Load testing is essential for ensuring web applications perform reliably under high traffic. Tools like Apache JMeter enable the simulation of user traffic to identify performance bottlenecks and optimize applications. When paired with the scalability and flexibility of AWS (Amazon Web Services), JMeter becomes a robust solution for efficient, large-scale performance testing.This guide explores the seamless integration of JMeter on AWS to help testers and developers conduct powerful load tests. Learn how to set up JMeter environments on Amazon EC2, utilize AWS Fargate for containerized deployments, and monitor performance with CloudWatch. With this combination, you can create scalable and optimized workflows, ensuring reliable application performance even under significant load. Whether you’re new to JMeter or an experienced tester, this guide provides actionable steps to elevate your testing strategy using AWS.
Key Highlights
Learn how to leverage the power of Apache JMeter and AWS cloud for scalable and efficient load testing.
This guide provides a step-by-step approach to set up and execute your first JMeter test on the AWS platform.
Understand the fundamental concepts of JMeter, including thread groups, test plans, and result analysis.
Explore essential AWS services such as Amazon ECS and AWS Fargate for deploying and managing your JMeter instances.
Gain insights into interpreting test results and optimizing your applications for peak performance.
Understanding JMeter and AWS Basics
Before we start with the practical steps, let’s understand JMeter and the AWS services used for load testing. JMeter is an open-source Java app that includes various features and supports the use of the AWSMeter plugin. It offers a full platform for creating and running different types of performance tests. Its easy-to-use interface and many features make it a favorite for testers and developers.
AWS has many services that work well with JMeter. For example, Amazon ECS (Elastic Container Service) and AWS Fargate give you the framework to host and manage your JMeter instances while generating transactional records. This setup makes it easy to scale your tests. Together, they let you simulate large amounts of user traffic and check how well your application works under pressure.
What is JMeter?
Apache JMeter is a free tool made with Java. It is great for load testing and checking the performance of web applications, including testing web applications and other services. You can use it to put a heavy load on a server or a group of servers. This helps you see how strong they are and how well they perform under different types of loads.
One of the best things about JMeter is that it can create realistic test scenarios. Users can set different parameters, like the number of users, ramp-up time, and loop counts, in a “test plan.” This helps to copy real-world usage patterns. By showing many users at the same time, you can measure how well your application reacts, find bottlenecks, and make sure your users have a good experience. Additionally, you can schedule load tests to automatically begin at a future date to better analyze performance over time.
JMeter also has many features. You can create test plans, record scripts, manage thread groups, and schedule load tests to analyze results with easy-to-use dashboards. This makes it a helpful tool for both developers and testers.
Overview of AWS for Testing
The AWS cloud is great for performance testing, especially for those with many years of experience. It provides a flexible and scalable setup. AWS services can manage heavy workloads. They give you the resources to create realistic user traffic during load tests. This scalability means you can simulate many virtual users without worrying about hardware limits.
Some AWS services are very helpful for performance testing. Amazon EC2 gives resizable compute power. This lets you quickly start and set up virtual machines for your JMeter software. Also, Amazon CloudWatch is available to monitor key performance points and help you find any bottlenecks.
Additionally, AWS offers cost-effective ways to do performance testing. You only pay for the resources you actually use, and there is no upfront cost. AWS also has tools and services like AWS Solutions Implementations that make it easier to set up and manage load testing environments.
Now that we understand the basics of JMeter and AWS for testing, let’s look at the important AWS services and steps to ready your AWS environment for JMeter testing. These steps are key for smooth and effective load testing.
We will highlight the services you need and give you advice on how to set up your AWS account for JMeter.
Essential AWS Services for JMeter Testing
To use JMeter on AWS, you should know a few important AWS services. These services help you run your JMeter scripts in the AWS platform.
Amazon EC2 (Elastic Compute Cloud): Think of EC2 as your virtual computer in the cloud. You will use EC2 instances to run your JMeter master and slave nodes. These instances will run your JMeter scripts and make simulated user traffic.
Amazon S3 (Simple Storage Service): This service offers a safe and flexible way to store and get your data. You can store your JMeter scripts, test data, and results from your load tests in S3.
AWS IAM (Identity and Access Management): Security is very important. IAM helps you control access to your AWS resources. You will use it to create users, give permissions, and manage who can access and change your JMeter testing setup.
Setting Up Your AWS Account
Once you have an AWS account, you need to set up the necessary credentials for JMeter to interact with AWS services and their APIs. This involves generating an Access Key ID and a Secret Access Key. These credentials are like your username and password for programmatic access to your AWS resources.
To create these credentials, follow these steps within your AWS console:
Navigate to the IAM service.
Go to the “Users” section and create a new user. Give this user a descriptive name (e.g., “JMeterUser”).
Assign the user programmatic access. This will generate an Access Key ID and a Secret Access Key.
Access Key ID
Secret Access Key
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Important: Keep your Secret Access Key confidential. It is recommended to store these credentials securely, perhaps using a credentials file or a secrets management service.
Boost your application performance with JMeter on AWS. Start your journey to scalable and efficient load testing today!
Having set up our AWS environment, let’s go over how to deploy JMeter on AWS. This process has two main steps. First, we will configure our AWS setup to support the JMeter master and slave nodes. Then, we will install JMeter on the AWS instances we created.
By the time you finish this guide, you will have a working JMeter environment on AWS. You’ll be ready to run your load tests easily. Let’s begin!
Now that we have set up our JMeter environment, let’s learn how to carry out our first load test. This includes understanding how to create test plans in JMeter, setting the parameters for your load test, and running and checking the test on AWS. Specifically, it is important to add an HTTP Header Manager for proper API testing.
