5 Best Practices for Cloud Performance Testing

The cloud has changed the landscape of application development and deployment. Ever since the pandemic, several companies have shifted to cloud services and technologies, a remarkable 37% year over year increase post-2020. Cloud environments offer scalability, flexibility, and cost-effectiveness, making them ideal for modern applications.

Cloud-based testing helps identify bottlenecks, measure scalability, and make sure that applications can handle expected and exceeded user loads. By proactively addressing performance issues, you can prevent outages, ensure smooth operation, and ultimately provide the users with the quality they deserve.

Understand your cloud environments

The wonderful thing about cloud availability is that it supports a wide range of domains through various cloud environment types. Here are a few of them:

Infrastructure as a Service (IaaS)

Provides the most control over resources (virtual machines, storage, and networking) but requires the most configuration and management effort. Performance depends on the chosen resources and configuration.

Platform as a Service (PaaS)

Offers a development platform with pre-configured resources. Provides a balance between control and ease of use. Performance may be limited by the underlying infrastructure offered by the provider.

Software as a Service (SaaS)

Delivers complete applications over the Internet. Least control over resources but is the easiest to use. Performance depends entirely on the provider’s infrastructure.

Understanding Cloud Performance Testing

The practice of assessing an application's performance that has been deployed in a cloud environment is called cloud performace testing. It assists in measuring scalability, locating any bottlenecks, and confirming that the application satisfies performance goals under varied load scenarios.

Key metrics and Parameters to consider

• Response Time
  Time taken for the application to respond to a user request.
• Throughput
  The number of requests handled in a certain amount of time.
• Scalability
  ‍Ability of the application to handle an increasing user load.
• Resource Utilization
  ‍How efficiently the application utilizes cloud resources (CPU, memory, and network).
• Concurrency
  ‍Ability of the application to handle multiple user requests simultaneously.

Various types of cloud performance testing

Cloud-based testing encompasses various approaches, each targeting specific aspects of application behavior under load. A range of techniques and methodologies are tailored to assess different aspects of app performance in the cloud environment.

Load Testing

• Purpose: Cloud-based load testing simulates increasing user loads to identify performance bottlenecks.
  
• Scenario: A popular e-commerce website during a holiday sale. To assess how the system responds to the increased traffic, the load test progressively raises the number of concurrent users.
  
• Objective: Check to see whether the program can sustain the anticipated load without crashing or slowing down.
• ‍Metrics: Response time, throughput, and resource utilization. To learn in detail about performance metrics, we recommend reading our Concepts and Metrics of performance testing.

Stress Testing

• Purpose: Stress testing pushes the application beyond normal usage to assess breaking points.
  
• Scenario: Consider an online banking platform. Stress tests bombard it with excessive transactions, concurrent logins, and heavy database queries.
  
• Objective: Identify the system’s limits, such as maximum user load or transaction volume.
• ‍Metrics: Response time under extreme load, error rates, and system stability.

Scalability Testing

• Purpose: Scalability testing evaluates the application’s ability to scale resources to meet growing demand.
  
• Scenario: Suppose a cloud-based video streaming service. Scalability tests increase the load gradually to observe how well the system scales (adds more servers, resources, etc.).
  
• Objective: Verify that the app can handle increased traffic without compromising performance.
• ‍Metrics: Resource allocation, response time, and auto-scaling efficiency.

Soak Testing

• Purpose: Soak testing simulates sustained user load over extended periods to uncover stability issues.
  
• Scenario: Imagine a social media platform. Soak tests run for hours or days, continuously stressing the system.
  
• Objective: Detect memory leaks, database connection issues, or performance degradation over time.
• ‍Metrics: Memory usage, response time consistency, and system stability.

Spike Testing

• Purpose: Spike testing simulates sudden bursts of traffic to assess the application’s responsiveness.
  
• Scenario: Picture a ticket booking website when tickets for a popular event go on sale. Spike tests simulate a sudden surge in user requests.
  
• Objective: Evaluate how quickly the system can handle the spike without crashing.
  
• Metrics: Response time during the spike, error rates, and system recovery time.

Best practices for cloud performance testing

Now let’s get down to the main objective of this blog post, the five most effective practices or strategies that every quality assurance engineer must adopt for cloud performance testing.

1. Setting clear performance objectives

Imagine driving a car without a destination in mind. How can you measure progress or know when you’ve arrived? The same applies to cloud performance testing. Clearly defined objectives act as your roadmap, guiding your testing efforts and making sure you gather meaningful data.

The SMART framework helps establish focused and achievable performance goals. Here’s how to apply it:

• Specific: Clearly define the performance aspect you want to improve. Instead of a vague goal like “improve performance”, aim for something like “reduce the average response time for product page loads by 20%”.
  
• Measurable: Identify metrics to track progress. In this case, you’d use the average response time in milliseconds.
  
• Achievable: Set realistic goals based on your application’s functionality and current resource allocation. Don’t aim for a 1-second response time if your application relies on complex calculations.
• ‍Relevant: Align your goals with business needs and user expectations. A faster checkout process on an E-commerce platform directly impacts conversion rates.
• Time-bound: Define a timeframe for achieving your objectives. This creates a sense of urgency and helps prioritize testing efforts.
  

