Design complexity measurement and testing
Communications of the ACM
Mt/G/∞ queues with sinusoidal arrival rates
Management Science
Software Engineering: A Practitioner's Approach
Software Engineering: A Practitioner's Approach
Anchoring the Software Process
IEEE Software
Analytical Network and System Administration: Managing Human-Computer Networks
Analytical Network and System Administration: Managing Human-Computer Networks
Performance by Design: Computer Capacity Planning By Example
Performance by Design: Computer Capacity Planning By Example
The System Administration Maturity Model - SAMM
LISA '93 Proceedings of the 7th USENIX conference on System administration
Theoretical System Administration
LISA '00 Proceedings of the 14th USENIX conference on System administration
(Awarded Best Theory Paper!) A Probabilistic Approach to Estimating Computer System Reliability
LISA '01 Proceedings of the 15th USENIX conference on System administration
Simulation of User-Driven Computer Behaviour
LISA '01 Proceedings of the 15th USENIX conference on System administration
Timing the Application of Security Patches for Optimal Uptime
LISA '02 Proceedings of the 16th USENIX conference on System administration
Dynamic dependencies and performance improvement
LISA'08 Proceedings of the 22nd conference on Large installation system administration conference
Troubleshooting with human-readable automated reasoning
LISA'10 Proceedings of the 24th international conference on Large installation system administration
Quantifying the complexity of IT service management processes
DSOM'06 Proceedings of the 17th IFIP/IEEE international conference on Distributed Systems: operations and management
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The core of system administration is to utilize a set of "best practices" that minimize cost and result in maximum value, but very little is known about the true cost of system administration. In this paper, we define the problem of determining the cost of system administration. For support organizations with fixed budgets, the dominant variant cost is the work and value lost due to time spent waiting for services. We study how to measure and analyze this cost through a variety of methods, including white-box and black-box analysis and discrete event simulation. Simple models of cost provide insight into why some practices cost more than expected, and why transitioning from one kind of practice to another is costly.