By doing these steps, you will get useful information about how well your applications perform and find areas that need improvement.
Developing Test Plans in JMeter
A JMeter test plan shows how to set up and run your load test. It has different parts such as Thread Groups, Samplers, Listeners, and Configuration Elements.
A “Thread Group” acts like a group of users. You can set the number of threads (users), the ramp-up time (time taken for all threads to start), and the loop count (how many times you want each thread to run the test).
Samplers: These show the kinds of requests you want to send to your application. For instance, HTTP requests can mimic users visiting a web page.
Listeners: These parts let you see the results of your test in different ways, like graphs, tables, or trees.
Running and Monitoring Tests on AWS
To run your JMeter test plan on AWS, you start from your JMeter master node. This master node manages the test. It shares the workload with the configured slave nodes. Using this way is key to simulating large user traffic because one JMeter instance alone may not create enough load.
You can watch the test progress and results using JMeter’s built-in listeners. You can also link it with other AWS services, like Amazon CloudWatch, and access the CloudWatch URL. CloudWatch gives you clear data on your EC2 instances and applications. These results help you understand your application’s performance, including response times, how much work it can handle, error rates, and resource use.
By looking at these metrics, you can find bottlenecks. You can see the load capabilities of the software and make smart choices to improve your application for better performanc
Conclusion
In conclusion, knowing how JMeter works well with AWS can improve your testing skills a lot. When you use AWS services with JMeter, you can set up, run, and manage tests more easily. You will also see benefits like better scalability and lower costs. Use this powerful pair to make your testing faster and get the best results. If you want to start this journey, check out our beginner’s guide. It will help you get going. Keep discovering all the options that JMeter on AWS can provide for your testing work.
Frequently Asked Questions
How do I scale tests using JMeter on AWS?
Scaling load tests in AWS means changing how many users your JMeter test plan simulates. You also add more EC2 instances, or slave nodes, to your JMeter cluster. This helps spread the load better. AWS's cloud system allows you to easily adjust your testing environment based on what you need.
Can I integrate JMeter with other AWS services?
Yes, you can easily connect JMeter with many AWS services. You can use your AWS account to save test scripts and results in S3. You can also manage deployments with tools like AWS CodeDeploy. For tracking performance metrics, you can use Amazon CloudWatch.
What are the cost implications of running JMeter on AWS?
The cost of using JMeter on AWS depends on the resources you choose. Things like the kind and number of EC2 instances and how long your load tests last can affect the total costs. Also, data transfer expenses play a role. Make sure to plan your JMeter tests based on your budget. Try to find ways to keep your costs low while testing.
How can I analyze test results in JMeter?
JMeter has different listeners to help you analyze the data from your test runs. You can see these results in graphs, tables, and charts, which is similar to what you would find on a load test details page. This helps you understand important performance metrics, such as response times, throughput, and error rates.
Is there a way to automate JMeter tests on AWS?
Yes, you can automate JMeter tests on AWS. You can use tools like Jenkins or AWS CodePipeline for this. By connecting JMeter with your CI/CD pipelines, you can run tests automatically. This is part of your development process. It helps you keep testing the functional behavior of your web applications all the time.
In today’s fast-paced digital era, where user experience can make or break a brand, ensuring your applications perform seamlessly under different loads is non-negotiable. Performance Testing is no longer just a phase; it’s a crucial part of delivering reliable and high-performing web applications. This is where K6 steps in—a modern, developer-friendly, and powerful tool designed to elevate your performance testing game.
Whether you’re a beginner looking to dip your toes into load testing or an experienced engineer exploring scalable solutions, this guide will introduce you to the essentials of Performance Testing with K6. From creating your first test to mastering advanced techniques, you’ll discover how K6 helps simulate real-world traffic, identify bottlenecks, and optimize your systems for an exceptional user experience.
Key Highlights
Learn why performance testing is important for modern web apps. It helps manage load, response times, and improves user experience.
Get to know K6, a free tool used for load testing. It helps developers create real traffic situations.
Find out how to write your first performance test script with K6. This includes setting up your space, defining tests, and running them.
Discover useful tips like parameterization, correlation, and custom metrics. These can make your performance testing better.
See how to use K6 with popular CI tools like Jenkins.
Understanding Performance Testing
Performance testing is a crucial process in ensuring that an application performs reliably and efficiently under various loads and conditions. It evaluates system behavior, response times, stability, and scalability by simulating real-world traffic and usage scenarios. This type of testing helps identify bottlenecks, optimize resource usage, and ensure a seamless user experience, especially during peak traffic. By implementing performance testing early in the development lifecycle, organizations can proactively address issues, reduce downtime risks, and deliver robust applications that meet user expectations.
The Importance of Performance Testing in Modern Web Applications
In our digital world, people expect a lot from apps. This makes performance very important for an app to succeed. Page load time matters a lot. If an app takes too long to load, has unresponsive screens, or crashes often, users will feel upset. They may even stop using the app.
Load testing is an important part of performance testing. It checks how a system performs when many users send requests at once. By simulating traffic that acts like real users, load testing can find performance issues that regular testing might miss.
Fixing issues early makes customers happy. It also helps protect your brand name. Plus, it makes your web application last longer. For this reason, you should include performance testing in your development process.
Different Types of Performance Testing
Load Testing: Evaluates how an application performs under expected user loads to identify bottlenecks and ensure reliability.
Stress Testing: Pushes the system beyond its normal operational capacity to determine its breaking point and how it recovers from failure.
