thread with a given identifier also uses a given file.  
  • After creating a CSV file, the last test is to parameterize the login request with new variables. To do this, substitute the necessary variables from the "Variable Names" configuration field of the CSV Data Set Config for the starting values.  
• Utilizing Databases: Utilizing database information is another technique to parameterize the performance scripts. The JMeterscripts will be parameterized using JDBC, an application programming interface that specifies how a client may access a database. 
  • To do this, download the appropriate JDBC driver for the database first, then include the .jar file in the test plan. After that, use the 'JDBC Connection Configuration' element to set up the database connection. The following parameters should be understood when configuring the JDBC connection: 
  • Name: The name of the connection configuration that the thread group tree will display. 
  • Variable Name: The name that will be used to identify the database connection specifically. 
  • Max number of connections: The most connections that can be added to the connection pool. Each thread will receive its own pool with a single connection in it if the value is 0.  
  • Max waits (ms): If the set timeout is exceeded during a database connection, the pool throws an error. 
  • Time between eviction runs (ms): The amount of milliseconds to wait in between thread runs that remove inactive connections from the database pool.  
  • Auto commit: Yes switch on auto-commit for connected databases that are linked. 
  • Test while idle: Before an effective request is seen, check for an idle connection.  
  • Soft min evictable idle time (ms): The time frame before a specific connection in the database pool can be removed while it is idle.  
  • Validation Query: Query that will be used as a health check to see if the database is still responding. 
  • Database URL: Database connection string for JDBC. 
  • JDBC driver class: Appropriate driver class name. For instance, "com.mysql.jdbc.Driver." is appropriate for the MySql database. 
  • Username: Username for the database. 
  • Password: Database login (will be stored unencrypted in the test plan).  
• Using the "Parameterized Controller" plugin: The "Parameterized Controller" plugin can also be used in cases where they need to carry out a recurring series of the same operation with varied parameters. This controller gives the ability to build up a group of variables that will be utilized in each step that is added to the controller.

Correlation is crucial in JMeter, it is the process of obtaining and passing on to subsequent queries the dynamic answer from the server that was received. It is crucial due to the fact that correlation is needed when writing performance load tests for dynamic sites. The script is worthless if it isn't handled properly.

It is important to distinguish between static and dynamic responses from a testing perspective (the data stays the same for iterating requests). Every HTTP web performance test often includes data correlation. Only when evaluating static content sites, such as certain homepages and contacts, may correlation be disregarded. In other situations, correlation handling must be done at some time throughout the test.

Limits often rely on a variety of variables, and JMeter restrictions are no exception. JMeter limitations vary depending on your machine's and network's capabilities, your performance scripts' complexity, the desired number of simulated users, and other factors.

Correlation is crucial in JMeter, it is the process of obtaining and passing on to subsequent queries the dynamic answer from the server that was received. It is crucial due to the fact that correlation is needed when writing performance load tests for dynamic sites. The script is worthless if it isn't handled properly.  

It is important to distinguish between static and dynamic responses from a testing perspective (the data stays the same for iterating requests). Every HTTP web performance test often includes data correlation. Only when evaluating static content sites, such as certain homepages and contacts, may correlation be disregarded. In other situations, correlation handling must be done at some time throughout the test.

Listeners are used to observe and examine the Sampler request and answer as tables, graphs, trees, etc. Additionally, there's the option of saving results to a file for later reading. When a load/stress test is running, the sampler result can be gotten without having to wait. The following is a list of listeners:  

1. Aggregate Graph: Aggregate graphs enable us to choose the settings for the graph presentation and make it simple to create bar graphs. The resulting data for the graph and table may be specifically saved as PNG and CSV files.  
2. Aggregate Report: The aggregate report displays a distinct table row for each test's variously titled sampler request. 
3. Assertion Results: Sampler's assertions are shown in the Assertion Results section. Note that assertion results should not be used in load or stress tests because they use a lot of CPU and memory resources. It is advised to use it for debugging or functional testing.  
4. View Results in Table: Every sample/request result is displayed in its own row when using View Results in Table. Note that using View Results in Table during a load or stress test will use quite a lot of memory and CPU. It is advised to use it for debugging or functional testing.  
5. View Results Tree: View Results Trees display the Sampler responses along with their requests in a tree. The View Results Tree should not be used when doing a load or stress test because it uses a lot of CPU and memory resources. It is advised to use it for debugging or functional testing.  

