performability

Performability is a field of study in systems engineering and computer science that examines how performance and dependability interact to determine how well a system meets operational requirements. It combines quantitative aspects of performance—such as throughput, latency, and resource utilization—with dependability measures like availability, reliability, and maintainability to evaluate system behavior under both normal and degraded conditions.

Models used in performability analyses typically couple performance states with fault/repair dynamics. Common approaches include stochastic models such as Markov chains, Markov reward models, semi-Markov processes, and stochastic Petri nets, which capture how failures, repairs, and workload affect performance. Queuing networks that incorporate failure states are also employed. Analytical methods and simulation, including discrete-event simulation, are used to derive metrics and explore design trade-offs.

Key outputs of performability studies are metrics that reflect the joint behavior of performance and dependability. This includes the performability function or index, which maps system states to performance outcomes, as well as availability-weighted performance measures, expected response time conditioned on uptime, and probabilities of performance loss under degraded operation.

Applications span telecommunications, embedded and real-time systems, data centers, cloud services, and critical infrastructures. Performability analysis supports capacity planning, fault-tolerance design, maintenance scheduling, and resource provisioning by clarifying how reliability strategies impact performance and vice versa.

Challenges include the complexity of modeling large systems, state-space explosion, and obtaining accurate failure and repair rates that vary with workload and environment. The approach requires careful selection of metrics to meaningfully couple performance and dependability, and is often used in conjunction with traditional performance evaluation and reliability engineering.