Scalability Testing: Assesses the system’s ability to scale up or down in response to varying workloads while maintaining performance.
Endurance Testing (Soak Testing): Tests the application over an extended period to ensure it performs consistently without memory leaks or degradation.
Spike Testing: Measures system performance under sudden and extreme increases in user load to evaluate its ability to handle traffic spikes.
Volume Testing: Checks how the application handles large volumes of data, such as database loads or file transfers.
Introduction to K6 for Performance Testing
K6 is a strong and flexible open-source tool for performance testing. It is built from our years of experience. K6 helps developers understand how their applications run in different situations. One of its best features is making realistic user traffic. This allows applications to be tested at their limits. It also provides detailed reports to highlight any performance bottlenecks.
K6 is a favorite among developers. It is popular because it has useful features and is simple to use. In this guide, you will find a complete table of contents. You will learn how to use K6’s features effectively. This will help you begin your journey in performance testing.
What is K6 and Why Use It?
K6 is a free tool for load testing. A lot of people like it because it is made for developers and has good scripting features. It is built with Go and JavaScript. K6 makes it easy to write clear test scripts. This helps you set up complex user scenarios without trouble.
People like K6 because it is simple to use, flexible, and provides great reporting features. K6 works well with popular CI/CD pipelines. This makes performance testing easy and automatic. Its command-line tool and online platform allow you to run tests, see results, and find bottlenecks.
K6 is a great tool for everyone. It is useful for both skilled performance engineers and developers just starting with load testing. K6 is easy to use and very effective. It helps you understand how well your applications are running. Key Features and Benefits of Using K6
K6 has many features to make load testing better. A great feature is its ability to simulate several virtual users. These users can all access your application at the same time. This helps you see how well your application works when there is real traffic.K6 uses JavaScript and HTML to run its scripts. This helps you create situations that feel like real user actions. You can make HTTP requests and work with different endpoints. The tool lets you manage test settings. You can adjust the number of virtual users, request rates, and the duration of the test. Feel free to change these settings to fit your needs.
K6 offers detailed reports and metrics. You can check response times, the speed of operations, and the frequency of errors. It works well with well-known visualization tools. This makes it easier to spot and solve bottlenecks in performance.
Getting started with K6 is easy. You can set it up quickly and be ready to do performance testing like a pro. We will help you with the steps to install it. This will give you everything you need to start your K6 performance testing journey.
First, let’s check that you have all you need to use K6. Setting it up is simple. You won’t need any special machine to get started.
System Requirements and Prerequisites for K6
Before you start your K6 journey, let’s check if your local machine is ready. The good news is that K6 works well on different operating systems.
Here’s a summary:
Operating Systems: K6 runs on Linux, macOS, and Windows. This makes it easy for more developers to use.
Runtime: K6 is mainly a command-line interface (CLI) tool. It uses very little system resources. A regular development machine will work well.
Package Manager: You can install it easily if you have a package manager. Common ones are apt for Debian, yum for Red Hat, Homebrew for macOS, and Chocolatey for Windows.
Installing K6 on Your Machine
With your system ready, let’s install K6. The steps will be different based on your operating system.
Windows:Download the K6 binary from GitHub releases, extract it, add the folder to your PATH, and verify by typing k6 version in Command Prompt or PowerShell.
macOS: Using a package manager is easy with Homebrew. Just type: brew install k6.
Linux: If you’re on a Debian-based system like Ubuntu, use this command: sudo apt-get install k6. For Red Hat-based systems like CentOS or Fedora, type: sudo dnf install k6.
Docker: With Docker, you can create a stable environment. Type: docker pull loadimpact/k6.
To check if the installation worked, open your terminal. Type k6 –version and press enter. You should see your version of K6. If you see it, you are all set to start making and running load tests.
Step 1: Setting Up Your Testing Environment
Before you begin writing any code, set up your environment first. This will make it easier to test your project. Start by creating a folder for your K6 project. Keeping your files organized is good for version control. Inside this folder, create a new file and name it first-test.js.
K6 lets you easily change different parts of your tests. You can adjust the number of virtual users and the duration of the test. For now, let’s keep it simple. Open first-test.js in your favorite text editor. We will create a simple test scenario in this file.
Step 2: Writing Your First Script
Now that you have your test file ready, let’s create the script for your first K6 test. K6 uses JavaScript, which many developers know. In your first-test.js file, write the code below. This script will set up a simple scenario. It will have ten virtual users sending GET requests to a specific API endpoint URL at the same time.
import http from 'k6/http';
import { check, sleep } from 'k6';
export const options = {
stages: [
{ duration: '30s', target: 10 }, // Ramp up to 10 users over 30 seconds
{ duration: '1m', target: 10 }, // Stay at 10 users for 1 minute
{ duration: '10s', target: 0 }, // Ramp down to 0 users
],
};
export default function () {
const res = http.get('https://test-api.k6.io/public/crocodiles/');
check(res, { 'status was 200': (r) => r.status === 200 });
sleep(1);
}
Now, save your first-test.js file. After that, we can move on to the exciting part: running your first load test with K6.
Step 3: Executing the Test
Go to your project folder in the project directory using your terminal. Then, run this command:
k6 run first-test.js
This command tells K6 to read and run your script. By default, K6 creates ten virtual users. Each of these users will send a GET request to the API you set up. You can see the test results in real time in your terminal.
K6’s results give helpful information about different performance metrics. This includes how long requests take, how many requests are sent each second, and any errors that happen. You can use this data to analyze the performance of your application.
Step 4: Analyzing Test Results
Congrats on completing your first K6 test! Now, let’s look at the test results. We will see what they say about how your application is working.