More listeners include: 

1. Backend Listener 
2. BeanShell Listener 
3. BSF Listener 
4. Comparison Assertion Visualizer 
5. Generate Summary Results 
6. Graph Results 
7. JSR223 Listener 
8. Mailer Visualizer 
9. Monitor Results 
10. Response Time Graph 
11. Saves Responses to a file 
12. Simple Data Writer 
13. Summary Report  

The WorkBench just provides a location to temporarily store test items. It has nothing to do with the Test Plan, as its components are not preserved with the Test Plan, so it may be used as a practice area or for short-term storage. It can also be used to load test scripts straight after recording them.

All HTTP(s) queries made by the application to the server are recorded using the HTTP(s) Test Script Recorder. JMeter has to be configured in a few different ways for it to function. The actions taken to record HTTPS traffic are listed below: 

1. Enhance WorkBench with HTTP(s) Test Script Recorder. 
2. Enter the port that you wish to use to launch your proxy server.  
3. Select "Workbench" as the only option for the Target, or add a Recording Controller to your test plan and choose it as the Target to store all recordings under. 
4. Now launch the Proxy server 
5. Manually set up your browser's proxy settings to point to the same port as the test script recorder.  

Special values known as JMeter functions can be used to fill in fields on any Sampler or other element in a test tree. A function is called like this: 

$[__functionName(var1,var2,var3)}

Make careful to escape any commas that are present in function parameters with "," 

The name of a function is the same: 

_functionNamee. For instance, $__threadNum

Variable names provided as parameters won't be created and variable references won't operate, variables are referenced as  

${VARIABLE} 

• Web HTTP – for testing bowser-based online applications and websites
• Web Services – testing SOAP, REST, and other APIs, including those that allow mobile apps.
• Ajax True Client – testing single-page web applications
• Citrix – testing applications hosted on a Citrix Desktop
• SAP – testing SAP programs (i.e Thick Client) that are not web-based.
• JAVA – testing Java desktop applications
• Mobility – evaluating mobile-specific protocols for devices like wearables and the Internet of Things.
• RDP – testing Remote Desktop Protocol testing.
• Oracle Web 11i – testing older Oracle web applications prior to Oracle 12
• Siebel Web – testing ancient, non-browser-based Siebel programs

One of the most frequently posed JMeter interview questions, be ready for it. Timers are crucial for maintaining equilibrium while doing JMeter performance testing. JMeter threads typically execute one after the other without pausing, this may be implausible in nature because a typical user will pause between each action to read or consider, which is called a Think Time, and it has to be included in the script to make it more realistic.  

JMeter offers 9 different timer types for use in such activities, and the user may choose the one that best fits the situation:  

• Constant Timer: This can be used to give time some Think Time in between requests. 

The name provided is shown on the tree, and the thread latency is measured in milliseconds here, as 1000 would be inputted for 1 second.  

• Uniform Random Timer: A random amount of wait time can be added between user requests using the uniform random timer.  

The name element's purpose is to provide a name for the timer that will be displayed in the tree. As the name implies, the maximum think time should be specified in Random Delay Maximum, while Constant Delay Offset is an extra millisecond-based variable.  

• BeanShell Timer: This scripting-based timer enables users to create a timer implementation logic. 
• JSR223 Timer: Similar to the Bean Shell timer, JSR223 Timer is also scripting-based. By using the JSR223 Scripting language, delays can be added between user requests in JSR223 Timer.  

More timers include: 

• Synchronizing Timer 
• BSF Timer 
• Constant Throughput Timer 
• Poisson Random Timer 
• Gaussian Random Timer

Aggregate Graph: Aggregate graphs enable us to choose the settings for the graph presentation and make it simple to create bar graphs. The resulting data for the graph and table may be specifically saved as PNG and CSV files.  

