GithubHelp home page GithubHelp logo

airob / monitoring-elasticsearch Goto Github PK

View Code? Open in Web Editor NEW

This project forked from packtpublishing/monitoring-elasticsearch

0.0 2.0 0.0 95 KB

Code repository for Monitoring Elasticsearch, published by Packt

License: MIT License

Shell 100.00%

monitoring-elasticsearch's Introduction

Monitoring Elasticsearch

Monitoring Elasticsearch by Packt Publishing

##Instructions and Navigation This is the code repository for Monitoring Elasticsearch, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish. The code files are organized according to the chapters in the book.

To follow along with the examples in the book, you'll need a real or virtualized three-node Elasticsearch cluster. You may optionally want two other nodes to run Marvel and Nagios, covered in Chapter 4, Marvel Dashboard and Chapter 5, System Monitoring respectively. It is possible to run Marvel and Nagios on the same host as a node in your Elasticsearch cluster, but you shouldn't do this in a production cluster. Check out VMWare Player (https://www.vmware.com/products/player) and VirtualBox (https://www.virtualbox.org/wiki/Downloads) for standing up your own virtual five-node environment or Amazon EC2 (https://aws.amazon.com/ec2/) for building a cluster in the cloud. For your Elasticsearch nodes, you'll need a 64-bit version of Windows, Mac OS X, or Linux and a recent distribution of the Java Runtime Environment. The CPU speed doesn't matter as much on these hosts, but we recommend that you have at least 512 MB of memory per node. We use Ubuntu 14.04 and Oracle Java 7 for all examples in this book, but any modern operating system and either OpenJDK or Oracle Java 7 and 8 will work for running through the examples. The only exception is Nagios, which needs to run on Linux. You will need the following software packages: • Java 7 or Java 8 (http://www.oracle.com/technetwork/java/javase/downloads/index.html) • Elasticsearch 2.3.2 (https://www.elastic.co/downloads/past-releases/elasticsearch-2-3-2) • Elasticsearch-head (https://github.com/mobz/elasticsearch-head) • Bigdesk (http://bigdesk.org/) • Marvel—free for development, subscription fee for use in production (https://www.elastic.co/downloads/marvel) • Kibana (https://www.elastic.co/downloads/kibana) • Kopf (https://github.com/lmenezes/elasticsearch-kopf) •Nagios (https://www.nagios.org/downloads/) All of these software packages are free and open source except for Marvel, which is only free for use in development. Finally, several examples in this book use the curl (https://curl.haxx.se/) command-line utility for making REST calls to Elasticsearch and, optionally, Python 2.7 for pretty-printing the results.

##Description Monitoring Elasticsearch book covers how to use several popular open source and commercial Elasticsearch monitoring tools, namely, Elasticsearch-head, Bigdesk, Marvel, Kopf, and Kibana. Elasticsearch cat API and how to use Nagios to perform general system monitoring is covered as well. Moreover, it discusses several case studies with real-world examples of troubleshooting Elasticsearch issues using these tools.

##Related Python/Machine Learning Products:

monitoring-elasticsearch's People

Contributors

dwnoble avatar hussaink72 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.