For a long time now, there are two major contestants for the "logs collection and shipping" throne. Those are Logstash (https://www.elastic.co/products/logstash) and Fluentd (https://www.fluentd.org/). Both are open source, and both are widely accepted and actively maintained. While both have their pros and cons, Fluentd turned up to have an edge with cloud-native distributed systems. It consumes fewer resources and, more importantly, it is not tied to a single destination (Elasticsearch). While Logstash can push logs to many different targets, it is primarily designed to work with Elasticsearch. For that reason, other logging solutions adopted Fluentd.

As of today, no matter which logging product you embrace, the chances are that it will support Fluentd. The culmination of that adoption can be seen by Fluentd's entry into the list of Cloud Native Computing Foundation (https://www.cncf.io/) projects. Even Elasticsearch users are adopting Fluentd over Logstash. What was previously commonly referred to as ELK (Elasticsearch, Logstash, Kibana) stack, is now called EFK (Elasticsearch, Fluentd, Kibana).

We'll follow the trend and adopt Fluentd as the solution for collecting and shipping logs, no matter whether the destination is Papertrail, Elasticsearch, or something else.

We'll install Fluentd soon. But, since Papertrail is our first target, we need to create and set up an account. For now, remember that we need to collect logs from all the nodes of the cluster and, as you already know, Kubernetes' DaemonSet will ensure that a Fluentd Pod will run in each of our servers.