  End-to-end (E2E) quality of experience (QoE) for 6G applications depends on
the synchronous allocation of networking and computing resources, also known as
slicing. However, the relationship between the resources and the E2E QoE
outcomes is typically stochastic and non-stationary. Existing works consider
known resource demands for slicing and formulate optimization problems for
slice reconfiguration. In this work, we create and manage slices by learning
the relationship between E2E QoE and resources. We develop a gradient-based
online slice reconfiguration algorithm (OSRA) to reconfigure and manage slices
in resource-constrained scenarios for radio access networks (RAN). We observe
that our methodology meets the QoE requirements with high accuracy compared to
existing approaches. It improves upon the existing approaches by approximately
98\% for bursty traffic variations. Our algorithm has fast convergence and
achieves low E2E delay violations for lower priority slices.
