Merge pull request LambdaTest#1304 from amanchopra1905/stage

hyperexecute jmeter

Author: surishubham

docs/hyperexecute-run-jmeter-tests.md

@@ -41,7 +41,6 @@ import {YOUR_LAMBDATEST_USERNAME, YOUR_LAMBDATEST_ACCESS_KEY} from "@site/src/co
       })
     }}
 ></script>
-
 > This is currently in the **Beta** version.
 
 ## Prerequisites
@@ -50,6 +49,8 @@ import {YOUR_LAMBDATEST_USERNAME, YOUR_LAMBDATEST_ACCESS_KEY} from "@site/src/co
 
 You can use your own project to configure and test it. For demo purposes, we are using the sample repository.
 
+> By default, HyperExecute supports **standard Thread Group** but you can use other custom thread groups as well.
+
 :::tip Sample repo
 Download or Clone the code sample for the JMeter Performance Testing from the LambdaTest GitHub repository to run the tests on the HyperExecute.
 
@@ -130,56 +131,65 @@ You can analyze the number of requests sent on that particular time.
 <img loading="lazy" src={require('../assets/images/hyperexecute/frameworks/performance_testing/logs.png').default} alt="HyperExecute"  width="1920" height="868" className="doc_img"/>
 
 ## Handling Special Scenarios: Overriding and Default Values
-### Scenario 1: Overriding Values via Projects portal
-When executing performance tests using HyperExecute, you have the option to override default parameters directly in the Projects portal. Let’s explore a sample scenario to understand how HyperExecute handles these overrides.
 
-You configure the following parameters in the HyperExecute UI:
-- **Virtual Users :** (The total number of simulated users for the test): 500
-- **Ramp-Up Time :** 1 minute
-- **Total Duration :** 2 minutes
-- **Regions :** 2 (50% distribution each)
-- **Maximum Users per Machine :** 100
 
-#### Resulting Test Distribution:
-- **Load Distribution Across Regions :**
-  - The total 500 virtual users are divided equally between the two regions.
-  - Each region is allocated 250 users (500 users ÷ 2 regions).
 
-- **Machine Allocation :** Since a single machine can handle a maximum of 100 users, each region requires multiple machines to support its load:
-  - **Region 1 :** 250 users → 3 machines (lets say it distributed as 84, 83, 83 users per machine).
-  - **Region 2 :** 250 users → 3 machines (lets say it distributed as 84, 83, 83 users per machine).
+<details>
+  <summary><h4>Scenario 1: Overriding Values via Projects portal</h4></summary>
 
-- **User Allocation per Machine:** Users are evenly distributed among machines to ensure optimal utilization and balanced load:
-For example, in Region 1:
-Machine 1 = 84 users, Machine 2 = 83 users, Machine 3 = 83 users.
+  When executing performance tests using HyperExecute, you have the option to override default parameters directly in the Projects portal. Let’s explore a sample scenario to understand how HyperExecute handles these overrides.
 
-#### Key Takeaways:
-- **Flexible Overrides :** HyperExecute dynamically adjusts the load distribution and machine allocation based on your specified parameters.
-- **Optimal Resource Utilization :** It ensures that no machine exceeds the maximum user threshold, maintaining a balanced and efficient test execution.
-- **Region-Specific Allocation :** Users are distributed proportionally based on the defined load percentages for each region.
+  You configure the following parameters in the HyperExecute UI:
+  - **Virtual Users :** (The total number of simulated users for the test): 500
+  - **Ramp-Up Time :** 1 minute
+  - **Total Duration :** 2 minutes
+  - **Regions :** 2 (50% distribution each)
+  - **Maximum Users per Machine :** 100
 