K6 shows results clearly. It points out key metrics such as:
http_req_blocked: refers to the time spent waiting for a free TCP connection to send an HTTP request.
http_req_connecting: refers to the time spent establishing a TCP connection between the client (K6) and the server.
http_req_duration: represents the total time taken to complete an HTTP request, from the moment it is sent to the moment the response is fully received.
iterations: Total test iterations.
K6’s output provides helpful information. Yet, seeing these metrics in a visual form can make them easier to grasp. You might consider connecting K6 to a dashboard tool such as Grafana. This will help you see clearer visuals and follow performance trends over time.
Optimize performance testing with expert tips and insights. Improve processes and achieve better results today!
As you keep going on your performance testing path with K6, you may face times when you need more control and detailed test cases. The good news is K6 has features that can help with these advanced needs.
Let’s explore some advanced K6 techniques. These can help you create more realistic and strict load tests.
Parameterization and Correlation in Tests
Parameterization puts changing data into your tests. This makes your tests seem more real. For instance, when you test user registration, you can use different usernames for each virtual user. This is better than using the same name over and over again. K6 provides tools to help with this process. It lets you get data from outside sources, like CSV files.
Correlation is important for parameterization. It keeps data consistent during tests. For example, when you log in and go to a page made for you, correlation makes sure it uses the correct user ID from the login. This works just like a real user session.
Using these methods makes your load tests feel more realistic. They help you find hidden bottlenecks in performance. If you mix different data and keep it stable during your test, you can see how your application works in various situations.
Implementing Custom Metrics for In-depth Analysis
K6 has several built-in metrics. However, for real-world projects, using custom metrics can be better. For example, you might want to check how long it takes for a specific database query in your API. K6 lets you make and track these custom metrics. This helps you understand any bottlenecks that may occur.
You can use K6’s JavaScript API to monitor timings, counts, and other special values. Then, you can add these custom metrics to your test results. This extra detail can help you spot performance issues that you might overlook with regular metrics.
You can see how often a database gets used when a user takes certain actions. This shows you what can be improved. By setting up custom metrics for your app’s key activities, you gain valuable information. This information helps you locate and resolve performance bottlenecks more easily.
Integrating K6 with Continuous Integration (CI) Tools
To connect k6 with continuous integration (CI) tools, first, place your test scripts in a GitHub repository. Next, set up your CI workflow to run the test file with k6 on a CI server, following a tutorial. You will need to select the number of virtual users, requests, and the duration of the test run. Use the dashboard to see metrics, like response time and throughput. Set up assertions to find any bottlenecks in performance. By automating performance tests in your CI/CD pipeline, you can catch problems early and keep your application strong.
Configuring K6 with Jenkins
Jenkins is a popular tool for CI/CD. It helps you automate tasks in your development process. When you use K6 with Jenkins, you can automatically run performance tests. This takes place every time someone changes the code in your repository.
You should begin by installing K6 on your Jenkins server. Jenkins has a special K6 plugin that makes this process easier. After you install and set up the plugin, you can add K6 tests to your current Jenkins jobs. You can also make new jobs specifically for performance testing.
In your Jenkins job settings, pick the K6 test script that you wish to run. You can also use different K6 command-line options in Jenkins. This lets you change the test settings right from your CI server.
Automating Performance Tests in CI/CD Pipelines
Integrating K6 into your CI/CD pipeline helps make performance testing a key part of your development workflow. This allows you to discover performance issues early on. By doing this, you can prevent these issues from impacting your users.
Set up your pipeline to automatically run K6 tests whenever new code is added. In your K6 scripts, you can define performance goals. If your code does not meet these goals, the pipeline will fail. This way, your team can quickly spot any performance issues caused by recent code changes.
Think about having different performance goals for each part of the pipeline. For example, you might set simpler goals during development. In production, you can then set more demanding goals.
Best Practices for Performance Testing with K6
K6 gives you all the tools you need for performance testing. To get good results in your tests, it is important to use best practices. Being consistent and following these practices is very important.
Here are some helpful tips to boost your performance testing with K6.
Effective Script Organization and Management
As your K6 test suite grows, it is important to make your code easy to read and organized. You should keep a clear structure for your tests. Group similar test cases and use simple names for your files and functions.
Use K6’s modularity to help you. Break your tests into smaller, reusable modules. This will help you use code again and make it easier to maintain. This method is very useful when your tests get more complex. It lets you manage everything better.
Use a version control system, like Git, to monitor changes in your test scripts.
This helps teamwork and lets you go back to earlier versions easily.
Think about keeping your K6 scripts in a separate repository.
This keeps them tidy and separate from your application code.
Optimizing Test Execution Time
Long tests can slow things down. This is very important in a CI/CD environment where quick feedback matters. You need to shorten the time it takes for tests to run. First, look for delays or long sleep timers in your test scripts. Remove them to make everything faster.
Sometimes, you need to take breaks to see how real users behave. But be careful. Long breaks can make the test time feel fake. If you have to include delays, keep them brief. This way, you can keep the test quality high.
You should cut down the number of requests during your tests. Concentrate only on the important requests for your situation. Extra requests can slow down the testing process. Carefully examine your test scenarios. Take out any extra or unneeded requests. This will help boost the overall execution time.
Conclusion
In conclusion, using K6 for performance testing can really help your web application work better. It can also make users feel happier about your site. It’s important to understand the types of performance testing. You should be able to easily connect K6 with CI tools. Using K6 Cloud will allow you to expand your tests. By following good practices, like managing your scripts and improving your methods, you can get great results. Whether you are new or experienced, K6 can help you find and fix performance bottlenecks. This way, your applications will be more reliable and work better. Start your journey with K6 today!
