I want to create a second elastic cluster for testing and view the data in Kibana.
My end goal is to setup fluentd so i can store the logs in elastic search and view them on kibana. But i think i should do this on a second elastic cluster to see how it works.
The first/initial elastic cluster was setup uising the following:
To what extent, can i (should i) extend the above to have a second elastic cluster.
Is it possible for me to simply create a new kind: Elasticsearch change the name to something more descriptive of a second cluster e.g cluster-2.
Is it possible to point to a new storage for the new cluster-2 ? or should i use the existing storage.
Is it possible to use the same kibana instance to view data across multiple clusters because i can see the kibana definition has an elasticsearchRef which is a reference to a single cluster.
You can create as many Elasticsearch clusters as you like provided that each one has a unique name (metadata.name) and there are enough resources (CPU, memory, and disks) available in your Kubernetes cluster.
When i create a second elasticsearch cluster is there anything else i need to configure or do i just need to change the metadata.name? I am using ECK https://www.elastic.co/guide/en/cloud-on-k8s/current/k8s-deploy-eck.html which i believe does a lot of the heavy lifting. So im wondering if i need to configure something else or will it automatically pick up the second cluster.
Do you have some method i can use to confirm this second cluster is working alongside the first one?
In this particular case, you can simply make a copy of your existing YAML file containing the Elasticsearch definition, change metadata.name, and kubectl apply to get a new Elasticsearch cluster identical to your existing one except for the cluster name.
Just in case it wasn't clear, you are not limited to creating a single type of Elasticsearch (or Kibana or APM server) with ECK. You can create as many as you like with differing configurations. That's the advantage of using an operator.
You can update an existing installation by running the kubectl apply command as described in the documentation. Existing resources (Elasticsearch, Kibana, APM Server) will continue to work (they may go through a rolling restart though). However, I would advise reading the release notes to make sure there are no breaking changes that affect you, testing the upgrade on a non-production cluster first, and taking backups of your data before upgrading production.
Can you point me to some documentation on how i can backup the existing index's. Also something to note I am using aws volumes as StorageClass. Does that make it easier/harder?
Apache, Apache Lucene, Apache Hadoop, Hadoop, HDFS and the yellow elephant
logo are trademarks of the
Apache Software Foundation
in the United States and/or other countries.