The simulation of turbulent flames fully resolving the smallest flow scales and the thinnest reaction zones goes along with specific requirements, which are discussed from dimensionless numbers useful to introduce the generic context in which direct numerical simulation (DNS) of turbulent flames is performed. Starting from this basis, the evolution of the DNS landscape over the past five years is reviewed. It is found that the flow geometries, the focus of the studies and the overall motivations for performing DNS have broadened, making DNS a standard tool in numerical turbulent combustion. Along these lines, the emerging DNS of laboratory burners for turbulent flame modeling development is discussed and illustrated from DNS imbedded in Large Eddy Simulation (LES) and flow resolved simulation of bluff-body flames. The literature shows that DNS generated databases constitute a fantastic playground for developing and testing a large spectrum of promising machine learning methods for the control and the optimisation of combustion systems, including novel numerical approaches based on the training of neural networks and which can be evaluated in DNS free from sub-model artefacts. The so-called quasi-DNS is also progressively entering the optimisation loop of combustion systems, with the application of techniques to downsize real combustion devices in order to perform fully resolved simulations of their complex geometries. An example of such study leading to the improvement of an incinerator efficiency is reported. Finally, numbers are given relative to the carbon footprint of the generation of DNS databases, motivating the crucial need for community building around database sharing.