Aggregate Report: The aggregate report displays a distinct table row for each test's variously titled sampler request. 

Assertion Results: Sampler's assertions are shown in the Assertion Results section. Note that assertion results should not be used in load or stress tests because they use a lot of CPU and memory resources. It is advised to use it for debugging or functional testing.  

View Results in Table: Every sample/request result is displayed in its own row when using View Results in Table. Note that using View Results in Table during a load or stress test will use quite a lot of memory and CPU. It is advised to use it for debugging or functional testing.  

View Results Tree: View Results Trees displays the Sampler responses along with their requests in a tree. The View Results Tree should not be used when doing a load or stress test because it uses a lot of CPU and memory resources. It is advised to use it for debugging or functional testing.  

More listeners include: 

1. Backend Listener 
2. BeanShell Listener 
3. BSF Listener 
4. Comparison Assertion Visualizer 
5. Generate Summary Results 
6. Graph Results 
7. JSR223 Listener 
8. Mailer Visualizer 
9. Monitor Results 
10. Response Time Graph 
11. Saves Responses to a file 
12. Simple Data Writer 
13. Summary Report 

Performance testing is a non-functional testing method where the effectiveness of the application is assessed under anticipated or greater demand. To make sure that the program doesn't crash and replies within a reasonable amount of time under actual demand, it is done before it is launched on a production server.  

Some benefits of Performance Testing include: 

• Server Compatibility: Regardless of the server or protocol, JMeter is a very powerful tool that can handle load and performance testing for many goods. Be it a database, FTP, LDAP, or MOM through NoSQL, HTTP, or HTTPS web services.  
• Expandable architecture: Due to the fact that JMeter is an open-source project, its users are very engaged in the creation of plugins for it. In reality, JMeter provides all the tools needed to work toward reporting objectives, particularly features for server resources monitoring. Overall, using JMeter is pretty convenient if you need to develop your own Plugins.  
• No investment required: The fact that JMeter is free is another important advantage. JMeter may be used by any team with a minimal budget to create internal tools or work on any commercial project that requires performance control. 
• Record & Playback: JMeter's drag-and-drop functionality makes it easy for users to make use of the record and playback capability, which speeds up the creation of test scripts while eliminating any latencies.  
• Customizations: You may always take use of JMeter's open-source status to change its source code and produce anything that meets your requirements if you're a developer who needs to use some more features.  
• Distributed Load Testing: Developers and testers can collaborate on a master-slave set using JMeter to provide distributed load testing on many computers. 
• Community Support: Since JMeter is an open-source tool, you may always ask the community for assistance with your testing projects. Additionally, there are several tutorials that are accessible online that may be used to comprehend its application. Even better, it provides a ton of free plugins that may be used to speed up the writing and analysis of scripts. 

JMeter script generation differs slightly from conventional automated script creation. A script may often be written by recording it or utilizing the JMeter UI.

Most definitely, Selenium scripts can be integrated with JMeter via the application of support web driver plugins in the following steps.

• Download plugins
• Make a copy of the jars found in the "lib" and "ext" folders
• Use the selenium written code stationed in the sampler to invoke the web driver sampler configuration features. These are part of the browsers like chrome etcetera.
• Other properties can also be configured in the configuration feature elements.
• Include a listener to the test plan that has the web driver sampler to be notified of the time taken by users in task execution processes.
• The log displayer should be left turned on to detect and view errors while running the tests

JMeter is a very common tool used for load testing that encourages the expansion of its capabilities. JMeter plugins are software features used by JMeter to expand functionalities and input functions. Numerous plugins are existing, which are used to enhance JMeter's functionality, these plugins avail a simpler way of installing and maintaining the execution of JMeter for its clients. 

The top-5 JMeter supported plugins include: 

1. Customized Simple Object Access Protocol (SOAP) Sampler 

The SOAP is a JMeter custom sampler that functions with or without numerous attachments. The sampler serves as a sender for SOAP requests to web services and allows users to edit, add or delete code attachments. 