Let’s take a real-life example of an E-commerce platform.

• Specific: Maintain a response time of under 500 milliseconds during peak shopping hours and during weekends. Achieve a system uptime of 99.9% over a one-month period.
  
• Measurable: Measure the number of concurrent users the platform can support without exceeding 500 ms of response time.
  
• Achievable: Create a dummy promotional event or holiday where the infrastructure should handle the expected surge of users.
  
• Relevant: Enhance the user experience and minimize bounce rates by optimizing page load times.
• ‍Time-bound: Achieve the performance target before the start of the holiday shopping season.

2. Perfect use of the cloud’s scalability

Unmatched scalability is provided by cloud environments, enabling dynamic resource provisioning and de-provisioning in response to demand. Because of its flexibility, testers can replicate real-world situations with different user activity and workload levels.

Unlike traditional on-premises infrastructure, cloud platforms provide instant scalability without the need for manual intervention, making it easier to conduct performance tests at scale.

Types of performance scaling tests

• Horizontal scaling tests: Add more application instances (horizontal scaling) to assess how the app behaves when distributed across multiple servers. This helps determine if your application can leverage horizontal scaling for increased capacity.
  
• Vertical scaling tests: Increase resource allocation (CPU, memory) for a single application instance (vertical scaling) to measure performance gains with more powerful hardware. This helps identify if resource limitations are causing any bottlenecks.

Before and After cloud performance testing for an E-commerce platform.

The expected response time for the example project is 100 ms of response time.

3. Designing realistic test scenarios

Imagine testing a social media app with just login scenarios. It wouldn’t reflect real-world usage where users post content, interact with friends, and upload photos. Realistic test scenarios that mimic user behavior are crucial for uncovering potential performance issues that might arise during the actual use of the product.

Let’s look at how you could craft realistic scenarios:

• User persona development: Create user personas representing different user types (e.g., casual browser, frequent poster, mobile user). Each persona should have a defined set of actions they perform within the application.
  
• Think like a user: Map out typical user journeys, including login, browsing content, performing actions (e.g., posting a video, posting comments), and logout.
  
• Load balancing: Simulate different user loads throughout the day. Morning login surges, peak traffic during business hours, and evening entertainment usage patterns should all be reflected in your test scenarios.

4. Always monitor and analyze performance metrics

Not monitoring and analyzing performance metrics is like conducting a science experiment without observing the results. Performance testing without real-time monitoring leaves you blind to the impact of your tests. Monitoring allows you to track key metrics and identify performance issues during testing.

Key KPIs to look out for during testing:

• Response time: The amount of time it takes a program to reply to a request from a user. This is an essential user experience metric.
  
• Throughput: The number of requests processed per unit time. This indicates how efficiently your application handles concurrent user activity.
  
• Resource utilization: Track CPU, memory, and network usage to identify if resource limitations are causing performance issues.
  
• Error rates: Monitor the number of errors encountered during testing. A spike in errors could indicate overloaded servers or application bugs.
  
• Concurrency: Measure how well the application handles multiple user requests simultaneously. High concurrency issues can lead to slowdowns or crashes.

The majority of cloud service providers have integrated monitoring tools or third-party platform interfaces, such as Datadog and New Relic. These tools let you efficiently monitor performance indicators using real-time dashboards, visualizations, and alerts.

5. Optimize and Iterate

Test results are a gold mine for optimizing your cloud infrastructure. By analyzing the test results and resource limitations, you can:

• Right-size resources: Adjust virtual machine configurations (CPU, memory) to ensure efficient resource usage without overpaying.
  
• Auto-scaling: Implement automation testing that automatically scales resources (up or down) based on real-time demand. This helps maintain optimal performance while avoiding unnecessary costs.
• ‍Caching: Use caching techniques to save data that is accessed often, which will lighten the strain on the application server and speed up response times.

The importance of iterative testing

Performance optimization is an ongoing process, it's not a one-time thing, rather, there is always an opportunity to optimize the product to a level further beyond the threshold. Here’s why iterative testing is crucial:

• Shifting business needs: As your business grows and user demands evolve, performance needs might change. Iterative testing helps adapt your cloud infrastructure to stay one step ahead of these changing requirements.
  
• Evolving cloud landscape: Cloud providers constantly introduce new features and services. Iterative testing helps ensure your application takes advantage of these advancements for optimal performance.
• ‍Continuous improvement: Regular performance testing with evolving application features and usage patterns helps identify new bottlenecks and ensure ongoing performance excellence.

Top tools and technologies for cloud performance testing

The best cloud-based testing tools for you will depend on your budget and unique requirements. Here is a summary of several well-liked choices, with an emphasis on their features, advantages, and special features.

PFLB

PFLB stands for Performance-Focused Load Balancer, a cloud-native load balancing solution designed to distribute incoming traffic across multiple instances for optimal performance. It dynamically adjusts traffic distribution based on real-time performance metrics to ensure efficient resource utilization and minimal latency for end users.

