DZone
Big Data Zone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
  • Refcardz
  • Trend Reports
  • Webinars
  • Zones
  • |
    • Agile
    • AI
    • Big Data
    • Cloud
    • Database
    • DevOps
    • Integration
    • IoT
    • Java
    • Microservices
    • Open Source
    • Performance
    • Security
    • Web Dev
DZone > Big Data Zone > Hunting the ELK (Stack): Data Monitoring to Visualization

Hunting the ELK (Stack): Data Monitoring to Visualization

Everything you need to master your big data workflow.

Peter Connelly user avatar by
Peter Connelly
·
Nov. 01, 19 · Big Data Zone · Presentation
Like (9)
Save
Tweet
22.01K Views

Join the DZone community and get the full member experience.

Join For Free

elk-in-field

 experts in the field 

made up of elastisearch, "a search and analytics engine," logstash, "a server-side data processing pipeline that "ingests data from multiple sources simultaneously, transforms it, and then sends it to a 'stash'," (according to  elastic's official site  ) and kibana, a robust visualization tool, the elk stack has quickly become one of the premier tools available to developers for data processing, management, and visualization.

whether you're just starting out with any of the three technologies, or you're a seasoned veteran, we've compiled the best that our community has to offer for basic questions about getting started to complex tutorials for real-time data management.

before we begin, we'd like need to thank those who were a part of this article. dzone has and continues to be a community powered by contributors like you who are eager and passionate to share what they know with the rest of the world.

let's get started!

elastisearch

getting started

  • if you're looking to get up and running with elastisearch, look no further than elastisearch setup and configuration by guarev rai mazra, as he walks readers through basic concepts behind the framework, installation, and configuration with java.

  • for further understanding concerning elastisearch, check out  elastisearch 101  by lucas saldana. in the article, readers will go further in-depth on the fundamentals of elastisearch, including indexing and searching, data analysis, and querying. (for a more in-depth look at querying data, see  an introduction to elastisearch  by hassan rahhal.)

  • follow along in  data analytics made easier with elastisearch  , as mitul makadia explains to readers why they should pick the framework for their data analytics needs.

  • get an overview of veronika rovnik's first-hand with elastisearch and the elastic stack in  reporting and analysis with elastisearch  .

elastisearch vs the rest

  • yigal compares  solr and elastisearch in solr vs elastisearch: who's the leading open source search engine?  find out which framework is best for your project's needs.

  •  follow along with vincent royer  , as he explains how elassandra can be a potential replacement for elastisearch when working with kubernetes logs, as the tool can give users the benefits of powerful scaling and low downtime.

spring boot and elastisearch

  • in this  sring boot and elastiesearch tutorial  , mvb, rajeesh bhojwani discuss how to use a spring-data-elastisearch project to connect with the elastisearch engine by using the transport client library in order to perform crud operations.

elasticsearch search api in action

 elasticsearch search api in action 

elastisearch query cheatsheets

  • tim ojo, in  one of our most popular posts to date  , lays out 23 useful elastisearch queries that readers can bookmark for the next time they need to work with elastisearch in a pinch.

  • in this  game-of-thrones-themed tutorial  , sohan ganapathy explains how parent and child relationships function within elastisearch and how to perform joins on data within those relationships.

reporting and analysis with elastisearch

  • follow along with veronika rovnik, as she discusses her experiences working with elasticsearch, the elastic stack, and a few complimentary dev tools for the big data platform in  reporting and analysis with elastisearch  .

  • in this two-part series by ayush jain, the developer covers the frameworks that make up the elk stack (elastisearch, logstash, and kibana) and how they all work together. parts one and two can be found  here  and  here  , respectively.

  • get elastisearch up and running on kubernetes, as itamar syn-hersko  explains the structure of both elastisearch and kibana and then shows readers how to deploy elastisearch on k8s  .

elastisearch clusters

  • in  elastisearch tutorial: creating an elastisearch cluster  , daniel burman walks readers through setting up an elastisearch cluster and offers them some operational tips and best practices to get started.

  • follow along with burak atlas, as he explains  how to configure settings for elasticsearch clusters  in order to improve queries latency.

elastisearch performance

  • follow along with burak atlas, as he explains how to optimize elastisearch

  • learn how to perform bulk inserts with elastisearch's rest high-level client in  sujith menon's most recent article  .

logstash

getting started

  • get started with logstash in  installing logstash  by perennial elk-stack-contributor, gaurav rai mazra, as he explains the tool's basic architecture and how to install it.

  • if you're a java programmer coding microservices and working with the elk stack, this  tutorial by nicolas frankel  is perfect for you. learn how to use grok and logstash's dissect filter to parse spring cloud tracing logs.

logstash alternatives

  • looking for other options for logstash? look no further than radu gheorghe's article,  five alternatives to logstash  , as he breaks down advantages and disadvantages of logstash, as well as its open source competitors.

  • in  filebeat vs logstash — the evolution of a log shipper  by daniel berman, readers can get an in-depth comparison of the two technologies and use cases for when each is optimal.

migrating data

  • in this  article  by leona zhang, learn how to migrate data clusters in elisticsearch with logstash for situations like backing up data during a system upgrade.

