The infrastructure of mobile networks in 5G will offer various services in the form of network slices that can be deployed and implemented in a highly customizable manner. A real dynamic network with time-varying network utility has not been considered in previous works. In this paper, we examine the multi-resource allocation problem for network slicing in an online manner where the utility functions change over time. To solve the problems as mentioned above, we present Metis, a first systematic solution. Metis is an online network slice resource allocation framework that combines the time-varying property of the network utility function given the bandwidth and processing capacity constraints with the virtual network functions isolation requirements. As a result, we aim to maximize the cumulative network utility over time. Utilizing state-of-the-art concave optimization methods, we formulate the multi-resource allocation problem. To the best of our knowledge, this is the first work investigating an online method for multi-resources allocation for network slicing in a real-time network. Metis can proveably converge to the optimal solution, and the experiment results show a steady state behavior for Metis which converges in dynamic network settings.