What is Testing in Production?

Testlio

October 18th, 2024

In fact, 60% of organizations now use some form of production testing. This method is crucial because it uncovers issues that may not appear in controlled environments. 

It helps teams catch bugs, improve performance, and enhance the user experience. In this article, we’ll dive into the key concepts of testing in production, including feature flags, monitoring, and incremental rollouts. 

Why Is It Important?

Testing in production is essential because it helps catch issues that are hard to detect in controlled environments. 

For instance, Netflix uses this method to identify rare playback errors that only occur with specific user interactions. 

Similarly, Facebook monitors new feature rollouts in real-time. If they see a sudden drop in user engagement, they can quickly roll back changes to maintain a smooth experience​.

DORA metrics highlight the importance of this approach. High-performing teams that test in production recover from incidents within an hour. In contrast, low-performing teams can take over six months to resolve similar issues​. 

This proactive testing enables rapid deployments, reduces downtime, and improves user satisfaction. Companies using these strategies deliver value more efficiently and maintain a competitive edge​.

Key Concepts of Testing in Production

Here are the key concepts of testing in production:

Feature Flags

Feature flags allow developers to control which features are active in real-time. Companies like Facebook use them extensively. 

They manage features through a system called Gatekeeper, which enables or disables features based on user segments. 

This flexibility helps Facebook quickly switch off problematic features without affecting the entire system​. 

Google also relies on feature flags to conduct A/B testing and roll out updates incrementally. This approach minimizes risk and accelerates the feedback loop, enabling rapid iterations​.

Monitoring and Observability

Monitoring and observability tools, such as Datadog and New Relic, are crucial in tracking system health and user behavior in production. 

These tools provide real-time insights, helping teams detect and address issues quickly. For example, monitoring alerts the team immediately if a new feature causes performance degradation. They can then investigate and resolve the issue before it impacts a broader user base​. 

Observability offers deep visibility into application performance, making debugging and optimization easier.

Incremental Rollouts

Incremental rollouts involve gradually releasing new features to a small user group before a full launch. This strategy reduces risk by limiting the potential impact of bugs. 

Companies like Netflix and Spotify use this method effectively. They start by releasing features to just 1% of users. If no major issues arise, they expand the rollout. 

This controlled approach ensures stability and gathers valuable feedback from real users before a broader release.

Benefits of Testing in Production

Testing in production offers several benefits that enhance software quality and user satisfaction. 

One major advantage is the early detection of issues that might not appear in controlled environments. 

For example, Facebook uses feature flags to deploy new features to a small group of users. If any issues arise, the feature can be quickly disabled without impacting the entire user base. This approach helps maintain stability while gathering valuable feedback.

Additionally, testing in production provides real-world insights into user behavior. It helps teams understand how features perform under actual conditions, leading to better data-driven decisions. 

This approach ultimately reduces deployment risks, speeds up problem resolution, and results in a more reliable product for users.

Drawbacks of Testing in Production

Testing in production has several drawbacks that can cause significant challenges. 

One major issue is the risk of affecting real users. Bugs or failures that go unnoticed during testing can lead to poor user experiences. 

For instance, a flawed feature rollout might cause site crashes or data loss. This can harm the company’s reputation and erode user trust.

Another challenge is the need for constant monitoring and quick response capabilities, which can be expensive to implement despite being worth it. Without these, identifying and fixing problems promptly becomes difficult. 

This can result in prolonged downtime or degraded performance. Moreover, testing in production demands meticulous planning. 

Teams must be ready for immediate rollbacks or hotfixes, which adds operational complexity.

Additionally, there’s the risk of exposing sensitive data. If new features involve changes to data processing, testing them in production can raise privacy and legal concerns. 

Therefore, while testing in production provides valuable insights, it requires careful execution and effective risk management to avoid these potential pitfalls.

Best Practices for Testing in Production

Testing in production requires careful execution to ensure safety and effectiveness. 

• Start by setting clear objectives. These could include performance monitoring, user feedback, or testing specific scenarios. 
• Use feature flags to control new features. This allows you to turn features on or off quickly without redeploying code, reducing the risk of widespread issues.
• Next, implement incremental rollouts. First, deploy new features to a small group of users based on data from user profiles and preferences. If everything works well, expand the rollout gradually. This approach helps catch issues early and limits the impact on users.
• Use robust monitoring and observability tools. These tools allow you to track performance and detect problems in real time.
• Always have a rollback plan ready. This ensures you can quickly revert changes if something goes wrong.
• Finally, involve users in the testing process. Gather feedback and use it to improve the final product.

How To Perform Production Testing?

1. Establish Clear Objectives

Start by setting clear objectives for your production testing. Identify what you want to achieve, such as validating a new feature, monitoring performance, or collecting user feedback. 

These goals will guide your testing strategy. For example, if your aim is to test a feature’s usability, focus on user interactions and feedback. 

If you want to assess system performance, concentrate on metrics like response times and error rates. Clear objectives help keep the testing process focused and aligned with business needs.

