A Guide to the Must-Have Features for Performance Testing Services

December 14, 2023

Performance testing evaluates the speed, responsiveness, and stability of an application or system when subjected to the expected workload. The primary objective of performance testing is to assess response times and latency, ensuring that the system complies with performance criteria for end-users or other software applications interacting with it (such as through an API or database). Essentially, performance testing addresses these questions:

  • “What is the system’s response time to transaction requests?”
  • “What are the system’s resource utilization patterns under different levels of load?”

The significance of performance testing lies in its ability to assess whether an application or system functions as intended under specific conditions. It helps developers and testers detect performance bottlenecks, resource constraints, or vulnerabilities in the early stages of development. This provides insights that help developers ensure a positive and consistent experience for end-users and optimize their applications’ performance and scaling.

This article discusses the desirable features of modern performance testing services and how they compare to more traditional performance testing techniques. Although traditional techniques are effective in some scenarios, they often introduce complexities, demand substantial resources, and impose financial and temporal burdens on projects. For this reason, we discuss how an effective performance testing service can alleviate many of these concerns. In doing so, we highlight key features to look for when choosing a performance testing service for your application.

Summary of key features of performance testing services

The table below identifies six features to look for when considering a performance testing service. A more in-depth discussion of each feature can be found in the sections that follow.

Desired Feature Description
Quick setup and cross-stack testing capability The tool should enable rapid, hassle-free performance testing across any tech stack without the use of proprietary languages or tools and with minimal configuration and setup time.
Test case and data management The tool should allow teams to easily document, organize, and maintain test cases and data for seamless performance testing and historical tracking of an application’s evolution.
Infrastructure management Hosted tools allow teams to avoid the hassle of setting up, managing, and scaling the infrastructure required for tests, which can significantly reduce overhead.
Ability to test any protocol with third-party packages The service should facilitate testing databases, sockets, gRPC, or other protocols in addition to HTTP requests.
Versatility for both enterprises and startups The tool should provide advanced features and integrations for complex enterprise scenarios as well as smaller-scale startups that wish to test their MVPs.
Custom metrics and log analysis The tool should support the creation of custom metrics to monitor application-specific performance indicators over time.

Quick setup and cross-stack testing capability

Ideally, the performance testing service should be easy to set up, with no need to learn proprietary languages or tools or write complicated configuration files. Avoiding these steps significantly speeds up the testing and development processes because learning a proprietary scripting language for writing tests and replicating production environments can be complex and time-consuming.

Another key feature to look for in performance testing services is compatibility with popular code repository hosting platforms like GitHub.

The service should also seamlessly integrate with any tech stack, eliminating the need for extensive configuration adjustments. This high level of compatibility significantly speeds up the setup process, enabling your team to smoothly shift from the initial setup to actual testing.

Test case and data management

The importance of saving and maintaining proper test cases and test data for future use is often overlooked in assessing performance testing services. Having a centralized storage repository for these resources is desirable because it can contribute to more effective test case and test data management; it is also a compliance requirement in certain industries, such as finance and healthcare.

Test case management

Properly documenting, saving, and maintaining test cases for future use can significantly impact the testing process’s efficiency and effectiveness. It provides a historical reference that allows you to track your application’s evolution over time and serves as a foundation for generating comprehensive test reports.

To help your team better maintain and manage test cases, keep in mind the following best practices:

  • Group test cases by modules or features to keep them organized: Create separate directories or test suites for different categories of tests (such as functional, integration, and regression).
  • Use a priority system to prioritize test cases based on their impact and likelihood of defects: Generally speaking, defects tend to cluster in areas that rely on interactions among different system components (such as sending/receiving data between the client and the database).
  • Manage test data separately from test cases: Store test cases in a version control system to track changes and updates.

Test data management

Test data includes the specific datasets and scenarios used to assess an application’s performance under various conditions. Effective test data management involves organizing, storing, and maintaining these datasets for testing purposes.