1. Performance Server Monitoring Plugins(PerfMon) 

The PerfMon plugin is used for the extension of JMeter using the listener performance and monitoring servers, permitting the follow-up of CPU, disks, and network I/Os and servers memory. 

1. JMeter Custom Thread Groups 

These custom plugins are used for adding five other thread groups in JMeter. They include: 

• Stepping 
• Concurrency 
• Arrivals free-form 
• Arrivals  
• Ultimate 

1. Flexible Writing File Plugins 

This plugin is used to expand JMeter with a flexible listening file which is applied in writing test results into a specifically flexible file format through the JMeter GUI. 

1. Dummy Sampler Plugins 

The dummy sampler plugin is known as the most compliant JMeter sampler used to imitate the request orders and responses without the need to run them. This dummy sampler makes it easy to debug post-processors and file extractors. 

Other common JMeter-supported plugins are: 

• Interrelated thread communication plugins 
• JMeter custom functions 
• Put through timer shaping plugins 
• Plugins manager 

There are two different sorts of controllers in JMeter; the Samplers and the Logical controllers which are responsible for driving the test processing phase.

The Sampler controllers 

• Inform JMeter on the need to send server requests such as the inclusion of an HTTP sampler request to JMeter to send a type of HTTP request, or the requests can also be customized by adding some elements for configuration to a sampler. Every sampler possesses various properties that can be set up or customized by the inclusion of certain configuration elements to the test plan while remembering to include a listener for display and/or saving of the results of the request results to the disc. 
• When sending more than one similar request, such as sending the HTTP requests to a particular server, attempt using a default configuration feature. Every controller has a configuration default element. 
• The samplers inform JMeter about sending requests and waiting for responses to and from the server, which are then processed in the organized format on which they are displayed in the tree. 
• Controllers help to regulate the occurrence of repetitions within a sample. 
• To make the JMeter execute simple and basic validation on request responses, include an assertion to the sampler. These assertions can be created with the aid of JMeter's regular expressions.  

Samplers used in JMeter are: 

• HTTP request order 
• FTP request order 
• JOR request order 
• JUnit request order 
• JDBC request order 

The Logical Controllers 

• These controllers permits the customization of the logic used by JMeter in making decisions about when to place and send a request. For instance, the addition of a controller for interleave logic to be shuffled between both HTTP requests samplers. 
• They allow for changes to be made to the requested order from their primary elements and have the self-ability to modify requests and make JMeter repeat requests. 
• A test tree can be used to understand the test plan of logic controllers.  

• Thread groups in JMeter are basic parent-feature components required for the execution of every test plan. 
• There are several thread groups in JMeter including the Stepping, Concurrency, Arrivals free-form, Arrivals, and Ultimate thread groups.  
• The ultimate thread group is part of the outer modules used for planning the test type like a spike test type or a responsibility model.  
• Using the ultimate thread group will require the application of a contingent burden on the server.   
• Unlike the others, ultimate thread groups permit the definition of diverse schedule records with separate ramp-up periods, shutting down, and flight mode times up to infinity and generates a graphical load display graph that can help in defining test plans that tally with real-time use cases. 
• Also, in the ultimate thread groups, there is permission for greater than one row which aids flexibility as it relates to a more advanced ramp-up and/or ramp-down pattern of behavior, this means that, in this instance, the addition of a load pattern multiple times is permitted. 
•  On the contrary, the other types of thread groups such as the concurrency thread group can be linked to the shaping timer through a feedback feature functionality to permit the control of test execution, like the addition of more threads to the numerous requests placed when there is a deficiency in the amount of the thread groups to attain and regulate the present shaping timer. 

Definition/ Explanation 

• "Spike" refers to a sudden change in traffic which could be in the direction of an increase or a decrease. 
• Spike testing is a kind of testing done to determine the performance of a test where a particular application obtains a drastic increase or decrease in load. The aim is to establish the behavioral attributes of a software application when it experiences severe variation in traffic. 
• The issues addressed by spike testing include the maximum load permitted by an application and recovery time verification for an application between activity spikes.  

