OpenStack all-in-one setup on CentOS

OpenStack is an open-source cloud operating system for setting up IAAS (infrastructure as a service). OpenStack provides a flexible solution for both public and private clouds, covering the two important requirements i.e. cloud must be simple to implement and massively scalable. For production a minimal OpenStack setup requires at-least 2 separate machine, one controller and one compute node. To get started with OpenStack, a common practice is to setup an all-in-one deployment i.e. using a single machine.
This guide is about setting-up an all-in-one setup for OpenStack Queens, the latest release.

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Install ELK stack on CentOS 7 to centralize logs analytics

What is the ELK Stack?

ELK is an acronym from the first letter of three open-source products — Elasticsearch, Logstash, and Kibana— from Elastic. The 3 products are used collectively (though can be used separately) mainly for centralizing and visualizing logs from multiple servers (as much as you want).
  • Elasticsearch is basically a distributed,  NoSQL data store, that uses on the Lucene search capabilities.
  • Logstash is a log collection pipeline tool that accepts inputs from various sources (log forwarder), executes different filtering and formatting, and writes the data to Elasticsearch.
  • Kibana is a graphical-user-interface (GUI) for visualization of Elasticsearch data.
The ELK Stack is the most widely used log analytics solution, beating Splunk’s enterprise software, which had long been the market leader. The ELK Stack is downloaded 500,000 times every month, making it the world’s most popular log management platform. In contrast, Splunk — the historical leader in the space — self-reports 10,000 total customers.
This tutorial is a guide to set up ELK stack and Filebeat as log-forwarder to gather syslogs of a remote machine (or as many servers as you want).

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Install Elasticsearch 5 on CentOS 7.x

Elasticsearch is a distributed storage and real-time search engine.
  • Distributed storage – you just need to setup and add Elasticsearch nodes, it’ll keep the data distributed on the cluster nodes. The distributed-ness makes data durable and highly-available too.
  • Real-time search engine – You can get to query the data the moment it’s been written.
Due to the above 2 attributes you have been listening and reading about Elasticsearch, wherever there’s a discussion of real-time data analysis. It’d not be an overstatement to say technologies like Elasticsearch set the foundation for any efficient and reliable search engine.

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