This add-on consists of a combination of Elasticsearch, Fluentd and Kibana. Elasticsearch is a search engine that is responsible for storing our logs and allowing for them to be queried. Fluentd sends log messages from Kubernetes to Elasticsearch, whereas Kibana is a graphical interface for viewing and querying the logs stored in Elasticsearch.
Elasticsearch is deployed as a StatefulSet, which is like a Deployment, but allows for maintaining state on storage volumes.
Elasticsearch has capabilities to enable authorization using the X-Pack plugin. For the sake of simplicity this example uses the fully open source prebuild images from elastic that do not contain the X-Pack plugin. If you need these features, please consider building the images from either the "basic" or "platinum" version. After enabling these features, follow official documentation to set up credentials in Elasticsearch and Kibana. Don't forget to propagate those credentials also to Fluentd in its configuration, using for example environment variables. You can utilize ConfigMaps and Secrets to store credentials in the Kubernetes apiserver.
The Elasticsearch StatefulSet manifest specifies that there shall be an
init container executing before Elasticsearch containers
themselves, in order to ensure that the kernel state variable
vm.max_map_count is at least 262144, since this is a requirement of
Elasticsearch. You may remove the init container if you know that your host
OS meets this requirement.
The Elasticsearch StatefulSet will use the EmptyDir volume to store data. EmptyDir is erased when the pod terminates, here it is used only for testing purposes. Important: please change the storage to persistent volume claim before actually using this StatefulSet in your setup!
Fluentd is deployed as a DaemonSet which spawns a pod on each node that reads logs, generated by kubelet, container runtime and containers and sends them to Elasticsearch.
Learn more in the official Kubernetes documentation.
Both images are now being hosted in quay.io and are built locally via
To build locally run
make build and then
make push to publish.
Since Fluentd talks to the Elasticsearch service inside the cluster, instances on masters won't work, because masters have no kube-proxy. Don't mark masters with the label mentioned in the previous paragraph or add a taint on them to avoid Fluentd pods scheduling there.
Running EFK stack in production
The configurations provided here for Elasticsearch, Fluentd & Kibana (EFK), are a starting point and should not be considered to be production ready.
If you like to run these tools in a production environment you could use the Helm charts, provided by the Helm community, which are used by a lot of people and therefore are widely tested. You can find them all via the Helm Hub.
The source of the mentioned charts can be found here: