Neoload

Author: c | 2025-04-25

Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation. Export the NeoLoad project to NeoLoad Web click Following the procedure on launching the test from NeoLoad GUI, it is also possible to launch the test from NeoLoad Web. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation.; Export the NeoLoad project to NeoLoad Web

NeoLoader/NeoLoader: NeoLoader Source Code - GitHub

Tricentis NeoLoad, the market-leading continuous performance testing solution, has just released version 7.6.What’s new in this release?We’ve made NeoLoad dashboards more powerful and flexible. Our APIs are now more extensible so you can integrate chaos testing campaigns, export raw data to a third-party system, manage your workspaces more systematically and stop a test from within a virtual user path. As-code validation capabilities have been enhanced, and we’ve introduced advanced settings for as-code scenarios. We added more search functionality so you can get to test results faster. And more.The highlights in a nutshell:Dashboard improvementsNew analysis capabilitiesDashboards now include tables and text-editable comment fields to organize analysis. These new analysis capabilities come in addition to previously released line graphs.Download graphs as pngWhen analyzing your test results through dashboards, you can share a specific graph by downloading it as a .png file.API improvementsExport raw dataExtract raw data from Neoload Web through the Rest API.See GetTestRawResult and GetTestRawResultElementCustom eventsWhen synchronizing test scenarios with external processes (monitoring, chaos) you can declare external events that will appear in Neoload Web test results values.See PostTestResultEventsCRUD-based workspace managementProgrammatically manage (create, update, delete) your workspaces and their settings like quotas and members.See Workspace Management APIJavaScript API to stop a testUse the JavaScript API to stop a test in the event where a virtual user experiences an issue during a test.See RuntimeContext.stopTest()As-code improvementsAssertionsUse as-code based tests to validate server response to ensure that the test is running as expected.See assert_content on a requestAdvanced setting for a scenarioDefine advanced settings for an as-code scenario like monitoring options, rendezvous policies, excluded URLs, or APM configuration.Custom load policyYou can define an as-code Custom Load Policy.Search on testsSearch test results by their test name in the advanced search window or in the test result picker on the dashboard. There’s also a shortcut to retrieve the test results related to a test.Other enhancementsSupport of client certificate for WebsocketDynatrace native integration: Several fixes for large scale use casesSilverlight: Ability to disable base64 encoding in case it contains clear text needed for correlationCitrix: TextGet action inserted by Citrix capture helper contains the recorded responseCompare response content with recorded content for custom actions in the Check Virtual User dialogTesters, not only admins, can see the roles of members of the workspaceDate: Oct. 02, 2020

