By nature, the amount of data collected in your ElasticSearch instance will continue to grow and at some point you will need to prune or warehouse indexes so that your active collections are prioritized. ElasticDump can assist in moving your indexes either to a distinct ElasticSearch instance that is setup specifically for long term data, or exporting … ELK: ElasticDump and Python to create a data warehouse job
The ELK stack (ElasticSearch-Logstash-Kibana), is a horizontally scalable solution with multiple tiers and points of extension and scalability. Because so many companies have adopted the platform and tuned it for their specific use cases, it would be impossible to enumerate all the novel ways in which scalability and availability had been enhanced by load balancers, … ELK: Architectural points of extension and scalability for the ELK stack
The heart of the ELK stack is Elasticsearch. In order to provide high availability and scalability, it needs to be deployed as a cluster with master and data nodes. The Elasticsearch cluster is responsible for both indexing incoming data as well as searches against that indexed data. Resources As described in the documentation, if there … ELK: Scaling an ElasticSearch Cluster
When automating software and infrastructure, it is not uncommon to need to supply a user id and password for installation or other operations. While it is certainly possible to pass these plaintext credentials directly in the state, this is not best practice. # not best practice!!! testdb_user: mysql_user.present: – name: frank – password: “test3rdb” – … SaltStack: Keeping Salt Pillar data encrypted using GPG