Escapes: When Defects Slip Through the Cracks

?? An escape is any issue or defect discovered by internal or external customers after a release or an update has been promoted to the production environment. From the customer point of view, their Sandbox, Dev, and UAT are all considered production environments.

Escapes can involve:

• Issues with new features.
• Defects in enhancements.
• Regression escapes—where something that previously worked as expected is now broken, the worst type of escape as it erodes customer trust and confidence.

We’ve previously explored What is a Software Regression? and Does Severity Matter for Regression Defects?. Now, let’s focus on how to prevent these defects from reaching production in the first place.

The High Cost of Escapes ??

Every escape, especially regression escapes, damages user experience, increases support burden, and can require emergency fixes —causing ripple effects across teams. Customers expect continuity in their workflows; when an update disrupts existing functionality, even unintentionally, it creates frustration and hesitation in adopting future releases.

“An ounce of prevention is worth a pound of cure.” The best way to minimize escapes is not just fixing them quickly, but ensuring they don’t happen at all.

The Zero-Day Checklist ?

Customers want their existing use cases to work flawlessly before they even consider exploring enhancements or new features. A thorough Zero-Day Checklist ensures that updates enhance the experience instead of disrupting it.

To prevent escapes from slipping through, implementing a Zero-Day Checklist for GA builds focused on all aspects that can impact production use cases for customers immediately after the update, over and above all the release regression testing activities is crucial. This checklist should prioritize various integrations that enable users to authenticate and monitor production use cases, backward compatibility, existing data integrity, response times, and security among other things.

Looking Ahead: Defect Severity & SLA ?

How should teams classify and respond to different severities of defects? In our next discussion, we’ll dive into defect severity definitions and the SLA for fixes for each category.

?? What are your thoughts? Have you seen regression escapes impact a release? How do you ensure your team catches defects before they reach production? Share your experiences in the comments below! ??