Introduction
The increased error rates in InterSystems's HealthShare Health Connect integration engine deployments this month present a critical issue that demands immediate attention. As we delve into this product root cause analysis, we'll systematically examine potential factors contributing to the problem, generate data-driven hypotheses, and develop a comprehensive resolution plan.
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes could directly impact error rates. Expected answer: Yes, a minor update was released 45 days ago. Impact on approach: If confirmed, we'd focus on changes introduced in that update.
Why it matters: Changes in deployment practices could lead to misconfigurations. Expected answer: No major changes reported by customers. Impact on approach: If confirmed, we'd shift focus to internal factors or the product itself.
Why it matters: Increased data load could strain the system, leading to errors. Expected answer: Some customers have reported increased data volumes. Impact on approach: If confirmed, we'd investigate scalability and performance issues.
Why it matters: Changes in error detection could artificially inflate error rates. Expected answer: No changes to error reporting systems. Impact on approach: If confirmed, we'd focus on actual increases in errors rather than reporting anomalies.
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