Schedulers and queuing systems are an essential component of all HPC systems. Their overall goal is easily explained: Fairly distribute the jobs on the nodes of a supercomputer according to the policies of the centre while optimizing the usage of the available resources. The implementation can be more complex than expected. Like any other optimization problem, there is no single solution, but different heuristics can be more appropriate depending on the criteria. The optimization is made more complex by the increasing heterogeneity of the resources: Future supercomputers will possibly be composed of a set of CPUs and GPUs with a common interconnect. What will the allocation algorithms look like then? Finally, this is the field in supercomputing where psychological aspects are essential: Do the users perceive the queuing system as fair and predictable? What user behavior is rewarded, what is punished? In a global world of standardized technologies, the algorithms and policies behind schedulers and queuing systems may be the last possible differentiation between competing data centers. Are we really ready to share this knowledge with our colleagues?