staging and QA will not save your systems

In the now named "traditional" software development workflows, staging environments and QA testing have been treated as essential steps to ensure software quality, right? However, in our current fast-crazy-ia-uncertain environments, these practices often fall short. Let’s explore why this approach is flawed and how a more clear/problem-solving approach addresses these shortcomings.

The Limitations of Staging Environments

A staging environment is intended to replicate production as closely as possible, or at least this is the goal. However, this replication is never perfect, leading to some problems like:

1. Environmental Drift: Staging environments rarely mirror production completely. Differences in configurations, data, and scale mean issues encountered in production might not surface in staging, even having a perfect infra as code you have and having perfect isolated containers configurations.

2. Maintenance Overhead: Keeping a staging environment in sync with production requires constant effort, adding operational complexity.

3. False Security: A successful test in staging does not guarantee that the software will work flawlessly in production. Relying on staging can create a false sense of confidence.

4. Cost: Staging environments consume resources and increase costs without necessarily providing commensurate value.

Why QA Cannot Fully Represent Customer Behavior

QA engineers focus at identifying edge cases, as funny illustrated in the classic meme:

A QA engineer walks into a bar. Orders a beer. Orders 0 beers. Orders a lizard. Orders -1 beers. Orders a alijskjficcckk.

First real customer walks in and asks where the bathroom is. The bar bursts into flames, killing everyone.

This rigorous testing is essential to ensure the system handles unexpected inputs gracefully. However, QA processes often miss real-world scenarios that customers encounter. For instance:

• Unpredictable User Behavior: Customers interact with software in ways that no QA process can fully anticipate. For example, a QA engineer might focus on functional correctness, while a customer might inadvertently trigger a critical bug by navigating an uncommon path.

• Environment Differences: Real customers operate in diverse environments with varying network speeds, devices, and configurations that QA tests might not cover.

In the joke’s conclusion, the real customer asks, “Where’s the bathroom?”—an ordinary scenario—and the entire system fails. This underscores the gap between QA testing and real-world usage.

A Better Validation Flow for Modern Companies

To mitigate these challenges, modern software development practices emphasize a validation flow designed to identify and address issues in production quickly and efficiently:

1. Unit Tests: These form the foundation by validating individual components in isolation, ensuring basic correctness.

2. Integration Tests: These ensure that components work together as expected, catching issues that unit tests might miss.

3. Canary Deployments: Instead of using a staging environment, deploy changes to a small subset of production users. This allows teams to observe real-world behavior with minimal risk.

4. Feature Flags: Feature flags enable teams to release features to specific user groups, providing granular control over the rollout process.

5. Rollout Approach: Gradually increase the user base for new features, monitoring for issues at each step. This minimizes the impact of potential problems.

Advantages of the real problem-solving approach

• Real-World Validation: By testing directly in production, teams gain insight into actual customer behavior.
• Faster Feedback Loops: Canary deployments and feature flags enable rapid iteration, reducing time to resolution for issues.
• Cost Efficiency: Eliminating staging environments reduces operational overhead.
• Improved Customer Experience: A gradual rollout with real-time monitoring ensures issues are addressed before they impact a large user base.

Recommended Libraries and Tools

To implement this approach effectively, consider these tools:

• Unit Testing: JUnit, Mocha, PyTest
• Integration Testing: Cypress, Postman
• Canary Deployments: Argo Rollouts, LaunchDarkly
• Feature Flags: Unleash, Flagsmith
• Monitoring: Datadog, New Relic, Grafana

Conclusion

Staging environments and QA testing have their place but are insufficient to ensure software quality in modern, customer-centric organizations. By leveraging a combination of unit tests, integration tests, canary deployments, feature flags, and gradual rollouts, teams can validate software in real-world conditions, reducing risk and delivering a superior user experience. This approach not only aligns with modern practices but also ensures that systems are truly ready for customer use.