In this talk, we take the unifying view of systems interacting over communication networks as distributed computing systems and propose to study them as networked control systems. We first show that a popular algorithm for distributed averaging can generate a collective global complex behavior when the inter-agent communication happens over unreliable links. To mitigate the effects of the unreliable information exchange, we propose a new distributed averaging algorithm based on control ideas resilient to noise and intermittent communication. The algorithm and the control perspective are the basis for the development of new distributed convex optimization systems that we can analyze and design as networked control systems. In particular, we can design distributed controllers to improve the performance of distributed optimization systems. We apply our approach to obtain new distributed least squares solvers and distributed solvers of system of linear equations, which are resilient to communication uncertainties. If time permits, we will present an application of the approach to the distributed solution of the non-convex Optimal Power Flow problem.