Out of Memory (OOM) events in Linux can significantly affect programs like Redpanda, which uses the Seastar library to optimize hardware utilization, making it vulnerable to the OOM Killer—a kernel function designed to terminate the largest process with the lowest priority when memory is scarce. To address these issues in a Kubernetes (K8s) environment, the Redpanda team developed a custom operator that automates deployment and optimizes memory allocation by leveraging cgroups, adjusting memory reservations, and isolating processes within containers. By reserving 10% of memory for the operating system and reducing the memory allocated to Redpanda, the team mitigated memory pressure and OOM events, ensuring the stability of long-running clusters and improving resource management for larger deployments. These adjustments allow for better observability and debugging, enhancing the overall experience for Redpanda users in a containerized cloud environment.