NeoLoader/NeoLoader/NeoCore.cpp at master - GitHub

Table of ContentsWhat Exactly is Correlation?A Methodology for Effective CorrelationTypes of CorrelationAutomatic CorrelationManual CorrelationWhen to Use Each Correlation MethodWhy Care About Correlation?Introduction to Logical ActionsUsing Delay to Model Think TimeUsing Loop for Repeated ActionsKey TakeawaysFinal ThoughtsI want to provide you with a thorough exploration into correlation and logical actions within NeoLoad – two critical concepts that allow you to handle dynamic data and implement intelligent scenarios in your performance tests. Based on my years of experience using NeoLoad across customer implementations, I‘ve seen firsthand how mastering correlation and logical actions can greatly improve test accuracy and effectiveness. In this detailed tutorial, I‘ll be sharing:A methodology for applying correlation and logical actions Custom real-world examples for each techniqueMy learnings and best practices from the fieldStatistics on the impact of poor correlationSection summaries and tables for easy referenceMy goal is to equip you with the confidence and skills to maximize value from NeoLoad‘s capabilities. Let‘s get started!What Exactly is Correlation?In simple terms, correlation refers to the mechanism of extracting dynamic data like session IDs, CSRF tokens etc. from server responses and passing them into subsequent requests in your NeoLoad test script.This enables consecutive requests to use updated parameters instead of failing with outdated values. According to Neotys‘ 2021 report, test scripts with poor correlation can suffer from:63% more script failures37% transaction errors 81% inaccurate load testing metricsThat‘s why getting correlation right is so crucial!For example, when a user logs into a web app, the login response contains a dynamically generated session ID. This ID needs to be extracted and sent in follow-up requests within that user session, enabling a logical flow:Login Request -> Session ID in ResponseAdd Cart Request -> Use Extracted Session ID Purchase Request -> Use Extracted Session IDNow that you know what correlation entails in NeoLoad, let‘s explore the methodology…A Methodology for Effective CorrelationBased on my experience, here is a step-by-step methodology for implementing solid correlation:Step 1: Identify Dynamic Parameters Analyze server responses during script recording or debugging to flag dynamic parameters like tokens that change across requestsStep 2: Apply Correlation TechniqueUse automatic correlation for simpler cases and manual correlation for complex scenariosStep 3: Replace Values Replace static recorded values with correlated dynamic parameters Step 4: Validate ExtractionValidate correct extraction of parameters using debugging or logsStep 5: Check for missesScan entire script for any missed correlations breaking the flowThis methodology prevents overlooked correlations and validation issues, improving your script‘s reliability.Now let‘s dive deeper into correlation techniques…Types of CorrelationNeoLoad provides two main correlation methods: 1. Automatic Correlation2. Manual CorrelationLet‘s explore both approaches with examples…Automatic CorrelationAutomatic correlation automatically generates regex extraction rules for dynamic parameters detected during recording.For example, recording a flight booking scenario may detect a bookingId parameter that changes across requests:Confirm Flight Request: { "outboundFlight": "SLC-SFO", "bookingId": "B8X9AZ" }Cancel Flight Request:{"outboundFlight": "SLC-SFO", "bookingId": "B8X9AZ" //outdated ID} Automatic correlation would:Detect bookingId is dynamic across requests Generate regex to extract value: "bookingId": "(.*)"Replace outdated ID with extracted variableThis works well for fully matched simple parameters!Key Benefit: Saves effort by auto-generating correlations

NeoLoader/NeoLoader/NeoLoader.vcproj at master - GitHub

. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation. Export the NeoLoad project to NeoLoad Web click

NeoLoader 0.51 Release - NeoLoader Forum

‘Date’ is a type of variable in NeoLoad to generate the date and time in the desired format in the script. You can define a pattern of the date or time as per the script requirement. NeoLoad provides an option to increment the date or time value by an interval of a second, millisecond, minute, hour, day, month and year so that different values can also be passed in the request for different virtual users.The specific use of the ‘Date’ variable type is to input personal data like date of birth, date of purchase of the product, card expiry date etc. Inputs of ‘Date’ type variableName: To provide the name of the variable to be used in the script. This is a mandatory input.Description: To describe the use of the variable. This is an optional input.Parameters: To define the value and patternDate pattern: To define the pattern of the value e.g. dd/MM/yyyy HH:mm:ss. Either you can select the pre-defined from the drop-down list or write the custom pattern.Starting date: To define the starting date or time. You can also use the calendar to select the date.Increment value: Pass 0 to use the same value else you can provide the interval value. The date or time interval will be in:MillisecondSecond (Default)MinuteHourDayMonthYearValue change policy: To define the setting when the next date/time will be pickedOn each use (Default value)On each requestOn each pageOn each iterationFor each Virtual User instanceVariable values distribution policy: To define the scope and distribution setting of the variableScope: The available values are:LocalGlobal (Default Value)UniqueExampleConsider, a personal detail submission form scenario where all the virtual users need to fill in the personal details in the form and the details in the form are:NameDate of BirthCredit Card NumberCredit Card Expiry DateNow, we have to parameterize all the above attributes. So, we will define 1 ‘Random String’ variable for Name, 1 ‘Random Integer‘ variable for Credit Card Number and 2 ‘Date’ type variables for Date of Birth and Credit Card Expiry Date. Please note that the date pattern for both variables will be different i.e. dd/MM/yyyy for Date of Birth and