-This approach ensures smooth execution of performance tests and provides precise control over resource utilization, enabling you to simulate real-world scenarios effectively.
+  #### Resulting Test Distribution:
+  - **Load Distribution Across Regions :**
+    - The total 500 virtual users are divided equally between the two regions.
+    - Each region is allocated 250 users (500 users ÷ 2 regions).
+  
+  - **Machine Allocation :** Since a single machine can handle a maximum of 100 users, each region requires multiple machines to support its load:
+    - **Region 1 :** 250 users → 3 machines (lets say it distributed as 84, 83, 83 users per machine).
+    - **Region 2 :** 250 users → 3 machines (lets say it distributed as 84, 83, 83 users per machine).
+  
+  - **User Allocation per Machine:** Users are evenly distributed among machines to ensure optimal utilization and balanced load:
+  For example, in Region 1:
+  Machine 1 = 84 users, Machine 2 = 83 users, Machine 3 = 83 users.
+  
+  #### Key Takeaways:
+  - **Flexible Overrides :** HyperExecute dynamically adjusts the load distribution and machine allocation based on your specified parameters.
+  - **Optimal Resource Utilization :** It ensures that no machine exceeds the maximum user threshold, maintaining a balanced and efficient test execution.
+  - **Region-Specific Allocation :** Users are distributed proportionally based on the defined load percentages for each region.
+  
+  This approach ensures smooth execution of performance tests and provides precise control over resource utilization, enabling you to simulate real-world scenarios effectively.
+</details>
 
-### Scenario 2: Default Parameters
-In this scenario, you proceed without overriding the default values in the HyperExecute Projects portal. The configuration parameters from your JMeter file and project setup are applied as-is.
+<details>
+  <summary><h4>Scenario 2: Default Parameters</h4></summary>
+  
+  In this scenario, you proceed without overriding the default values in the HyperExecute Projects portal. The configuration parameters from your JMeter file and project setup are applied as-is.
 
-#### Scenario Details:
-- **Total Users :** 250 (Specified in the JMeter .jmx file.)
-- **Regions :** 2 
-- **Machines :** 3 (Each region is allocated three machines.)
+  #### Scenario Details:
+  - **Total Users :** 250 (Specified in the JMeter .jmx file.)
+  - **Regions :** 2 
+  - **Machines :** 3 (Each region is allocated three machines.)
 
-#### Resulting Test Distribution:
-- **Load Distribution Across Regions :** The total of 250 virtual users is not divided across the regions because no overrides were applied. Instead, each region receives the full 250 users.
+  #### Resulting Test Distribution:
+  - **Load Distribution Across Regions :** The total of 250 virtual users is not divided across the regions because no overrides were applied. Instead, each region receives the full 250 users.
 
-- **Machine Allocation :** Each region is allocated three machines. The total user load for the region is replicated across all three machines in the region:
-  - **Region 1 :** 3 machines → 250 users per machine.
-  - **Region 2 :** 3 machines → 250 users per machine.
+  - **Machine Allocation :** Each region is allocated three machines. The total user load for the region is replicated across all three machines in the region:
+    - **Region 1 :** 3 machines → 250 users per machine.
+    - **Region 2 :** 3 machines → 250 users per machine.
 
-- **User Allocation per Machine :** Each machine in both regions processes **250 users**, resulting in a total of 750 users (250 users × 3 machines) per region.
+  - **User Allocation per Machine :** Each machine in both regions processes **250 users**, resulting in a total of 750 users (250 users × 3 machines) per region.
 
-#### Key Takeaways:
-- **Default Behavior :** Without overrides, the user load from the .jmx file is replicated across all configured machines in each region.
-- **Resource Replication :** Instead of splitting the total users among machines, HyperExecute applies the same load to each machine in a region.
-- **Importance of Overrides :** To distribute users proportionally across machines and regions, use the UI to override parameters such as total users, maximum users per machine, or load percentages.
+  #### Key Takeaways:
+  - **Default Behavior :** Without overrides, the user load from the .jmx file is replicated across all configured machines in each region.
+  - **Resource Replication :** Instead of splitting the total users among machines, HyperExecute applies the same load to each machine in a region.
+  - **Importance of Overrides :** To distribute users proportionally across machines and regions, use the UI to override parameters such as total users, maximum users per machine, or load percentages.
 
-This behavior highlights how HyperExecute ensures flexibility in test execution while allowing for configuration control based on project requirements.
+  This behavior highlights how HyperExecute ensures flexibility in test execution while allowing for configuration control based on project requirements.
+</details>