Why has Datto's Continuity service seen a 15% drop in successful backups over the past month?

Introduction

The recent 15% drop in successful backups for Datto's Continuity service over the past month is a critical issue that demands immediate attention. This analysis will systematically identify, validate, and address the root cause while considering both short-term fixes and long-term strategic implications.

I'll approach this problem by first clarifying key details, ruling out external factors, and then diving deep into the product, metrics, and potential internal causes. My goal is to provide a comprehensive analysis that leads to actionable solutions and preventive measures.

Step 1

Clarifying Questions (3 minutes)

• Looking at the timing, I'm thinking there might be a recent change in the backup process. Has there been any recent update to the Continuity service or related systems?

Why it matters: Recent changes often correlate with performance issues. Expected answer: Yes, there was a minor update to the backup algorithm. Impact on approach: If confirmed, I'd focus on the update's impact and potential rollback.

• Considering user segments, I'm curious about the distribution of the issue. Is this 15% drop uniform across all customer types, or is it more pronounced in specific segments?

Why it matters: Helps identify if the issue is systemic or segment-specific. Expected answer: The drop is more significant in enterprise customers. Impact on approach: I'd prioritize investigating enterprise-specific factors and configurations.

• Thinking about the metric itself, I want to ensure we're comparing apples to apples. Has there been any change in how we define or measure "successful backups" in the past month?

Why it matters: Metric definition changes can lead to false alarms. Expected answer: No changes in metric definition. Impact on approach: If confirmed, I'd focus on actual performance issues rather than measurement discrepancies.

• Considering potential external factors, I'm wondering about any significant changes in our customers' data volumes or patterns. Have we seen any unusual spikes in data volume or changes in data types being backed up?

Why it matters: Changes in data characteristics can affect backup success rates. Expected answer: Some increase in unstructured data volume. Impact on approach: I'd investigate how our system handles increased unstructured data and if it's causing failures.