What is production testing?

Production testing, also known as Testing in Production (TiP), is the practice of running tests on a live production environment using real user data. This approach ensures that your software behaves correctly under actual operating conditions.

When you test in production, you use real-world scenarios and data, unlike synthetic environments. This method captures edge cases and unexpected behaviors that pre-production environments might miss. It provides a high level of accuracy since the tests reflect how actual users interact with your product.

Why is production testing important?

• Accuracy: Real environments provide the most precise results. They cover edge cases that synthetic data often misses. For more insights on the importance of accurate testing in real environments, refer to Client-Side Testing.

• Immediate Feedback: Developers see the software as end-users do. This helps spot issues only real-world conditions reveal. To understand how immediate feedback can enhance the development process, check out Bucket Testing.

• Safety Nets: Feature flags let developers disable problematic features quickly. This minimizes the impact on users. Learn more about the role of feature flags in production testing by exploring Feature Management.

Types of production testing

Canary releases

Canary releases involve rolling out new features to a small user subset first. This approach helps catch issues early. It keeps the wider user base unaffected. To learn more about how canary releases align with continuous delivery pipelines, visit the Statsig Glossary on Canary Testing. Additionally, feature flags are often used in canary testing for gradual rollouts, as explained in the official documentation. For those who want to dive deeper into the concept, check out the Canary Launch page.

A/B testing

A/B testing compares two feature versions in real-world conditions. This method identifies which version performs better. It optimizes user experience using actual data. For a detailed guide on getting started with A/B testing, refer to the Walkthrough Guides. You can also explore the A/B Testing Calculator to help you set up your experiments. If you're interested in learning more about different types of A/B testing, such as A/B/n testing, check out the Statsig Glossary on A/B/n Testing.

Benefits of production testing

• Real-world data: Testing with actual user interactions captures true performance metrics. Synthetic data can't match the complexity of real user behavior. This ensures your software meets real-world demands. Learn more about server-side testing, client-side testing, and bucket testing.

• Reduced risk: Feature flags allow quick issue isolation. You can disable problematic features instantly. This keeps the user experience smooth. Discover how canary testing and sequential testing can further lower risks.

• Cost efficiency: Production testing cuts down on the need for expensive staging environments. This reduces overhead costs significantly. You save money while still ensuring quality. Check out the build vs buy comparison and explore A/A testing to understand cost-saving strategies better.

Incorporating production testing into your workflow offers these clear advantages. It provides accurate data, lowers risks, and saves costs. This makes it an essential practice for modern software development.

Examples of production testing

• E-commerce platform: An online store tests a new checkout process with 5% of users. Feedback and issues are addressed before full deployment.

• Streaming service: A video streaming company introduces a new recommendation algorithm to a small user segment. Engagement metrics validate improvements prior to broader implementation.

• Banking app: A financial institution rolls out a new mobile feature to a limited group. Performance and security are closely monitored to ensure reliability and compliance.