How to perform spike testing using JMeter: 

• Performing a spike test may be daunting, as testers may discover that the application's performance progressively worsens, slows down, or is completely halted. Establishing the exact location for the cause of the failure of the application under spike tests permits developers to be more proactive in tackling unforeseen spikes in a load production environment. For instance, a spike test can be applied to a commercial application in preparation for an open sales day. 
• It is recommended to utilize a different test environment, not the live one when spiking a test application. It is beneficial to identify the maximum load capacity of spike testers to encourage the placing of more effort on more relevant software failures emanating beyond the confines of the expected capacities.  
• To monitor the software, the JMeter application is applied which allows the simulation of a system under conditions of sudden increase or decrease of test load, executed by the test performers. This is carried out over a shortened time before returning to a normal load.  
• The simulation monitoring then provides graphs representing performance operations to be analyzed by spike testers to detect possible breaks in the application under the conditions of peak loads.   

The Gaussian timer is a random timer element used in delaying each request made by users for a random period. Based on the gaussian curve distribution, there is a random deviation premised on the constant offset delay. The gaussian timer halts each thread request for a specified and on time, with the majority of the timeframes happening close to the gaussian distribution times value, the specified value, and the offset value.

An example of this is having a deviation of 500 milliseconds and a constant offset delay of 1000 milliseconds. Here, about 65% of the delays will fall between 500 and 1500 milliseconds. This range is obtained by simply subtracting and adding the values (1000-500 and 1000+500) because the gaussian random timer possesses a random deviation that is dependent on the distribution of the gaussian curve about a constant offset delay.

The total delay is the summation of the distributed value of the gaussian curve with a mean of 0.0 and a standard deviation (SD) of 1.0, multiplied by the specified offset and deviation value.

JMeter assertions are values that provide the basis on which they determine what should be seen as a "pass". Assertions are run against samples and subsamples to confirm if values returned to stay in conformation to expected results. They can as well be added to JMeter variables, and the two major reasons for employing the use of assertions are scope and cost in JMeter.  

Some of the different JMeter assertion types are outlined below.  

• Assertions of Duration 
• Assertions of  Response 
• Assertions of Size 
• Assertions of compare 
• Assertions of Beanshell 
• Assertions of SMIME 
• Assertions of XML 
• Assertions of HTML 
• Assertions of XPath 
• Assertions of MD5Hex 
• Assertions of BSF and JSR223

JTL stands for JMeter Text Logs and these are results created for use by JMeter test runs. They are often referred to as JTL files by default extension, however, any other extension may be utilized. If greater than one is run via the same name of an output file, the then work of JMeter would be to automatically append new data at the termination of the file. 

To view the JTL file, the following step should be followed. 

• JMeter should be opened 
• Load the particular script 
• Enter the script monitor logs in the ASM UI that is displaying the error. 
• Click on analysis on the side menu>logs>monitor 
• Select the root cause or detailed analysis icon in the log 
• Wait for the analysis window to open up, scroll through and locate the link for the JTL file 
• Download the link  
• Return to the JMeter and ensure there is a View Result Tree in the script, if it is not available, right-click on the button on thread group>Add>Listener>View Results Tree(VRT). 
• Click the VRT option and select browse 
• Load and open the downloaded JTL file  
• View steps in the test view  
• See the results of tests in the sampler result 

A red notification signifies a failed step, and an explanation for this failure will be included for display by the sampler result. 

Test script recorders like HTTP(S) are used to keep a record of every request made by the HTTP(S) to the server from the home application. Before the test script recorder begins to function, certain configurations will need to be made in the JMeter to make it function effectively. 

Here are the steps showing the flow of the test script recorder like the HTTP (s) which should be followed. 

• To the benchwork, include an HTTP(S) test script recorder 
• Enter the port number to be utilized in the commencement of the proxy server. 
• Select the target which could be as the "workbench" alone or include a recording controller in the test plan and pick the same target to save every recording under it. 
• Initiate the proxy server 
• Manually perform a browser configuration with a non-automated proxy setting that directs to the same port number that is used in the test script recorder. 