Frequently Asked Questions
How Does K6 Compare to Other Performance Testing Tools?
K6 is a tool that some people like to compare to JMeter and LoadRunner. But it is different in important ways. K6 is designed for developers and uses JavaScript to write scripts. It works well with CI/CD processes. These features make K6 popular among teams that want to keep their code clean and automate their tasks.
Can K6 Be Used for Load Testing Mobile Applications?
K6 does not work directly with mobile interfaces. Instead, it tests the load on the APIs used by your mobile apps. It simulates a large number of requests to your backend system. This helps K6 identify any bottlenecks that might impact the performance of your mobile app.
What Are Some Common Issues Faced During K6 Tests?
During K6 tests, you may run into problems due to bad configuration, network issues, or problems with your testing setup. It's important to look at your K6 script carefully. Make sure your network is stable. You should also try to create realistic loads. These actions can help reduce these problems.
How Can I Integrate K6 Tests into My Development Workflow?
-You can easily use K6 with CI/CD tools like Jenkins or GitLab CI. -Set up K6 tests to run automatically when you change your code. -This helps you find any performance issues early.
Tips for Beginners Starting with K6 Performance Testing
As a beginner, start your K6 journey by understanding the main ideas. After that, you can slowly make your tests more complex. You have many resources available. For example, the official K6 documentation is a great one. These resources provide helpful information and examples to support your learning.
Quality assurance (QA) services are necessary to ensure that any product or service you are putting out there is at its best possible state before you release it. In terms of software delivery, you need to make sure you have proper QA performance testing before you go live.
A lot of people tend to take a lot of shortcuts during this phase because of the notion that there can always be updates and fixes down the line. That said, there are real benefits to conducting thorough performance testing before you go live. Let’s discuss some of its advantages.
Your First Impression On Users Has a Better Chance
People will remember your launch state whether you like it or not. Clients will base their impression on the quality of your app or service upon going live, and their opinion will affect the perception of other potential consumers.
Proper QA performance testing before you go live means that your users will be more likely to have the best first impression. You want to get the best possible version of your product or service so that any feedback from the launch will just work on other tweaks and improvements.
A bad launch can stick with your name even when you make significant improvements over time.
You Can Get Better Performance Before Launch
QA services and performance testing can determine how well your product or service will fare in the real world. Once you’re out, it’s up to the users to determine how well your app or service runs.
Performance testing highlights both the strengths and weaknesses of your software, so you get the chance to make necessary adjustments, additions, and subtractions to streamline performance.
You Can Optimize Capacity
You can determine how many concurrent users your app or service can handle. It’s good to establish limitations and scalability right away, so you can make necessary adjustments for its live state.
You want to find the optimal amount of concurrent users and server usage so you can accommodate them without compromising the security or functionality of your product or service. It’s also good to know that this information is crucial to determine how well your app or service will fare when used or accessed by many people.
You Can Prepare For Expected Challenges
Testing how your product or service will fare with different devices, screen sizes, and environments lets you prepare for some of the challenges that may arise once you’re in the real world.
Even though you may not have all the time and resources to make your launch bug-proof, this can still help you have a head start on solutions toward expected hiccups.
You Can Eliminate Problems and Start Working on Scalability
Performance testing also lets you know how well your app or service can handle and accommodate different types of traffic and brings bugs and other problems to the surface.
This is a big help so that you don’t waste extra resources when you go live trying to eliminate problems that could be avoided already.
Conclusion
The performance testing process is essential for maximizing your results when you go live. The best QA companies will be able to provide the right services so you can have a thorough preparation.
Codoid is one of the top QA companies in the industry because of our passion to help guide and lead the Quality Assurance community. Reach out to us for robust testing solutions.
The level of cost and effort it takes to fix a software bug depends on when the bug is first detected. So it goes without saying that finding bugs at the earliest stages can be instrumental in not only improving the product’s quality but also good for business before and after deployment. If you’re aware of the term, ‘Shift-Left’ Testing, you will know that it can be used to detect bugs at the early stages of development. But you might be confused with the concept of shift-left performance testing as performance testing is very different from the usual shift-left tests such as unit & functional tests.
Performance tests are usually performed at the tail end of the development cycle as it requires a lot of pricey hardware in dedicated testing environments. So in this blog, we will be exploring why is shift-left performance testing important, how to do it, and take a look at its undeniable advantages as well.
Why is Shift-Left Performance Testing important?
We no longer live in a world where users stick to a product just because it is functional. It is extremely hard for products to even reach the right people at this level of competition. So imagine doing all the hard work and reaching your intended end-user only for the person to be unhappy with your product’s performance. According to a report, 47% of users expect a website to load within a mere 2 seconds. The same could apply for all other products and you could lose hours in just a matter of seconds.
That is why as a leading software testing company, we always recommend viewing performance testing to be as important as unit or functional testing. The real severity of any issue is known only when it is time to fix it.
Solutions to performance issues also won’t come easy as they will require architectural reformation. So naturally, shift-left performance testing is the way to go to detect such issues early and fix them with ease.
The key benefits of shift-left performance testing are:
The test cycles become more agile & shorter and in turn boost the project velocity.
Early detection saves a lot of time to ensure faster deployment and delivery to the market.
Reduce the cost to fix performance issues by identifying the defects early (i.e) when they are cheaper to fix.
Helps in developing a bankable product that doesn’t face any unexpected performance issues and makes the releases smoother.
