Performance Testing Strategy Document
The Importance of Performance Testing in Azure
Performance Testing Services
Performance testing ensures user experience consistency and reliability. Performance testing is essential for app responsiveness, stability, and speed. To ensure the application can handle expected user volume, performance testing simulates user loads and scenarios to find bottlenecks. Performance testing can optimize application efficiency and responsiveness through thorough analysis. Changes to an application can affect performance and stability.
Performance testing should be integrated into CI/CD pipelines to catch regressions. Performance testing tools like Azure Load Testing make it easy to start and analyze metrics to find and fix performance bottlenecks. Azure Load Testing simplifies performance testing by helping you start and analyze metrics to find and fix bottlenecks.
“Application reliability is crucial in today’s digital world. Application smoothness is essential as we use digital technologies for communication, commerce, and daily tasks. No matter the platform or device, users expect apps to be available and responsive. Application reliability matters in e-commerce, finance, healthcare, and other critical sectors.
Variety of performance testing
Performance tests can improve application reliability and efficacy in different ways.
Application load testing: Can it handle expected load?
Stress testing: Test the application’s response and recovery under extreme conditions.
Soak/Endurance testing: How does the app perform over time?
Breakpoint testing: Maximum application load?
Test scalability: Does the app scale with load?
Test strategy
Understanding key application reliability and effectiveness factors is essential to a thorough performance testing strategy. They will discuss test definition, execution, and analysis in this section.
Define the test
A solid strategy starts with realistic user scenarios. Tests that closely simulate user behavior provide a more accurate assessment of the system’s responsiveness and performance in real life. Some methods are:
Develop user personas from real-world usage. User roles, interaction frequency, and workflows should be considered.
Interrupt user actions with thought time. Users don’t use apps constantly. Delays between actions simulate real user thinking and interaction patterns to better represent user behavior.
Simulate the application’s user load variability. Actual user traffic is rarely constant, so performance tests should include scenarios with varying concurrent users to assess how the system handles demand fluctuations.
User transactions often involve multiple steps. Create tests that simulate complex transactions like buying, submitting, or navigating multiple pages.
Consider actual user geography. For global applications, simulate tests from different locations to determine how latency and network conditions affect performance.
Benchmarking is another important performance testing strategy. Performance benchmarks set measurable standards for application performance. These benchmarks allow comparison of builds or versions and identification of performance improvements or regressions over time. Frequent load tests establish a baseline for these benchmarks and are part of application quality gates. Typically, response time, throughput, error rate, resource utilization, and network latency are benchmarked.
Conducting testing
Knowing how often, what, and where to test is crucial.Type of testing When to perform Frequency Environment Load testing When there are significant changes (updates, new features, or infrastructure changes). Perform periodic tests for ongoing validation. Initial load testing in the development environment. UAT environment testing for validating expected user loads. Stress testing After load testing, usually in later stages or before major releases. Less frequent than load testing but repeat after significant changes. Stress tests in the staging environment to assess extreme conditions. Soak testing Typically after load and stress testing to evaluate extended behavior. Less frequent but periodic, especially for continuous operation. Conduct soak testing in the staging environment over an extended period. Breakpoint testing Essential after significant changes impacting capacity. Done after load and stress testing, not as frequent. Perform in a pre-production environment mirroring production. Scalability testing Conduct when assessing ability to scale with increased load or architecture changes. Can be performed less frequently for future growth planning. Evaluate scalability in an environment replicating production infrastructure
In some cases, system components must be tested in addition to end-to-end application testing. Imagine an e-commerce website with a seller app that updates the product catalog. Both apps access the product inventory database. In such cases, individual database testing is necessary due to its interaction with multiple applications.
Result analysis
Performance testing requires monitoring multiple metrics to understand your application’s behavior under different conditions. Test results should be compared to benchmarks to determine if the application is meeting goals. To diagnose performance issues, you need deeper insights to find the cause. Azure Load Testing’s dashboard displays client-side and server-side metrics to help you find bottlenecks. These metrics should be monitored.
Response time: The system’s response time. Going further, detailed response time breakdowns for components or transactions help identify bottlenecks and optimize critical application paths.
The percentage of testing errors is the error rate. Investigating error types and patterns improves system stability by revealing the application’s error resilience.
Throughput is the number of transactions per unit time. Analyzing throughput patterns under different loads helps plan system capacity.
Concurrency: Number of concurrent users or connections. Finding peak concurrency levels helps optimize resources and infrastructure for different user loads.
Resource utilization: Monitor CPU, memory, disk, and network usage. Examining resource usage patterns helps identify resource-intensive operations, optimize allocation, and prevent exhaustion.
Monitor your application component metrics as well as these metrics, which apply to most applications.
Continuous performance testing
Performance testing is seamlessly integrated into CI/CD pipelines to evaluate application scalability and responsiveness throughout the development lifecycle. This practice helps identify and fix performance issues early in development, reducing the risk of deploying underperforming apps. The early detection of performance bottlenecks allows developers to address issues early in development. This reduces the cost and effort of fixing performance issues later in development.
Key CI/CD pipeline integration considerations include:
Test every build with basic tests to catch regression quickly. Consider weekly builds for more thorough performance tests, depending on development velocity. Perform thorough performance testing before critical releases or major updates to ensure application meets performance criteria.
Server configurations, databases, and network conditions should match production. This identifies production-specific issues.
Analyze performance regressions and deviations using benchmarks. Teams can receive automated alerts for issues.
Stress testing in action
This section covers a stress testing scenario, including critical system components and test result interpretation. They will use Azure Load Testing and Application Insights.
Online retailer Contoso Ltd. is preparing for Black Friday. During this event, a massive number of users try to access the platform, browse products, and buy. The stress test simulates a scenario where user load exceeds peak traffic to see how well the platform handles the extra demand. It uses the Contoso Ltd. e-commerce website and back-end APIs.
Contoso Ltd. tests critical user flows like product search, cart addition, and checkout. They use Azure Load Testing to stress test the system by gradually increasing user load beyond capacity. To determine when performance degrades, observe how the system responds to load.
Application Insights inspects errors to debug. App Insights’ Failures tab shows a 500 error caused by a Cosmos DB gateway timeout during the load test.
When Cosmos DB is under load, Azure Load Testing server-side metrics show normalized Request Units (RU) consumption reaching 100%.
This means Cosmos DB cannot handle the incoming requests, causing the application to fail. Contoso Ltd. can increase Cosmos DB Request Units (RU) or switch to Auto scale.
Understand performance testing
Business strategies require performance testing, not just a checkbox in the software development lifecycle. Thorough planning, proactive testing, and quick bottleneck resolution are essential. Performance testing helps organizations prepare for peak events and unexpected challenges by pointing them toward reliable, high-performance systems that can handle user demands. Performance testing should be part of ongoing development because implementation changes can affect reliability. Start performance testing with Azure Load Testing.
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