i am trying to understand how does the round robin load balancing across elastic search data nodes work if the number of fluentd replicas > 1. Is the load balancing only for the data processed by a specific fluentd pod? Is there a recommended configuration on how to scale out aggregator pods while still able to achieve load balancing across multiple elastic search nodes
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Problem
i am trying to understand how does the round robin load balancing across elastic search data nodes work if the number of fluentd replicas > 1. Is the load balancing only for the data processed by a specific fluentd pod? Is there a recommended configuration on how to scale out aggregator pods while still able to achieve load balancing across multiple elastic search nodes
Steps to replicate
N/A
Expected Behavior or What you need to ask
Using Fluentd and ES plugin versions
Fluentd on k8s Bitnami chart 5.0.15