Planning to do performing testing at the very end in higher environments is not easy as other activities such as functional testing, security testing, batch runs, exploratory testing, and infrastructural changes will be happening. So you’d either have to wait until they are over as performance testing can be impacted by such activities.
How to Perform Shift-left Performance testing?
Shift-left performance testing does come along with a lot of challenges, but we always feel that the benefits it has to offer make it an unavoidable practice. Being a leading performance testing service provider, we are now going to explore the various focus points that can help you implement shift-left performance testing at the earliest possible phases of development.
Adopting Test-Driven Development (TDD) and executing Performance Testing at the code level is one of the foundational steps. The challenge here would be defining the Key Performance Indicators (KPIs) at this level. Conventionally, we would be familiar with defining them at an application level. But going the extra mile here will have long-running benefits as defining KPIs for modules and sub-modules will ensure performance at the unit level at first and finally at the application level as well.
Continuous Performance Testing
Integrate performance testing with your CI/CD pipeline by doing performance testing and response time testing for every new feature that is developed during the sprints. So once the newly developed features get integrated with the overall system, performance testing should be conducted to ensure that the newly developed features do not introduce any performance bottlenecks in the overall system behavior.
Service Virtualization
We have already mentioned that not all the components will be ready when it comes to performing shift-left performance testing. So you might wonder how we will be able to do it without the product having the required infrastructure. Even if you develop components in parallel, having all of them ready will be extremely difficult. You could overcome this issue by using a service virtualization tool to define a baseline of those dependent components and model them as well.
Scaling the Load
So when performing such shift-left performance testing, it is important to keep in mind that the load has to be scaled based on the environment that the product will be tested in. Conventional wisdom would mislead us and make us scale the load using a linear approach. But in reality, scaling depends on multiple parameters and should be handled with care.
Automating the Performance Tests
Think beyond just UI testing during the early phases of development and focus on automated database and API tests. The primary reason behind utilizing API & database testing is that it can be used to accurately narrow down the performance issues hotspot in various products. In addition to that, both those tests possess great scalability qualities that can make it easier to scale the tests as the product starts to go through the next stages of development. We had also mentioned that performance regression testing has to be carried out whenever new features are added to the product. So automation of these regression tests will also be a crucial factor as it would take a lot of time if done manually.
We make sure to build robust and scalable automated test suites that can adapt to the change in requirements that can happen at any given moment. So in addition to achieving the primary objective of shift-left performance testing, it will also serve as an end-to-end solution for the product.
Enhanced Dev & Tester Collaboration
Shit-left testing in general isn’t just about moving the testing steps ahead in the pipeline, it is also crucial to have effective communication and collaboration between the developers and testers at the earliest stages of the development process. You can achieve this by using a centralized dashboard that both can access easily.
Using the right tools
There are various tools available in the market that can match our needs. But picking the right one is always a challenge that you wouldn’t want to fail. Here are a few factors you should look into when choosing a tool for shift-left performance testing.
The provision to stay in the IDE.
The ability of the tool to perform the tests using local resources, and scale to the cloud when needed.
Its integration capabilities to the CI/CD process.
At this point, it is pretty obvious that shift-left performance testing is the only way to ensure that your product doesn’t have any very hard-to-resolve performance bottlenecks. So it definitely has to be a criterion to the ‘Definition of Done’. As explained in the blog, it does come with quite a few challenges that might be hard to overcome. But with an experienced QA company such as us on your side, you will be able to create a winning product.
Load testing is a form of software testing that enables teams to test software performance under varying user loads. Load testing aims to emulate real-world scenarios by putting a strain on the application and examining how it responds.
Many teams perform load testing near the end of the project after developers have finished their work. However, this is not the only time to check for performance issues. You can run various forms of load tests throughout the development process to ensure your product will perform well in the real world.
Here are the benefits of load testing in software:
1. Speed Up Software Deployment
Load tests offer valuable information on how your app will perform in the real world. The earlier you test, the easier it is to adjust to the application. Once you have made adjustments, it will be easier to predict when your application is ready to go live.
Software is only as valuable as the speed at which it can be deployed. With load testing, you can deploy your product faster and more confidently.
2. Get Better Insight into Software Performance
Load testing helps you understand how various elements of your app work together. This enables you to determine how well your software and the supporting infrastructure support the demands of the end-user.
For example, your software may crash under load if you have an extensive database and high-volume transactions. With load testing, you can isolate the errors and fix them.
3. Avoid Costly Software Errors
When developers perform load testing, it is easier to anticipate and prevent software errors. This makes it easier to avoid expensive software errors that can cost you and your company valuable resources.
4. Minimize Software Bugs
Software bugs can cause various issues, from frustrating user experiences to data corruption. Load tests help you identify the bugs and fix them before they become a problem.
5. Identify Useful Software Features
A load test can show you how your application works under various parameters. This can give you insight into how users will respond to your app. That insight can help you identify valuable features.
6. Create a Better User Experience
Load tests help you identify and fix issues with your software that could impact the user experience. If you are trying to increase conversions and every shopper has to wait, your conversion rates will suffer. You can fix the problem before you launch.
7. Explore Real-World Scenarios
Load tests help you prepare for real-world scenarios. You can simulate a busy online store, a website experiencing a spike in traffic, or a chat application processing heavy traffic.
Load testing allows you to find and fix potential problems before they happen. It also allows you to identify valuable features and create an enjoyable user experience.
Conclusion
Load testing is critical for any software project. Load testing can identify software problems, help improve the performance of your software and create a better user experience. Load testing is often done near the end of the project after core development work is complete. However, this is not the only time to perform load tests. It is much easier to adjust to the software earlier in the development process.
