Before revision:  We develop a pure approximation for fair robust fault-tolerant k-center and multi-criteria approximation algorithms for the knapsack and matroid variations .
After revision:  We develop a pure approximation for fair robust fault-tolerant k-center and many others. We give concrete results for load balancing on unrelated parallel machines and clustering problems, including constant-factor approximation algorithms when f belongs with a certain rich family of norms, and O(\log n)-approximations when f is general and satisfies some mild assumptions. We also consider the aforementioned problems in a generalized fairness setting. As a concrete example, the insight is to prevent a scheduling algorithm from assigning too many jobs consistently on any machine in a job-recurring scenario, and causing the machine's controller to fail. Our algorithm needs to stochastically output a feasible solution minimizing the objective function, and satisfy the given marginal fairness constraints .