What I learnt: Elastic search & Kibana : introduction, installtion & configuration

Jul 18, 2016Download as PPSX, PDF5 likes1,136 views

This document provides an overview of the ELK stack components Elasticsearch, Logstash, and Kibana. It describes what each component is used for at a high level: Elasticsearch is a search and analytics engine, Logstash is used for data collection and normalization, and Kibana is a data visualization platform. It also provides basic instructions for installing and running Elasticsearch and Kibana.

 ELK stands for
› Elastic search
› Logstash
› Kibana
Although a separate project but built to work
exceptionally well together by open source
vendor elastic.
Used by Mozilla, Quora, Wikimedia, foursquare,
Github, Netflix, Stack exchange etc

 A java based distributed hence scalable and
cross-platform open source search service
based on Apache Lucine Search Engine.
 Based on HTTP Rest API
 Schema less JASON doc
 Real time data insight

 Data Normalization tool (Collect, Enrich &
Transport Data)
 Fast track option for time consuming ETL
 Normalize any type of log (system log, web server log, error log,
app log etc) irrespective of data source like Apache or IIS.

 data visualization platform
 stunning, powerful graphics from histograms
to geomaps.

 Node
› Node is s single machine/server stores
searchable data
› Participate in cluster indexing and search
capabilities
Node 1 Node 2 Node 3 Node4 Node 5
CLUSTER 1

 Cluster
› Collection of nodes
› Contains one or more than one nodes
› Node contains all data
 Index
› Collection of documents
› E.g. product, account, movies
› Identified by name (lowercase)
 Used in indexing, updating, deleting, searching docs
within index
› Can have as many as index within cluster

 Type
 A convenient way to store several types of data in same
index.
 multiple types may live in the same index as long as their
fields do not conflict
 It is stored within metadata with fixed name
 _type
 Mapping
› Like scheme for table in RDBMS
› Describes fields
› Include information on how fields should be indexed
* Bit confused ! Do not worry see the next slide , hopefully concept will be
clear

 Document is basic unit of info that can be
indexed , expressed in jason format.
 Can be many documents in an index

 Shard
› When an index contains large amount of data e. 500
GB or 1 TB, then it is divided into multiple pieces
called Shard
› Fully functional and independent index that can be
stored on any node in a cluster.
 Replica
› Copy of a shard
› Take over if shard fails
› By default elastic search adds 5 primary and 1
replica shards.

 only requirement for installing Elastic search is
a recent version of Java
 Install java
› Make sure to configure the run-time environment
› Set JAVA_HOME under
Advance Settings->environment variable
*if it is already added , add the path of java installation
folder, if not add new variable.
See the next slide

What I learnt: Elastic search & Kibana : introduction, installtion & configuration

 Download elastic seach for folloing links
› https://www.elastic.co/downloads/elasticsearch
 Download the zip file, Unzip it into C: for
convenient
 Open command prompt , go to unzipped
folder and run binelasticsearch.bat
 * you might get JAVA_HOME path problem as I faced

 Now go to browser and type
 http://localhost:9200
 Check the output is , if the output is like
below.. CONGRATS.. Its working fine.

 Download Kibana (.zip) from below link
› https://www.elastic.co/downloads/kibana
 Unzip in to C drive
 Now you need to do some configuration
 Go to C:kibana-4.5.2-windowsconfig
 You will find kibana.yml
 Delete the ‘#’ before
‘elasticsearch.url: "http://localhost:9200" ‘

 Now run
 Now go to browser and type
› http://localhost:5601. if you see the below
screen. Cool! Kibana is working perfectly.

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What I learnt: Elastic search & Kibana : introduction, installtion & configuration

1. What I learned …

2.  ELK stands for › Elastic search › Logstash › Kibana Although a separate project but built to work exceptionally well together by open source vendor elastic. Used by Mozilla, Quora, Wikimedia, foursquare, Github, Netflix, Stack exchange etc

3.  A java based distributed hence scalable and cross-platform open source search service based on Apache Lucine Search Engine.  Based on HTTP Rest API  Schema less JASON doc  Real time data insight

4.  Data Normalization tool (Collect, Enrich & Transport Data)  Fast track option for time consuming ETL  Normalize any type of log (system log, web server log, error log, app log etc) irrespective of data source like Apache or IIS.

5.  data visualization platform  stunning, powerful graphics from histograms to geomaps.

6.  Node › Node is s single machine/server stores searchable data › Participate in cluster indexing and search capabilities Node 1 Node 2 Node 3 Node4 Node 5 CLUSTER 1

7.  Cluster › Collection of nodes › Contains one or more than one nodes › Node contains all data  Index › Collection of documents › E.g. product, account, movies › Identified by name (lowercase)  Used in indexing, updating, deleting, searching docs within index › Can have as many as index within cluster

8.  Type  A convenient way to store several types of data in same index.  multiple types may live in the same index as long as their fields do not conflict  It is stored within metadata with fixed name  _type  Mapping › Like scheme for table in RDBMS › Describes fields › Include information on how fields should be indexed * Bit confused ! Do not worry see the next slide , hopefully concept will be clear

9.  Document is basic unit of info that can be indexed , expressed in jason format.  Can be many documents in an index

10.  Shard › When an index contains large amount of data e. 500 GB or 1 TB, then it is divided into multiple pieces called Shard › Fully functional and independent index that can be stored on any node in a cluster.  Replica › Copy of a shard › Take over if shard fails › By default elastic search adds 5 primary and 1 replica shards.

11.  only requirement for installing Elastic search is a recent version of Java  Install java › Make sure to configure the run-time environment › Set JAVA_HOME under Advance Settings->environment variable *if it is already added , add the path of java installation folder, if not add new variable. See the next slide

13.  Download elastic seach for folloing links › https://www.elastic.co/downloads/elasticsearch  Download the zip file, Unzip it into C: for convenient  Open command prompt , go to unzipped folder and run binelasticsearch.bat  * you might get JAVA_HOME path problem as I faced

14.  Now go to browser and type  http://localhost:9200  Check the output is , if the output is like below.. CONGRATS.. Its working fine.

15.  Download Kibana (.zip) from below link › https://www.elastic.co/downloads/kibana  Unzip in to C drive  Now you need to do some configuration  Go to C:kibana-4.5.2-windowsconfig  You will find kibana.yml  Delete the ‘#’ before ‘elasticsearch.url: "http://localhost:9200" ‘

16.  Now run  Now go to browser and type › http://localhost:5601. if you see the below screen. Cool! Kibana is working perfectly.

What I learnt: Elastic search & Kibana : introduction, installtion & configuration

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