Codoid is an industry leader in QA with a passion for guiding and leading the Quality Assurance community. Our brilliant team of engineers loves to attend and speak at software testing meetup groups, forums, software quality assurance events, and automation testing conferences. If you need load testing services in the United States, get in touch with us! Let us know how we can help.
If your development is focused on providing HTTP support, Gatling is one of the best performance testing tools that we can use in load generation. Gatling is a Scala, Akka, and Netty-based open-source load and performance testing framework. Despite the fact that it is written in a domain-specific language, the tool provides us with a graphical user interface that allows us to record the scenario. When we finish recording the scenario, the GUI generates the Scala script that represents the simulation. Excited to learn how to master such a tool with so many features like the Gatling Recorder and a guide to creating a new Maven project? You’re at the right place, as we are one of the leading QA Companies with a lot of experience in using Gatling to its full potential.
Features of Gatling:
Let’s kickstart this blog by exploring the prominent features of Gatling.
Excellent HTTP Protocol – It makes Gatling a great choice for load testing web applications or directly calling APIs.
Scala simulation scripts – Since all the Gatling scripts are written in the Scala language, writing load testing scenarios in Scala provides great flexibility.
The Gatling Recorder – The Gatling recorder helps convert the flow of an application into a Gatling scenario. It is very much useful if you come across a complex web application.
The Code can be kept in the Version Control System – As the Gatling load test scenarios are written in the Scala language, they can be easily stored in the Version Control System. So the process of scenario code maintenance gets simplified.
Why Gatling?
Now that we have seen the main features of Gatling, let’s explore the other real-world benefits Gatling offers. Since it is an excellent tool for load/stress testing your system without regarding other performance requirements, several thousand concurrent users can be created from a single JVM. So, Gatling is an excellent tool for you to include in your continuous integration as it doesn’t require you to set up a distributed network of machines to perform testing. Apart from that, it is also useful if you want to write your own code rather than just recording the scripts. Now let’s see how to install Gatling.
Installing Gatling from Website
First and foremost, you have to download the Gatling performance testing tool from their official website. You will find two download options available there, one is the open-source version and the other is the Enterprise edition. We will be using the open-source version for this blog, and so you can go ahead and download that. The Enterprise edition does have a few additional features that you can explore once you are well-worse with the free version. Once your download has been completed, open the folder and unzip it.
Gatling has its own set of installation requirements for Windows and macOS. So you must have a JDK installed to execute the basic version. In addition to that, the utility requires JDK8.
Before we start, make sure to go through the Gatling manual to verify if you have got all the necessary prerequisites ready. Start by going to the bin folder in the unzipped Gatling folder to get Gatling from here. You could also do it by using the command prompt.
You could use Gatling.sh if you’re a Mac user. But since we’re on Windows, we’ll be using Gatling.bat. The tool will start up and run once you double-click on Gatling.bat. We will also be able to run a few example scripts provided by Gatling in the user directories.
If you wish to use command prompt, go to the Gatling Directory and open command prompt. Once you’ve opened the Gatling Directory Command Prompt, you can get the Gatling.bat file by using the following commands as shown in the image below.
cd bin
dir
gatling.bat
Gatling Recorder
We have already established the fact that the Gatling recorder is one of the prominent features of Gatling. As one of the leading Test Automation Companies, we have found this feature to be very resourceful. So let’s learn how to set up and run your recorder as an HTTP proxy or a HAR converter.
The Gatling Recorder assists you in swiftly generating scenarios by acting as an HTTP proxy between the browser and the HTTP server or converting HAR (HTTP Archive) files. In either case, the recorder creates a rudimentary simulation that closely resembles your previously recorded navigation.
So, let’s take a look at how we can record using the HAR option.
Gatling Recorder Prerequisites
1) Gatling should be put in place.
2) The path to the Java Home should be set.
3) The Gatling Home path must be defined.
Gatling Recorder using the HAR File Converter
A HAR file (HTTP Archive) can be imported into the Recorder and converted into a Gatling simulation. The Chrome Developer Tools or Firebug or the NetExport Firebug add-on can be used to obtain the HAR files. Follow the below steps to convert the HAR files to Gatling simulations.
Step 1:
Right-click on the page and click on Inspect to open Developer Tools. Make sure the Preserve log option is checked under the ‘Network’ tab.
Step 2:
Once you finish navigating the website, right-click on the requests you want to export and click on the ‘Export’ option as shown in the below image.
Step 3:
Launch Gatling recorder
Use the below-mentioned command in command prompt to execute the file recorder file from the Gatling directory.
Once you’ve run the above command, the Gatling Recorder will start and you will be able to see the following page.
Step 4:
Check the Recorder mode and make sure that the HAR Converter mode is selected. In this scenario, it is set as ‘HTTP proxy’ by default and so let’s change it to HAR Converter. We will also be seeing how to record using the ‘HTTP Proxy’ mode in the next stage of the blog.
Step 5:
Import the saved HAR file into the recorder and click on the ‘Start’ button.
Step 6:
Once it has been successfully imported, you would have to run the following script using the below command.
So as stated above, we will now be seeing the steps you’ll need to follow to use the recorder using HTTP Proxy.
Step 1:
Configure the Browser
In order to use Gatling to capture our scenario, we must first configure our browser’s proxy settings. The following instructions will help you to set up Chrome for Gatling recording.
Open the Chrome Browser.
In the top right corner, click on the three dots to get a drop-down menu.
Click on the ‘Settings’ option.