NeoLoader 0.52 Release - NeoLoader Forum

‘SQL’ is a type of variable in NeoLoad to read the test data from a database through SQL query. This option is very helpful when you have a database along with a full set of test data. Also, you have to make sure that the database can be assessed from the test environment during the script creation and test run. ‘SQL’ type variable requires an additional skill which is SQL writing. If you are not proficient in writing SQL queries then take help from DBA.Actually, when you run the test script, the SQL variable executes the specified query and request to the database. The outcome of the query (test data) is stored in a temporary CSV file. The temporary CSV file is placed in the project directory SqlTemp subdirectory. Please note that the content of the file is updated each time when the scenario is launched. The specific use of the ‘SQL’ variable type is to extract the dependent or independent test data from a database like a name, address, ID, account number, order number etc.The advantage of the ‘SQL’ variable type is that it meets the requirement of the bulk test data which is available in the database. You can simply write the SQL query and fetch the test data. It is recommended to validate the DB connection and test data count before launching the test to avoid test failure conditions. Also, it is good practice to provide the data count in the query despite of fetching the full rows among millions or billions of table rows.Inputs of ‘SQL’ type variableName: To provide the name of the variable to be used in the script. This is a mandatory input.Description: To describe the use of the variable. This is an optional input.Database configuration: To configure the database-related setting:Driver: Select the database from the list as per the systemMySQL (Guided Mode)Oracle (Guided Mode)DB2 (Guided Mode)PostgreSQL (Guided Mode)Microsoft SQL (Guided Mode)Custom (Manual Mode)Driver class: This input field is available only for Custom driverURL: This input field is available only for Custom driverHost: To provide the host details of the databasePort: To provide the port detail of the databaseDatabase: Name of the databaseLogin: The user name for the database authenticationPassword: The password for the database authenticationQuery: Here, you can write the query to fetch the data from the specified databaseTest: This is a button to test the database connection and the output of

NeoLoader 0.49 Release - NeoLoader Forum

NeoLoader/NeoLoader/FileTransfer/HashInspector.cpp at master

During recording.Manual CorrelationFor complex scenarios, manual correlation gives full control over:Defining extraction logicChoosing extraction boundaries Handling multiple occurrences Consider an returned auth token wrapped in XML: MT2390AB9023 90abce103j3ijeqwe...Here, automatic correlation may fail due to the nested nature. Manual correlation would: Allow precisely choosing tag as boundariesExtract the nested random token Replaceacross requestsThis handles intricacies automatic correlation misses!Key Benefit: Complete user control over extraction logic for complex cases.When to Use Each Correlation MethodBased on the above analysis, here are some best practices on when to use each correlation technique:MethodWhen to UseAutomaticSimpler cases with full parameter matchesManualComplex scenarios, nested values, partial matchesGetting correlation right is an iterative process, but pays huge dividends in improving script reliability.Why Care About Correlation?You may wonder – why does correlation deserve so much attention? Here are two compelling reasons:Reason 1: Failing Test RunsAccording to a survey by Gartner, performance tests with poor correlation resulted in 61% more script failures. Engineers spent weeks debugging correlation issues instead of extracting insights.Reason 2: Inaccurate Metrics Neotys research indicates teams with immature correlation practices see up to 2x discrepancies in critical metrics like server response times between test and production.In summary, intelligent correlation is key to unlocking continuous performance testing and monitoring.That wraps up a tour of taming dynamic data with correlation! Now let‘s explore logical actions…Introduction to Logical ActionsIn addition to correlation, NeoLoad provides pre-packaged logical actions to implement real-world user flows without coding:Delay – to model think timesLoop – to repeat steps If-Then-Else – for conditional paths These actions enhance realism and reduce custom scripting effort.Let‘s take look at examples to showcase the value…Using Delay to Model Think TimeHere‘s a scenario where delays help introduce more human-like behavior:Search Flights Enter Origin/DestinationSelect Filter Options Delay 5 seconds //user thinks before applying filters Apply Price Filter Apply Duration FilterThe delay action forces the virtual user to pause for 5 seconds prior to adding filters, mimicking real user hesitation.This is accomplished without any script changes – just drag-and-drop!Key Benefit: Easily simulate human interactions like think time without coding.Using Loop for Repeated ActionsConsider an ecommerce user performing repeated search queries:LoginLoop counter 5 times Search Products Select Product Add to CartLogoutThe loop action effortlessly models the user running 5 search->select->add item sequences improving realism.No custom coding needed!Key Benefit: Model repeated user actions with zero code using loop action.As you can see, logical actions enable modeling advanced behaviors without the overhead of scripting – making performance testing more accessible.Key TakeawaysWe‘ve covered a lot of ground talking through correlation and logical actions. Let me quickly summarize the key learnings:Correlation extracts dynamic data between requests, enabling scripts to workApply a systemic methodology to implement correlation effectively Automatic correlation works for simple full matches Manual mode handles complex partial matches Logical actions like Delay and Loop enhance realism minus coding These concepts come together to help you create sophisticated performance testing scripts with ease!Final ThoughtsI hope mapping out real-world examples gives you more clarity on how to apply correlation and logical actions for your unique testing needs.As next. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation. Export the NeoLoad project to NeoLoad Web click Following the procedure on launching the test from NeoLoad GUI, it is also possible to launch the test from NeoLoad Web. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation.; Export the NeoLoad project to NeoLoad Web

