In architecture, we’re building a system to fulfill expectations across a number of system attributes: scalability, reliability, performance, and so on. When possible, the valued attributes are measured based on numbers, and sometimes those expectations are coded into SLAs or SLOs.
Inherent in the problems the system is solving are other attributes like cardinality, dimensionality, capacity, volume, complexity, and throughput. Those attributes impact our ability to deliver to expectations. Sometimes we also measure them.
Michelle Brush explores the numbers, functions, and constants that can be used to measure and influence your architectural decisions. Michelle provides examples of how organizations can determine what attributes they really value in their architectures and shares practical approaches for how to measure those attributes using mostly available data. Along the way, she discusses what a healthy attitude toward architectural measurement and accountability looks like and the guidelines you should set to ensure you’re measuring what matters to your organization.
Michelle Brush is engineering director for Cerner Corporation, where she leads teams that develop the platform for ingesting stream and batch data specific to Cerner’s Population Health solutions. A math geek turned computer geek with 15 years of software development experience, Michelle has developed algorithms and data structures for search, compression, and data mining in both embedded and enterprise systems. She is the chapter leader for the Kansas City chapter of Girl Develop It.
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