With the exponential growth of virtualization and cloud computing over the last decade, many companies in the telecommunications sector have started their journey towards cloud migration by exchanging a lot of specialized hardware for virtualized solutions. With more and more applications running in a cloud environment, it became essential to run these applications on heterogeneous systems with shared underlying hardware and software resources. However, running these applications in a heterogeneous cloud environment often leads to  unpredictable and non-deterministic performance, as all the applications compete for the shared resources to improve their individual performance. This becomes a problem when the interference from the co-hosted applications starts affecting the performance of the critical applications running on the same server. Ericsson is therefore investigating a solution to dynamically manage the low-level hardware and software resources to get deterministic performance on applications deployed using Kubernetes.  In this thesis, the Intent Driven Orchestration (IDO) model developed by Intel is used as the baseline model. This model was then extended by adding another tool to the setup called Container Runtime Interface-Resource Manager (CRI-RM), which is used to manipulate low-level software and hardware resources managed by a Kubernetes cluster at runtime. The results achieved in this thesis suggest that it is possible to get deterministic performance for an application deployed using Kubernetes, by identifying and isolating the CPU cores in the cluster on which the application is running.