EKL Architecture Best Practices

Hi All,

Could some one suggest me the best practices for creating a multi clustered ELK environment. Any leads will be helpful.


Why are you looking to create a multi-cluster deployment? What is the use case? What are the requirements?

The more information you provide the better chance of a relevant and useful answer.

Sorry for the confusion. Please read it as multi nodes. Below are the high level requirements.

  1. Able to connect to various Azure components including IAAS, PAAS and should create dashboard in Kibana with details on CPU, Memory, Logs, storage, infra failures etc. The components includes VMs, ADF, SQLDB/DW, HDInsight, WebApps, AAS, Logic App, Key vault, Storage accounts, Runbook jobs etc.
  2. Able to perform analysis based on the matrices captured.
  3. Should connect to multiple meta data sources (hosted in MSSQL, PostGRE etc.) and create kibana dashboards
  4. Kibana will be accessed by ~50 users internally. The ELK platform needs to be installed in Azure.
  5. Create dashboards connecting to third party tools and components.

It sound like a single cluster should be sufficient. I would recommend you follow the documentation and set up a small Elasticsearch cluster to start with. 3 nodes is often a good starting point.

Thanks a lot Christian for the information provided

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