Why has Bitbucket's pull request merge time increased by 40% over the past month?

Introduction

The recent 40% increase in Bitbucket's pull request merge time is a critical issue that demands immediate attention. This metric directly impacts developer productivity and project timelines, potentially affecting Bitbucket's core value proposition. I'll approach this problem systematically, starting with clarifying questions, then moving through data analysis, hypothesis generation, and finally proposing actionable solutions.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might have been a recent product update. Has there been any significant change to Bitbucket's codebase or infrastructure in the past month?

Why it matters: Recent changes could directly impact merge times. Expected answer: Yes, there was a major update to our CI/CD pipeline. Impact on approach: If confirmed, we'd focus on investigating the new CI/CD implementation.

• Considering user segments, I'm curious about the distribution of this increase. Is the 40% increase uniform across all users, or are certain groups more affected?

Why it matters: Helps identify if the issue is systemic or specific to certain user types. Expected answer: Enterprise users are experiencing longer delays than individual developers. Impact on approach: We'd prioritize investigating enterprise-specific features or workflows.

• Regarding performance metrics, has there been any change in the volume of pull requests or the average size of code changes in the past month?

Why it matters: Changes in usage patterns could explain increased merge times. Expected answer: Pull request volume has remained stable, but average PR size has increased. Impact on approach: We'd focus on optimizing large PR handling and educating users on PR best practices.

• Thinking about potential data issues, can we confirm that the definition of "merge time" hasn't changed and that our measurement systems are functioning correctly?

Why it matters: Ensures we're addressing a real problem, not a measurement artifact. Expected answer: The definition and measurement systems remain unchanged. Impact on approach: We'd proceed with confidence in the data's accuracy and focus on operational causes.