Kubernetes environments, particularly in the context of large-scale data ingest across APIs, suffer from unique challenges posed by data gravity. This presentation aims to explore the newer avenues to overcome these challenges such as local storage layer optimizations, integration of edge computing, and/or network efficiencies that can help reduce latency. Participants will be exposed to ways of reducing data transfer costs, increasing data transfer rates and improving data storage characteristics without loss of scalability of the system. Many of the provided examples will relate to the real situations which will help the audience to use those techniques effectively in the real-life complex Kubernetes environments.