Why has the average deployment time for applications built with Mendix's low-code platform increased by 20% in the past two weeks?

Introduction

The recent 20% increase in average deployment time for applications built with Mendix's low-code platform is a critical issue that demands immediate attention. This analysis will systematically investigate the root cause, considering both technical and non-technical factors that could be contributing to this performance decline. We'll follow a structured approach to identify, validate, and address the underlying issues while keeping in mind both short-term fixes and long-term strategic implications.

Step 1

Clarifying Questions (3 minutes)

• Given the sudden increase, I'm wondering about recent platform changes. Have there been any significant updates or new features released in the past month?

Why it matters: Recent changes could directly impact deployment processes. Expected answer: Yes, a major update was released three weeks ago. Impact on approach: If confirmed, we'd focus on the update's components and rollout process.

• Considering user behavior, has there been a shift in the types of applications being deployed recently?

Why it matters: Changes in application complexity could affect deployment times. Expected answer: No significant changes in application types have been observed. Impact on approach: If true, we'd look more closely at platform or infrastructure issues.

• Thinking about infrastructure, have there been any changes to the deployment environment or cloud services used?

Why it matters: Infrastructure changes could directly impact deployment performance. Expected answer: Some minor cloud service updates were implemented recently. Impact on approach: This would lead us to investigate the impact of these updates on deployment processes.

• Regarding measurement accuracy, has the method for calculating average deployment time remained consistent?

Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: Yes, the calculation method has not changed. Impact on approach: If confirmed, we can rule out measurement discrepancies and focus on actual performance issues.