The documentation explains the importance of setting appropriate resource limits for LogScale pods in Kubernetes deployments, emphasizing the need to reserve CPU and memory capacity for operating system functions. Proper limit configuration in production environments ensures LogScale pods are allocated to worker nodes with sufficient resources, preventing competition with other applications and maintaining operational efficiency.

The limits and resources set on the LogScale pods should be appropriate for the size of the instance leaving 2-4 CPUs and 4GB of memory for the OS in the case of LogScale and Kafka.

When running in a production environment setting limits is important to ensure the LogScale pods run on instances where they will have enough resources to operate efficiently and not compete with other applications on the worker node.