In this talk I will present recent results and open questions in the context of scheduling real-time jobs with hard deadlines on m parallel machines. Each job has a processing time and a deadline, and the objective is to schedule jobs so that they complete before their deadline. It is known that even when the instance is feasible it may not be possible to meet all deadlines when jobs arrive online over time. Therefore, we consider settings in which the online algorithm has additional resources, such as higher speed or more machines, than the optimal offline algorithm that knows all jobs in advance.