Scroll down to the bottom of the settings page and click on the ‘Advanced’ drop down option.
Click on System from the list of options that appear.
Once you click on ‘Open your Computer Proxy Setting’, the proxy page will be shown.
Uncheck the ‘Automatically detect settings’ option.
Check the ‘Use the proxy server for your LAN’ option.
The address should be “localhost” and the port should be “8000”.
Click on the ‘Save’ Button.
Step 2:
Recording the Scenario
First, you have to go to the bin folder of the Gatling bundle. (In our case: C:\Gatling\gatling-charts-highcharts-bundle-3.6.1\bin)
Double click the “recorder.bat” file or run it using command prompt. Follow the same procedure as you did when using the HAR converter.
The recorder window will be displayed.
Enter the port number in the local host box as per your preference. (In our case, we have used 8000).
Enter the package name.
Enter the class name.
Select the following options: “Follow Redirects,” “Infer HTML resources,” “Remove Cache Headers,” and “Automatic Referrers.”
Choose the location of the output files. We have used C:\Gatling\gatling-charts-highcharts-bundle-3.6.1\user-files\simulations.
Note: It’s a good idea to set simulation folders as defaults so that you wouldn’t have to copy the recorder file during load testing.
Keep all the other options to be the same and don’t change any existing options as well.
Click on the ‘Start’ button.
Open Chrome browser and navigate the flow you wish to record.
Once you are done, click the “Stop & Save” button to close the Gatling recording window.
The recorded file will be saved and ready to run. The file will be stored in the directory that you specified in the previous step.
Step 3:
Executing load testing using Gatling
After the import is complete, you can run the script using the command given below.
Creation of First Maven Project Using Scala for Gatling
Before creating a maven Project using Scala, we will look at the prerequisites you will need for its creation.
1) JDK 1.8 or Higher version should be installed in your system
2) The following environment variables have to be set
a. Java_Home Environment Variable
b. Maven_Home Environment Variable
c. Gatling_Home Environment Variable
If you want to check if you have all the prerequisites, you can simply follow the following steps.
Step 1:
Right Click on ‘This PC’ > Properties > Advanced System Settings > Environment Variables > System Variables
Now, you will find all the environment variables available in your system. If you have all the required prerequisites, you can start with the creation of your first Maven Project.
Creating Your First Project
The easiest way to create a new project is by using an “archetype”. An archetype is a general skeleton structure or template for a project.
To create the project we need to follow a few steps:
Step 1:
Run the archetype plugin using command prompt by using the following command.
Once you press enter, you will see Maven downloading many Jar Files by resolving dependencies and downloading them as needed (Only once).
Step 2:
Once all the jar files have been downloaded, assign the groupId, artifactId, and the package name for your classes before confirming the archetype creation.
Step 3:
Once you’ve provided all the required details, you will see a build success message and the location of the particular project that implies your project has been successfully created.
Step 4:
Open the Generated Project using Intellij Idea and follow the below steps to open the project using Intellij.
File > Open > Select the directory for the generated project > Click on the pom.xml file
Once you click to open the pom.xml, you will notice that it takes a little time to load all the dependencies and the project structure. It will also contain the following launchers.
Gatling Engine
Gatling Recorder
The Gatling load test engine can be launched by right-clicking on the Engine class in your IDE. The target/Gatling directory will be used to store the simulation reports.
You can easily start the Recorder by right-clicking on the Recorder class in your IDE. The src/test/Scala directory will be used to construct the simulations. We have attached an image reference to show how it’ll look once everything has been loaded.
Now, you are all set and ready to write your first Gatling script.
To start writing your first Gatling Script first of all we need to create a package with the name simulation under SRC > test > scala as shown below.
Once you have created the simulations folder, we need to create a class under that particular folder and name it as you wish.
Now, you can start writing your script in that particular class. If you’re not aware of the general procedures to follow while writing your script, don’t be worried as we’ve got you covered.
The protocols to be followed for writing the scripts:
The Package Name should be Mentioned
Make sure to import all the important Gatling Classes
The Class should extend the Simulation Class
The script should consist of the below three integral parts
HTTP Configuration
Scenario
Setup
In the HTTP configuration part, we should provide the base URL to pass the header and the value.
Here, we give the scenario a name and execute the request by providing the request URL and an assertion for the particular request.
When it comes to the setup part, we must inject the number of concurrent users utilizing the setup method and pass the protocols.
The Script should be as follows:
package simulations;
import io.gatling.core.scenario.Simulation
import io.gatling.core.Predef._
import io.gatling.http.Predef._
class TestApiSimulation extends Simulation {
//http conf
val httpConf = http.baseUrl("https://reqres.in/")
.header("Accept", value = "application/json")
.header("content type", value = "application/json")
//scenario
val scn = scenario("get user")
.exec(http("get user request")
.get("https://reqres.in/api/users/2")
.check(status is 200))
//setup
setUp(scn.inject(atOnceUsers(1))).protocols(httpConf)
}
Once the script is ready, you can run it by
Clicking right on the ‘Engine’ option
Click Run Engine
After you click on run Engine, you will see the script run and you will be asked to enter the description of the run in the console. Once you have entered the description, you will get the output in the console along with the report link. If you want to view the report, all you have to do is just copy the report link and paste it into any browser.
Global Information Results
Statics Report
Detail Report
Conclusion:
We hope you enjoyed reading our blog while learning how to install & use Gatling to load test an HTTP server and also how to create your own maven project. Using a graphical user interface, we can record a simulation based on a defined scenario, and once the recording is complete, we’ll be good to start our test.