Recording in JMeter is an initial step to getting started with application performance testing. The recording flow of business speeds up the process of generating test plans, and if this step is neglected, more time will be wasted in an attempt to manually craft requests. Generally, almost every performance GUI-based testing tool provides a method by which the application can record by proxy. 

The actions and requests made on a mobile application can be recorded by JMeter using the HTTP(S) Script Recorder. This script recorder possesses specific features to set it up and run the performance test script. The needed action here is to configure JMeter on the mobile device, which varies between an iOS and an Android device. 

The addition of the non-Test element in JMeter to the plan setup permits the capturing of network traffic. This can be achieved by right-clicking on this access path; 

Test plan>Add>Non-Test Elements>HTTP(S) Script Test Recorder.  

This expands the recording capacity of JMeter. 

Tips for commencing a recording phase are to ensure there is a good understanding of the business flow and to have all necessary data available and ready. It is advised to clear out the cache and cookies from a frequently used browser. 

• A workbench is referred to as a practice premise or a transient and temporary storage area because the component features on the workbench are often not saved together with the test plan. 
• The workbench is a valuable component in the HTTPS test script recorder that helps to record scripts in a direct manner which the tester can be offloaded subsequently to measure response time. The information temporarily stored by the workbench can be added to the test plan if need be. 
• The workbench is unrelated to the test plan and JMeter will not save any contents or components of the workbench automatically, and will only save the components of the test plan branch. 
• If the workbench components must be saved, it has to be done separately in the form of "test fragments"

During the building of a performance test, the importance of using properties and values cannot be overemphasized to keep static values outside the tests, therefore, ensuring that alterations made to these values are all done in one place instead of having to make changes in several tests.

Oftentimes, although a JMeter suite might have been inherited, or the developer had to rush through a creative process, and may have hard coded the values in the tests, meaning that for every alteration made to an endpoint or server name or a payload sampler, then the changes must be made to the static values within the tests.

The need to update tests may also present, or a developer may have decided to update static values together with properties or variables so that subsequently, changes can be made to the input file of each test. This updating process can be exhausting and time-wasting, but since a JMeter test is a simple XML, updates to the tests can be done in an automated manner by parsing the XML and performing a code update.

The Apache's Xerces XML parer comes with the JMeter application, but a user is at liberty to request and select a different parser from JMeter by incorporating a class for a third-party parser in JMeter's classpath and then updating the properties in the jmeter.properties file together with the name of the full class of the parser implementation.

JMeter is used for testing load functionalities and performance measurement. It executed this task by creating a large-scale number of concurrent users in a heavy-load simulation. The performance testing feature of JMeter is an expanded functionality as it was previously designed for basic processes such as test application activities.

The need to use JMeter for performance testing stems from the reasoning that it is a high-capability resource that can load as well as monitor observable performance for various products, regardless of their protocols or servers, which could be HTTP or HTTPS service webers, databases, Message Oriented Middleware (MOM).

Also, the reason for using JMeter as a chosen application for performance testing results from these factors. 

1. It is cost-free 
2. Can aid performance testing for both dynamic and static resources 
3. Its testing in JMeter encompasses both load and stress testing. 
4. Its framework permits multithreading 
5. Graphically enhanced representation of performance testing 
6. An independent java-based platform

Take, for instance, a brand new API that has been created on the REST principles and configured under the ASP.NET interface. An attempt to save this will require the creation and running of certain stress tests for the API to grasp how rapidly it functions and the amount of load supported by it.

The .NET applications currently can be run against web APIs or applications, and the JMeter application operates the endpoints similar to the different media types since the .NET team stopped their cloud-based operation testing services due to poor community adoption.

JMeter can be used for load testing of .net web applications. This is done to know how fast a site will operate when the number of users on it is doubled or multiplied. Assuming the .net application makes use of a "postback" and has given access to the .net security or validation features, the postback here would submit the page to itself and the server will forward some long variables which are hidden to the user