However, the VPA can bring unforeseen challenges with stateful applications, garbage-collected languages, and specific Kubernetes workload types like DaemonSets and StatefulSets. Additionally, it has several limitations that impact its ability to accurately balance performance, cost, and resource efficiency in real-work Kubernetes deployments. 

The importance of Kubernetes requests and limits

Kubernetes requires precise configuration to allocate resources such as CPU and memory efficiently. Without explicit guidance on resource usage, the basics of Kubernetes orchestration are broken, leading to poor performance, application crashes, or excessive resource waste.

By properly defining requests and limits, you ensure that your applications always have the resources they need to perform optimally, preventing the Kubernetes scheduler from making uninformed decisions that could impact application stability.

As the complexity of applications increases, so does the difficulty in predicting resource needs. Making better-informed resource allocation decisions requires gathering and evaluating actual usage data during normal and peak conditions.