When needing to implement flexible resource allocation in a Kubernetes cluster, which approach is preferred?

Assigning resource requests and limits in deployment specifications is the preferred approach for implementing flexible resource allocation in a Kubernetes cluster. This method provides a way to define the minimum (request) and maximum (limit) resources—such as CPU and memory—that an application can use.

By specifying these values, Kubernetes can effectively manage resources across the cluster. When pods are scheduled, Kubernetes uses the requested resources to make placement decisions, ensuring that pods have the necessary resources to run effectively while preventing them from consuming excessive resources, which can lead to performance degradation or resource starvation for other applications. Additionally, this approach allows for efficient utilization of cluster resources by enabling Kubernetes to make informed decisions about resource allocation based on actual needs.

Using resource quotas for every application, while beneficial for establishing boundaries, doesn't provide the same granularity of control over individual applications' resource needs. Enforcing application specifics through service accounts primarily focuses on security and permissions rather than resource allocation. Creating namespaces without resource constraints could lead to uncontrolled resource consumption and potential conflicts among applications, hampering performance and reliability. Thus, specifying resource requests and limits directly in deployment configurations is the most effective strategy for managing resource allocation.