This chapter starts with the development of a resilience index covering prevention, vulnerability, and prevention. A graphical presentation shows that it covers high-impact rare events (HIRE) as well as low impact high probability cases. The index is then compared to those in engineering, geography, and economics. Reducing shock probabilities and vulnerability and speeding up recovery is costly. Maximization of the index under a resilience-budget constraint shows how expenditures should be well balanced over the three aspects. Numerical and historical examples are constructed and discussed to illustrate the principles. Interactions of systems like digitalization and electricity are considered more broadly for eleven interacting systems. Incentives and policies regarding investment in resilience are described also regarding the international dimension. We provide a simple empirical vector-error correction model for German data in electricity, consumption, GDP per capita and oil prices, which is stable in growth rates. Shock analysis through impulse-response functions show cases of no return to baseline after negative shocks, and long-run overshooting for all variables after a negative shock to GDP per capita, supporting the possibility of the idea of coming out stronger out of a crisis, called super resilience. Policy suggestions from the literature are collected in a separate section.