Because test data often contains sensitive or personal information, it is crucial to manage it in compliance with data protection regulations like GDPR, HIPAA, or CCPA. In addition, it is essential to ensure that the test data also reflects real-world scenarios and remains consistent across different testing phases and environments.

Proper test data management also addresses issues related to data privacy and security, ensuring that sensitive or personal information is protected during testing. For instance, if your application handles sensitive data (such as user information), the development team should mask this information using a data masking tool like K2view. Data masking replaces sensitive data with fictional or scrambled data while maintaining the data’s structure and format, which ensures data privacy while maintaining the integrity of the test.


Infrastructure management

Choosing your application’s testing infrastructure is a critical decision that can significantly impact the testing process. Setting up and maintaining infrastructure to mimic real-world conditions is a complex process, and failing to do so properly can lead to errors and inefficiencies in tests and test results.

There are several options for test infrastructure, each with its own set of advantages and difficulties.

Local (on-premises)

A local testing infrastructure entails conducting performance tests using an organization’s on-premises computing resources. The primary drawback of this approach is that in-house performance testing often requires provisioning additional physical resources to generate load, and there can be a sunk cost for the setup of this infrastructure. As an application scales, additional computing resources must be provisioned accordingly.

On the other hand, this approach offers full control over the testing environment, which also provides full control over security. This can be a benefit or a potential drawback: Avoiding the use of cloud-based resources can lead to better security within a testing environment, but in-house environments can have security vulnerabilities if they are not properly configured or updated.


Leveraging cloud infrastructure for performance testing has gained immense popularity due to its scalability and flexibility. Services like AWS, Azure, and Google Cloud provide on-demand resources, allowing testers to simulate various scenarios easily. In addition, many cloud providers adhere to rigorous security and compliance standards, which mitigates security concerns and can be advantageous for businesses in regulated industries. Utilizing cloud resources can also provide cost savings in comparison to provisioning on-premises machines. However, the cost of cloud resources can still quickly escalate if those resources are not managed efficiently.


Hybrid infrastructure integrates aspects of both local and cloud setups. It utilizes cloud resources for scalability when needed while maintaining the reliability of an on-premises environment. This more flexible approach can be difficult to configure and scale depending on application infrastructure, but it allows development teams to tailor the environment to their own requirements and security standards.


Although not testing infrastructure in and of themselves, containers are often used to create test environments. Containerization ensures a consistent application or testing environment, which eliminates issues related to hardware, operating systems, and missing or incompatible dependencies. In addition, containerization services like Docker provide versioned container images, which makes it easy to reproduce test environments at different points in time. This is valuable for regression testing and ensuring that new changes do not break existing functionality.

A single Docker image can be used to spin up multiple containerized test environments (Source)

One drawback to using containers is that they can demand significant system resources, such as CPU and memory usage, depending on how containers are configured, the scale of the tests being conducted, and the nature of the application under test. This consideration is particularly important for companies with limited testing resources.

Performance testing services

Performance testing services come in the form of third-party vendors and, more recently, hosted SaaS services. While both can save time and effort in setting up and managing the test infrastructure, cases, and execution processes, there are important differences between the two options that should be considered.

  • Third-party performance testing vendors: Third-party performance testing vendors specialize in end-to-end performance testing services, taking on complete responsibility for performance testing from initial setup to final reporting. This approach means that the development team can focus on core tasks while experts conduct the testing. However, this approach may slow down development and is not well-aligned with agile methodologies and shift-left testing practices, which emphasize early testing and rapid iteration.
  • Hosted performance testing services: These services offer a convenient and efficient solution for companies aiming to streamline their testing processes. Hosted services are user-friendly and often designed to be intuitive, making them accessible to a broad range of teams regardless of technical expertise. This simplification allows organizations to rapidly set up performance testing, making it more practical and less resource-intensive. Hosted tools like Multiple also offer nearly infinite scalability on demand, which effectively alleviates scalability concerns in performance testing. This enables businesses to easily adjust testing capacity to match fluctuating workloads.