2. Implement Feature Flags

Feature flags are crucial for safe production testing. They allow you to enable or disable features for specific user groups without deploying new code. This minimizes risk and provides flexibility. 

3. Choose the Right Testing Techniques

Select the appropriate testing techniques based on your objectives. Techniques like canary releases and A/B testing using tools like LaunchDarkly, Split.io, and Optimizely Full Stack are effective for production environments. 

Canary releases involve rolling out a new feature to a small subset of users first. This helps identify any issues before a full launch. 

A/B testing compares two versions of a feature, which can be both new versions or one old and one new, to determine which performs better. Choosing the right technique ensures that you gather the data you need while minimizing potential disruptions.

4. Ensure Robust Monitoring and Observability

Implement robust monitoring and observability tools to track system health and performance in real-time. 

Use tools like Datadog, New Relic, or Prometheus to monitor metrics such as response times, error rates, and server load. 

Observability goes beyond traditional monitoring by providing deeper insights into system behavior. It includes distributed tracing, log aggregation, and detailed performance metrics. 

With these tools, you can detect and address issues quickly, minimizing downtime and user impact.

5. Prepare for Rollback

Always be prepared for a quick rollback in case something goes wrong. Develop a rollback plan for each new feature or update. 

This plan should include steps to revert changes and restore the previous stable state. Use version control systems like Git to manage code changes effectively. 

Automate the rollback process as much as possible to reduce time and effort. Being prepared for rollback ensures you can quickly mitigate any negative impacts on users.

6. Engage Users in Testing

Involve users in the testing process to gather valuable feedback. Use techniques like beta testing or soft launches to expose the new feature to a select group of users. 

Encourage them to report bugs and share their experience with the new features. This direct user feedback can reveal issues that internal testing may miss. 

Platforms like Testlio or UserTesting can facilitate structured user testing. Engaging users not only improves the quality of your product but also builds trust and loyalty.

7. Analyze Data and Gather Feedback

After deploying a new feature, analyze the data collected during testing. Look for patterns in user behavior, performance metrics, and error logs. 

Use tools like Google Analytics and Mixpanel to track user interactions and identify pain points. Combine quantitative data with qualitative feedback from users. 

This will give you a comprehensive understanding of how the feature is performing. This analysis will inform future iterations and help refine the feature.

8. Iterate Based on Findings

Use the insights gathered from data analysis and user feedback to iterate on the feature. Make necessary adjustments and improvements before rolling out the feature to a broader audience. 

This iterative approach is at the core of agile development. It helps create more resilient and user-friendly products. 

Continuous iteration based on real-world feedback ensures that the feature meets user expectations and performs reliably.

9. Document and Share Learnings

Document all findings, including what worked well and what didn’t, during production testing. Share this documentation with your team to ensure that everyone learns from the experience. 

This practice helps build a knowledge base that can be referenced for future projects. It also fosters a culture of continuous learning and improvement. 

Proper documentation and knowledge sharing enable teams to avoid repeating mistakes and improve their processes over time.

10. Maintain a Culture of Collaboration

Successful production testing requires collaboration between development, operations, and business teams. 

Encourage open communication and teamwork to quickly address any issues that arise. Use collaboration tools like Slack or Microsoft Teams to facilitate real-time discussions. 

A collaborative culture ensures that everyone is aligned and can work together to achieve the best results. 

Collaboration also helps in faster decision-making and problem-solving, making the production testing process more efficient.

11. Regularly Review and Adjust Your Approach

Regularly review your production testing strategy to identify areas for improvement. Evaluate what worked well and what needs adjustment. 

Make changes based on these insights to enhance your testing process. Continuous improvement is key to maintaining an effective production testing strategy. 

Regular reviews help you stay adaptable and prepared for future challenges. Adjusting your approach based on past experiences ensures that you are always optimizing for better performance and user experience.

Tools to Help You With Testing in Production

Several tools can help you with testing in production. Feature flagging tools like LaunchDarkly and Split.io enable you to turn features on or off for specific users. 

This flexibility lets you test new features without impacting the entire user base. For real-time monitoring, use tools like Datadog and New Relic. 

They provide detailed insights into system performance and user behavior, helping you catch issues early.

For deeper visibility, observability platforms like Grafana and Elastic offer distributed tracing and log aggregation. 

This allows you to trace errors and understand their root causes quickly. If you need automated testing, consider Selenium or Cypress. 

These tools simulate user interactions and test features directly in the production environment.

Lastly, use deployment tools like Jenkins or GitLab CI/CD for quick rollbacks in case of issues. This ensures you can revert changes and minimize user disruption efficiently. 

Combining these tools enhances the safety and effectiveness of your production testing.

Outsourcing Testing in Production through Testlio

Outsourcing testing in production through Testlio helps improve software quality and supports global expansion. 

With extensive testing coverage across 600,000+ devices, 150+ countries, 100+ languages, and 800+ payment methods, our comprehensive and customizable services ensure that your product is tested under diverse conditions. 

Talk to a member of our team to learn how we help ensure seamless user experiences by providing the speed, flexibility, and expertise required for high-quality digital products.