In the fast-paced world of software development, ensuring your applications can withstand real-world traffic is crucial. In this blog post, we’ll embark on a journey through the field of automated load testing. We’ll explore why load testing matters, how we chose the right tool, and share valuable insights gained along the way.
First of all, what is load testing?
Load testing software is like stress-testing a bridge before it opens to traffic. It helps us identify weak points to ensure that your application can handle the real-world load without crumbling.
It places a simulated “load” or demand on your web application to ensure that it remains stable during operation. During a load test, the testing software will measure the capacity of your web application through transaction response times.
One of the key advantages of load testing is its ability to simulate realistic user activity. By simulating the behavior of actual users, we can recreate scenarios that our application might face in the real world. This approach enables us to uncover performance issues that might otherwise go unnoticed in a controlled environment.
Load testing also helps to provide a seamless user experience even under heavy usage. We can also proactively address issues, improve efficiency, and deliver high-quality software to our clients.
Choosing the Right Load Testing Tool for WebRTC Applications
When it comes to load testing WebRTC applications, selecting the right tool is paramount. In our quest for an effective solution, we encountered two prominent alternatives: TestRTC and Loadero.
TestRTC
TestRTC is undeniably a robust choice, offering a comprehensive suite of features tailored for WebRTC load testing. Its capabilities are extensive and cater to complex testing scenarios. TestRTC’s pricing model is based on purchasing testing hours in advance.
Loadero
Loadero offers simplicity and ease of use. It provides a streamlined, easy-to-understand interface. Loadero’s operates on a pay-per-simulated-user model. My QA colleague, Andrée Gutiérrez, wrote a great technical post on Load Testing for WebRTC with Loadero.
In the field of load testing for WebRTC applications, the choice between Loadero and TestRTC ultimately depends on your unique needs and specific use case. Both platforms offer robust solutions that can help you ensure the reliability and performance of your real-time communication applications.
The Virtual Classroom EdTech Test Case
In one of our recent projects, we were tasked with conducting a load test for a virtual classroom-based edtech application. This application revolves around the interaction between instructors and students, creating a dynamic and real-time virtual classroom environment.
To meet this challenge, we developed an automated load testing approach that we’d like to share with you today.
What you see in the next section is a simplified representation of our testing scenario. We aimed to replicate this flow multiple times within a single test run to simulate a substantial user load effectively.
Test Parameters & User Flow
Our load test involved:
8 students and 2 instructors per session (Classroom)
The user flow was as follows:
- Login: Simulating the login process for each user.
- Accept Waiting Room Users: Emulating the admission of users from the waiting room into the classroom.
- Turn On Camera: Activating the camera for video transmission.
- Pin (Single Stream Connection “1:0 Video Call”): Pinning a single user’s video stream for focused viewing.
- Connect (Both Ways Connection “1:1 Video Call”): Establishing a bidirectional video call connection between users.
In our largest test, this flow simulated 720 sessions with 10 users each. With 2 instructors and 8 students in each, this gives a total of 7200 users.
It’s important to note that we didn’t immediately subject our system to this high load. Instead, we incrementally increased the load until we achieved a favorable success rate while maintaining the desired user load.
Tangible Application Improvements Based on Test Insights
The results of our load testing efforts had a significant impact on enhancing the application. Here’s how we used the insights gained from load testing to make tangible improvements:
1. Enhanced Auto Scalability
Load testing revealed crucial insights into our application’s autoscaling capabilities. By simulating heavy user loads, we were able to identify the precise points at which our server infrastructure needed to scale to meet demand.
This information was invaluable in optimizing our server resources, ensuring that we could efficiently accommodate traffic spikes without sacrificing performance. For example, we utilized ECS scheduled tasks to ensure that extra containers were started during spiked traffic periods.
2. Optimized Resource Allocation
Load testing helped us fine-tune our resource allocation strategy. We were able to pinpoint resource-intensive components in our application and allocate resources more effectively. This not only improved overall system performance, but also led to cost savings by avoiding unnecessary over-provisioning.
3. Improved User Experience
One of the most critical outcomes of load testing was the identification of potential bottlenecks and areas of suboptimal performance. With this knowledge, we implemented targeted improvements to eliminate these bottlenecks, resulting in a smoother and more responsive user experience.
4. Identify UI Issues
Load testing revealed UI issues that surfaced when a significant number of users were on board. These insights enabled us to refine the user interface, ensuring a seamless experience even during peak usage.
5. Enhanced Error Handling
Load testing also helped us uncover edge cases that could lead to errors under extreme conditions. We refined our error handling and recovery mechanisms to ensure the application remained stable, even when subjected to heavy loads.
6. Cost Reduction
By load testing, we gained insights into how efficiently our application was utilizing resources. This allowed us to optimize our cloud service subscriptions and reduce unnecessary expenses.
7. Improved Load-Balancing Strategies
Load testing provided data on how our application handled traffic distribution. We fine-tuned our load-balancing strategies to ensure even distribution of users across our servers, preventing overload on specific instances.
Conclusion
We’ve taken you on a journey through the world of automated load testing, showcasing its significance and the transformative impact it can have on your applications.
It’s important to reiterate that the enhancements we’ve discussed are just a glimpse into the advantages of load testing. Load testing is a multifaceted practice that yields a wide range of insights and benefits. It serves as a proactive measure to ensure your application not only meets but exceeds user expectations.
Our real-world case study highlighted the tangible benefits of load testing, from optimizing auto scalability to resource allocation and improving user experiences. The world of load testing is rich with benefits. Its potential impact on your application’s success is immeasurable.
Thank you for reading. If you need help load testing your application, reach out to the experts at WebRTC.ventures!