Ability to test any protocol with third-party packages

The ability to utilize third-party packages (such as npm packages) in test scripts offers a significant advantage: the ability to test a wide range of protocols. This means you can evaluate not only standard protocols like HTTP requests but also other protocols such as WebSockets, REST, MongoDB, GraphQL, Redis, gRPC, and more. With the rise of microservices, this is an especially important consideration.

Choosing a tool that easily facilitates this feature allows developers to write test scripts like they do client-side code, which speeds up the testing process and allows test scripts to more closely resemble real user interactions. It also allows teams to evaluate the interactions between system components rather than simply testing each component in isolation.

The UI of a performance testing service that supports the use of npm packages

Versatility for both enterprises and startups

Whether your product falls into the category of enterprise-level software with a complex architecture or is designed as a minimal viable product (MVP) for a startup, the performance testing service you choose should accommodate both scenarios. Although there is certainly overlap between the features useful for enterprise-level software and startups, we have provided a categorized list of features below.

Enterprise-level software:

  • Scalability: Enterprise-level software often experiences fluctuating usage demands, so the testing service should seamlessly scale to simulate these variations. It should be capable of conducting large-scale performance tests to ensure that the software can handle extensive workloads.
  • Advanced integrations: Enterprise software may rely on various third-party services and databases and may have complex integrations. The performance testing service should support testing these intricate dependencies.
  • Security: Many enterprises prioritize data security to protect their brand images or to comply with data privacy regulations. The testing service should provide robust security measures to protect sensitive information during performance tests.


  • Cost-effectiveness: Startups may have limited financial resources. The service should be budget-friendly, offering economical pricing plans suitable for smaller teams that can be upgraded as the application scales.
  • Minimal configuration: As mentioned previously, the quick setup and stack compatibility features are essential for startups hoping to transition from idea to MVP as quickly as possible. Reducing the time needed to write test cases and configure testing infrastructure significantly reduces time to market without compromising confidence in the product’s reliability.

Custom metrics and log analysis

Metrics play a crucial role in the context of performance testing by providing valuable insights into the behavior and health of a system under various conditions. Some common performance metrics include response time, throughput, and network latency. Metrics serve as benchmarks to compare performance across different versions of the application. The ability to create custom metrics specifically designed to measure project-specific aspects (for instance, database queries per second, GPU usage, or disk I/O) is also desirable. In the code snippet and figure below, notice how the custom metrics are created in the test script and appear in the graph after it.

let startTime = Date.now();
// Capture the time taken for the POST request. Adding "(API)" to separate it from the VU Loop metric.
ctx.metric('Post /chat', Date.now() - startTime, 'ms (API)');

startTime = Date.now();
// Send a GET request to the chat endpoint
await apiClient.get('chat');

// Capture the time taken for the GET request
ctx.metric('GET /chat', Date.now() - startTime, 'ms (API)');

Although performance metrics can be analyzed as raw data, access to a dashboard that provides a graphical representation of performance metrics helps testers consistently monitor important metrics, share test results with other team members, and better track product health.

In addition, the ability to store test results centrally with role-based access control (RBAC) facilitates easier collaboration among team members. The RBAC approach also helps organizations manage security, control access, and maintain the principle of least privilege. Permissions can be granted to allow different team members to observe and monitor real-time test runs or access the test results data for further analysis and collaboration.



Performance testing services offer a streamlined approach to performance testing and allow engineers to spend more time developing features without worrying about the complexities, resource demands, and management challenges associated with in-house performance testing.

Hosted performance testing services like Multiple provide a cost-effective and efficient alternative to third-party performance testing vendors by harnessing cloud-based infrastructure, employing automation for scalability, and providing user-friendly interfaces. Tools like Multiple empower development teams to conduct performance testing without extensive hardware procurement, and they allow both technical and non-technical team members to contribute to the performance testing process.

Ultimately, choosing an effective performance testing service helps teams deliver software that performs reliably, meets user expectations, and increases user satisfaction. We hope that the desired features presented in this guide will help your team choose a performance testing service that fits your needs.