• ‍Pros of PFLB:
  • ‍Ability to seamlessly scale with increasing traffic volume, accommodating growing application demands without manual intervention.
  • The fault-tolerant architecture of PFLB ensures high availability and reliability, minimizing service disruptions.
  • PFLB offers intuitive configuration options, allowing users to define routing rules and load-balancing algorithms effortlessly.

PFLB’s unique selling point lies in its ability to prioritize performance optimization while maintaining fault tolerance and scalability. By dynamically adjusting traffic routing based on real-time performance data.

• Installation guide:
  • Step 1: Sign in to your cloud provider’s management console.
  • Step 2: Navigate to the networking or load balancing section.
  • Step 3: Choose to create a new load balancer and select PFLB as the type.
  • Step 4: Configure the load balancer settings, including routing rules, health checks, and target instances.
  • Step 5: Complete the installation process and verify the functionality of the load balancer.

SOASTA CloudTest

SOASTA CloudTest is an adequate performance cloud testing platform that enables organizations to simulate real-world user behavior, analyze app performance, and identify bottlenecks. It offers a range of features, including load testing, stress testing, and real-user monitoring.

• Pros of SOASTA CloudTest:
  • ‍An easy-to-use interface offered by SOASTA CloudTest makes it easier to create, run, and analyze tests.
  • SOASTA Cloud Test provides a unified platform for all your performance testing needs, eliminating the need for multiple tools.
  • The platform offers visual scripting capabilities alongside traditional code-based testing, making it accessible to testers with varying technical skill sets.

CloudTest’s selling point lies in its ability to offer end-to-end performance testing capabilities, from test creation to result analysis. By providing a solution for load testing and monitoring.

• Installation guide:
  • Step 1: Sign up for a SOASTA CloudTest account on the official website.
  • Step 2: Download and install the CloudTest software on your local machine or cloud instance.
  • Step 3: Follow the on-screen instructions to set up your testing environment and configure test scenarios.
  • Step 4: Execute the tests and monitor the results using the CloudTest dashboard.
  • Step 5: Analyze the performance metrics and take the necessary actions to optimize application performance.

K6

Using K6, an open-source performance testing tool, we can create JavaScript test scripts and run large-scale tests. Because of its developer-friendly architecture, teams can easily integrate cloud software testing into their pipelines for continuous integration and delivery.

• Pros of K6:
  • K6 is lightweight and efficient, making it suitable for testing applications of any size or complexity.
    
  • Leverages JavaScript (ES6) for writing test scripts, offering a familiar and efficient language for developers.
    
  • K6 integrates seamlessly with cloud environments and containerization technologies like Docker.

K6's selling point lies in its simplicity and flexibility. By leveraging the power of JavaScript for test scripting, K6 enables us to create and execute performance tests with ease, facilitating rapid feedback loops and continuous improvement.

• Installation guide:
  • Step 1: Download the K6 binary or install it via package manager (e.g., Homebrew, Chocolatey).
  • Step 2: Verify the installation by running the "k6 version" command in the terminal.
  • Step 3: Write your test scripts using JavaScript or import existing scripts from the K6 script repository.
  • Step 4: Execute the tests using the "k6 run" command and monitor the results in real-time.
  • Step 5: Analyze the performance metrics and iterate on your test scenarios as needed.

Gatling

A Scala-written high-throughput load testing tool for assessing application performance and simulating concurrent users is called Gatling. It is appropriate for testing complex web applications and APIs since it has a strong scripting engine and extensive reporting features.

• ‍Pros of Gatling:
  • Being open-source, Gatling offers greater flexibility and customization compared to some commercial tools.
  • Gatling can handle large-scale load testing scenarios effectively.
    
  • Gatling provides a wide range of features, including performance reports, comprehensive data analysis, and integration with CI/CD pipelines.

Gatling is a powerful option for experienced testers or development teams comfortable with Scala. It provides extensive features, scalability, and the flexibility of an open-source solution.

• Installation guide:
  • Step 1: Download the Gatling bundle from the official website and extract it to your desired location.
  • Step 2: Navigate to the "bin" directory and execute the Gatling script (e.g., "gatling.bat" for Windows or "gatling.sh" for Unix).
  • Step 3: Choose the desired simulation scenario or create a new one using Gatling's DSL (Domain-Specific Language).
  • Step 4: Configure the test parameters, such as the target URL, number of users, and ramp-up period.
  • Step 5: Run the simulation and monitor the results using Gatling's real-time dashboard.

Conclusion

Cloud performance QA plays a pivotal role in this endeavor by enabling organizations to proactively identify and address performance issues, optimize resource utilization, and ensure the reliability and scalability of cloud-based applications.

As businesses increasingly rely on cloud-based solutions, ensuring exceptional cloud application performance has become a fundamental for success. That’s where Alphabin comes in. We are a trusted partner for businesses seeking to optimize their cloud applications. Our team of performance quality professionals will provide you an upper hand when it comes to performance quality.