Code Monkey home page Code Monkey logo

elasticsearch-paramedic's Introduction

ElasticSearch Paramedic

Paramedic is a simple yet sexy tool to monitor and inspect ElasticSearch clusters.

It displays real-time statistics and information about your nodes and indices, as well as shard allocation within the cluster.

The application is written in JavaScript, using the Ember.js framework for sanity and the Cubism.js library for visuals. While the project is useful, the codebase, with most logic in controllers, lacking proper component separation and test suite, can't be considered mature enough, yet.

For basic overview, see a screenshot below.

ElasticSearch Paramedic Screenshot

Installation

The easiest way to check out the application is to open it in a modern browser: http://karmi.github.com/elasticsearch-paramedic.

If you have ElasticSearch running on http://localhost:9200, you should see the stats for your cluster.

You can also download or clone this repository and open the index.html file in your browser:

git clone git://github.com/karmi/elasticsearch-paramedic.git && cd elasticsearch-paramedic
open index.html

The easiest way to use Paramedic in production is to install it as an ElasticSearch plugin:

plugin -install karmi/elasticsearch-paramedic

If your cluster is publicly accessible (authenticated with firewall rules or HTTP Authentication via proxy), open it in your browser:

open http://localhost:9200/_plugin/paramedic/index.html

Overview

The application displays basic information about your cluster: cluster name, health, number of nodes and shards, etc., using the Cluster Health API.

The “Stats” chart displays key metrics from the Nodes Stats API, updated every second.

The “Nodes” part displays the most important information about the cluster nodes (used disk space and memory, number of nodes, machine load and ElasticSearch CPU consumption, etc.), using the Nodes Info and Nodes Stats APIs.

The “Indices” part displays basic information about the indices: number of primary shards, number of replicas, basic index statistics, using the Cluster State, Indices Status and Indices Stats APIs. Primary shards are displayed in blue, allocated replicas in green, unassigned replicas in yellow, and unassigned (missing) primary shards in red.

To display shard allocation across the nodes, use the “Show Details” button. All information is updated periodically, which allows you to see node and index statistics, shard initialization or relocation, etc. in real time.

Note, that a considerable number of Ajax calls is being performed, and launching the application for large clusters, with large number of nodes and indices/shards, may leave your browser unresponsive, or crash your machine. Try increasing the polling interval and hiding the charts if you experience performance problems.

The application performance has been successfuly tested for clusters with around five nodes and sixty shards.

Similar Applications

You are encouraged to try similar existing tools for ElasticSearch:


Karel Minarik

elasticsearch-paramedic's People

Contributors

karmi avatar lothiraldan avatar vhyza avatar

Watchers

 avatar  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.