  • follow along with shriram untawale, as he shows readers how to  migrate mysql data to elastisearch using lohstash  .

logstash architecture and workflow

 logstash architecture and workflow 

logstash debugging and tips

  • having some trouble with your configuration file? check out this  tutorial  by daniel berman, as he walks readers through issues he's previously faced and how to fix them.

  • in  10 things to consider when parsing with logstash  by bipin patwardhan, the developer walks readers through pain points he's encountered in the past when writing logstash scripts.

  • get some quick and dirty debugging hints for all of your logstash-needs with nicolas frankel's article,  debugging hints for logstash  .

  • see how to handle issues related to the "multiple" feature in logstash with bipin patwardhan's article,  logstash — quirky "multiline." 

monitoring logs

  • learn how to set up filebeat, logstashs, and elastisearch to monitor docker swarm logs to ensure reliable microservice architecture in arun sharma's two-part series on the subject. part one and two can be found  here  and  here  , respectively.

  • in this  article  by radu gheorghe's, see how to replay elastisearch slowlogs with logstash and jmeter.

  • follow along with mvb, comsysto gmbh, as he explains how to  combine logstash and graylog in order to create an enterprise-ready, flexible, scalable controlled log management system  .

creating a plugin

  • logstash for a java developer means jumping into the world of gems, rbenv, jruby, etc. getting started means diving headfirst into the entire ruby ecosystem. see how in  so, you want to make a logstash plugin  by nicolas frankel.

kibana

getting started

  • let's start at the very beginning: installation. follow along with guarav rai mazra, as he explains to readers how to get this powerful visualization tool onto your local machines in  installing kibana  .

create robust visualizations

 create robust visualizations 

visualizing data

  • learn how to begin creating robust and powerful visualizations and dashboards with kibana and elastiseach data in veronika rovnik's article,  kibana and beyond: how to visualize elastisearch data  .

  • in this  article  by asaf yigal, see how to get started with kibana from basic installation to some helpful tips and tricks for data visualization.

  • go in-depth on visualizations with mvb, daniel berman. in  creating custom kibana visualizations  , the author explains how to work with vega-lite in kibana in order to create visualizations that better help tell a story with your data.

kibana queries

  • in his  second appearance  in this collection, daniel berman walks readers through different types of queries in kibana to help you search for a wider variety of data in a more flexible way.

logs

  • in this  article  by rafal kuc, check out basic behind logging data to elastisearch, including log structure in kibana, writing logs to a json file, and sending json-formatted logs to elastisearch.

kibana tips and tricks

  • in  kibana hacks: five tips and tricks  , daniel berman takes a look at some workarounds he's found useful for tackling specific pain points or missing features in kibana, including embedding images, inserting links, and adding log messages to dashboards.

the elk stack: putting it all together

getting started

  • for more on elastisearch use cases, check out  elk stack overview and use cases  by sudip bhandari to see just why this tool has become so popular for data analysis and visualization.

  • want to bring in the elk stack for your aws logging and monitoring needs? check out this  comprehensive guide  by asaf yigal, as he walks readers through step-by-step on how to get started with this powerful set of data analysis tools.

elk stack tutorials

  • see how the elk stack works in real-world application with this  tutorial  by asaf yigal, as he shows readers how to use the open source, log analysis platform with openstack.

  • follow along with developer, ayush jain in his two-part series on working with the elk stack. in  part one  , he explains how elastisearch, logstash, and kibana (plus beats) work together. in  part two  , he dives into elk's overall architecture and workflow.

  • in this two-part series by guarav rai mazra, see how to use elastiseach, logstash, and kibana to  run analytics on application events and logs  , and then check out how to  watch and alert on real-time data  within that application.

  • forget about logstash for this tutorial. in  using telegraf elastisearch input plugin  by sonia gupta, see how to set up an influxdb sandbox with an elastisearch node (populated with data using kibana).

  • in this article by joydip kumar, learn about monitoring and logging and how to collate logs for multiple microservices in  setting up the elk stack with spring boot microservices  .

  •  in kafka logging with the elk stack  by daniel berman, explore a tech combination you might not be used to — using the elk stack to collect and analyze kafka logs.

  • with this last tutorial, mvb, rishav rohit, shows readers how to develop a demo app for click-stream weblog ingestion, search, and visualization with the elk stack.

be a part of the conversation!

think we missed something? want to contribute? let us know in the comments below... or, join the conversation by becoming a member of our community of thousands of developers eager to share their knowledge and passion for programming with others.


further reading

  •  authentication and authorization: mastering security 
  •  code quality: honing your craft  .
Big data Visualization (graphics) Docker (software) Kibana Spring Framework Open source

Opinions expressed by DZone contributors are their own.

Popular on DZone

  • 6 Myths About the Cloud That You Should Stop Believing
  • On Some Aspects of Big Data Processing in Apache Spark, Part 1: Serialization
  • What Are Ephemeral Environments and How to Deploy and Use Them Efficiently
  • Authentication and Authorizing for Webservice/ Rest API Calls

Comments

Big Data Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • MVB Program
  • Become a Contributor
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 600 Park Offices Drive
  • Suite 300
  • Durham, NC 27709
  • support@dzone.com
  • +1 (919) 678-0300

Let's be friends:

DZone.com is powered by 

AnswerHub logo