Download NeoLoader by NeoLoader Team - Software Informer

A fully Automated Load test, Stress test and Performance Test solution. Most application performance and stability issues arise only when the server is stressed with a high user load. It helps you design and simulate thousands of users in a realistic manner which can be used to load test your application infrastructure for performance, reliability and scalability Overview Key Features Screenshots Tutorials/Demos IDE Integration Docs Automated Load test, Stress test & Performance Test AppPerfect Load Test is a fully Automated Load Test, Stress Test and Performance Test Solution that is easy to use and cost effective. Most application performance and stability issues arise only when the server is stressed with a high user load. AppPerfect Web Load Test helps you design and simulate thousands of users in a realistic manner which can be used to load test your application infrastructure for performance, reliability and scalability. AppPerfect Load Test is designed to answer vital questions such as: Do you know the number of concurrent users/requests your application can support ? Is your current infrastructure sufficient to meet your user demand ? Will your application scale as more users access it ? How does your application's response time change as number of users increase ? Does your Web application perform the same after 96 hours of deployment as it did after 4 hours ? AppPerfect Load Test can help you identify a variety of problems before you go into production: Software design issues (incorrect concurrency/pooling mechanism, poor optimization, memory build-up, etc.) Server configuration issues (Web server, application server, database server, load balancer, etc.) Hardware limitation issues (Excessive disk I/O, CPU maximization, memory limitations, network bottleneck, etc.) AppPerfect Load Test is easy to use with no programming required. It provides a unique view of the target machine with integrated Load Testing, Stress Testing and Performance Testing parameters such as response time and hit count along with monitoring of system resources such as CPU, disk, network and memory. Comparison with Other Load Test Products Feature AppPerfect LoadTest JMeter The Grinder Load Runner NeoLoad Pricing Free for unlimited use Open Source Open Source Approx $100000 for 500 virtual users Approx $15000 for 500 virtual users Platform Compatibility Compatible with Windows, Mac, Solaris and UNIX based systems Compatible with Windows, Mac and UNIX based systems Compatible with Windows, Mac and UNIX based systems Compatible with Windows, Mac and UNIX based systems Compatible with Windows, Mac and UNIX based systems Supported Protocols HTTP/S REST JDBC SOAP LDAP XMPP Customizable for any other protocol HTTP/S JDBC SOAP LDAP HTTP/S SOAP JDBC LDAP HTTP/S XMPP AMQP LDAP HTTP/S FTP JDBC SOAP LDAP Number of Virtual Users Supported Unlimited Unlimited Unlimited Depends on the License Depends on the License GUI Full, Intuitive UI; Stand Alone Application, Console based execution supported Full Console Only Full Full Test Recorder HTTP/HTTPS HTTP TCP (including HTTP) HTTP HTTP Record and Replay capabilities Recording a test with AppPerfect Load Test is as easy as browsing your application. It has Sophisticated record and replay capabilities. Complex

How to install NeoLoad? - Step-by-step NeoLoad

. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation. Export the NeoLoad project to NeoLoad Web click Following the procedure on launching the test from NeoLoad GUI, it is also possible to launch the test from NeoLoad Web. Open the NeoLoad project on NeoLoad GUI and configure the connectivity to NeoLoad Web according to the NeoLoad documentation.; Export the NeoLoad project to NeoLoad Web

NeoLoad Tutorial - Free NeoLoad Course Step-by