ARender rendition performances with ELK stack

Study and Analysis of ARender performances in ELK stack is now possible!

The ARender Rendition Server  returns information on its usage, like the loading time of a document and the opened document type. This information is stored in a log file. It is possible to analyse these logs with the ELK stack.

ELK stack is composed of three applications: Elasticsearch, Logstash and Kibana.

  • Elasticsearch stores and indexes data. It is a NoSQL base allowing to manage big data.
  • Logstash collects the log file, filters and sends data in Elasticsearch.
  • Kibana is a Web interface allowing to search and visualize graphically data.

ELK-stack_imagelarge

In Kibana, a dashboard is obtained with graphical information on the rendition performances.

On the below image, the first number is the average loading time to open a document. The others are the minimum and maximum loading time to open a document. The pie chart to the right displays the number of good (green) and bad (red) responses of the rendition. The other pie chart returns the number of opened documents by document type. Finally, the line chart represents the average loading time by document type.

Kibana-dashboard-1_imagelarge

On the below image, the two first charts analyse the different exceptions met by the rendition. The line chart displays the average loading time in terms of these exceptions. Finally, the last bar vertical chart presents the average loading time by Java methods.

Kibana-dashboard-2_imagelarge

Finally, on the last image, the line chart displays the average loading time by day. The first vertical bar chart is the number of loaded documents by month. And the last, presents the average loading time by month in terms of document type.

Kibana-dashboard-3_imagelarge

Installation/configuration instructions

Prerequisites

To install the ELK stack, it is necessary to have at least Java 7 installed. To check the Java version, open a shell prompt and enter java -version. If the version of Java is less than 7, install a new version.

Verify that the JAVA_HOME environment variable is available in the environment variables:

  • On Linux : echo $ JAVA_HOME
  • On Windows : Control Panel \ System and Security \ System, click Advanced System Settings and Environment Variables

If JAVA_HOME is not available add it:

  • On Linux: export JAVA_HOME = { path to java }
  • On Windows : New System Variable
    • Variable name : JAVA_HOME
    • Variable value : { path to java }

Elasticsearch

Installation on Linux (Centos or Redhat)

Open a shell prompt and enter the following commands:

Installation on Windows

Download the zip file on: https://www.elastic.co/downloads/Elasticsearch.

Unzip the folder to the chosen folder, for example C:\Users\{name}\.

Open Elasticsearch.yml file located in .\elasticsearch-{Version}\config\ with a text editor like Notepad++. Modify the following lines:

  • cluster.name: arender-cluster
  • Network.host: [address IP of virtual machine] if Elasticsearch is installed on a virtual machine

Save the modifications.

To install Elasticsearch as service, open a shell prompt and enter:

  • cd C:\Users\{nom}\Elasticsearch-{Version}\bin
  • service.bat install

installES_large

Elasticsearch is now installed as service. To start it, open the services application of Windows. Select Elasticsearch service and click on start.

Plugin head-Elasticsearch

The plugin head is an interface for Elasticsearch. To install on Linux, open a shell prompt and enter sudo Elasticsearch-{Version}/bin/plugin install mobz/Elasticsearch-head.

For Windows, the plugin is available in zip file on: https://github.com/mobz/Elasticsearch-head.

Unzip the folder in ./Elasticsearch-{Version}/plugins. And rename the folder by “head”.

Restart Elasticsearch. The plugin head-Elasticsearch is available at this URL:  {host}:9200/_plugin/head.

Elasticsearch template

It is possible to add templates in Elasticsearch. In the following template, fields of string type not analysed finishing by .raw are created from fields of string type analysed. The fields of string type can be used without its cut after a space.

Add a template from “Any Request” tab of head-Elasticsearch plugin.

http://{host}:9200/

_template/{name_of_template}  PUT

 

{

"template":"*",

"settings":{

"index.number_of_shards":5

},

"mappings":{

"_default_":{

"_all":{"enabled":true},

"dynamic_templates":[{

"string_fields":{

"match":"*",

"match_mapping_type":"string",

"mapping":{

"type":"string",

"index":"analyzed",

"omit_norms":true,

"fields":{

"raw":{

"type":"string",

"index":"not_analyzed",

"ignore_above":256
}

}

}

}

}]

}

}

}

Template-Elastisearch_imagelarge

Logstash

Installation on Linux

Open a shell prompt and enter:

Installation on Windows

Download the zip file on: https://www.elastic.co/downloads/logstash.

Unzip the folder to the chosen folder, for example C:\Users\{name}\.

Logstash configuration file

Create a file of configuration myfile.conf, with a text editor like Notepad++, in the folder: ./logstash-{Version}/bin.

This file is composed in three parts:

  • An “input” part to define the enter points. For example, the paths to read the log file.
  • A “filter” part where Logstash read the log file line by line and apply a filter to extract data.
  • A “output” part to define the exit points. Here, it is Elasticsearch.

myfile.conf

input {

file {

path => “{Path to the log file}

type => “syslog”

start_position => “beginning”

}

}

filter {

# Grok cut the field « message » into several fields

# Attention, for the inferior versions at 3.0.6 the specific spaces

# are not the same,

# chose SEPARATORSPE for Linux

# and SEPARATORESP for Windows

# For the versions equals or superior at the 3.0.6 version

# chose SEPARATOR and add a space after right brace

grok{

match => {

# "message" => "…" must be on only one line

"message" => "%{NAME}%{TIMESTAMP_ISO8601:dateStart} %{SEPARATOR} %{NAMEEND}%{TIMESTAMP_ISO8601:dateEnd} %{SEPARATOR} %{NAME}%{BASE10NUM:time}%{USERNAME:unite} %{SEPARATOR} %{NAME}%{METHOD:method} %{SEPARATOR} %{NAME}%{MIMETYPE:mimeType} %{SEPARATORSPE}%{NAME}%{DOCID:documentId} %{SEPARATORSPE}%{NAME}%{USERNAME:result} %{SEPARATOR} %{NAME}%{EXCEPTION:exception} %{SEPARATORSPE}%{NAME}%{GREEDYDATA:args}"}

# patterns_dir give the path of file, pattern.conf

# This file regroup regex of each new field

patterns_dir => ["{path to the file pattern.conf}"]

}

# date change the type of a field in date

date {

locale => "fr"

match => ["dateStart", "YYYY-MM-dd HH:mm:ss,SSS"]

target => "@timestamp"

}

# mutate convert the type of a field

mutate {

convert => { "time" => "integer" }

}

}

output {

elasticsearch {

hosts => ["{host}:9200"]

action => "index"

# The index name must not have uppercase

index => "rendition-perfs"

}

stdout { codec => rubydebug }

}

 

pattern.conf

NAME [a-zA-Z]*=

NAMEEND [a-zA-Z]*\s=

SEPARATOR \|\|

METHOD [a-zA-Z][^\|]*

MIMETYPE [a-zA-Z][^\|]*

DOCID [a-zA-Z][^\|]*

EXCEPTION .*[^|]

# Version of specific separator for Windows

SEPARATORESP \|\|

# Version of specific separator for Linux

SEPARATORSPEC \|\|Â\\xA0

NAMEREQUEST [a-zA-Z\/?=]*

LOADINGTIME [0-9]*

SEPARATORAND &

NAMEVERSION [a-zA-Z=]*

VERSION [0-9a-zA-Z.-]*

 

To launch Logstash, open a shell prompt and enter: ./logstash-{Version}/bin/logstash –f myfile.conf

Kibana

Installation on Linux

Open a shell prompt and enter:

To launch Kibana: nohup /opt/ELK/kibana-{Version}-linux-x64/bin/kibana &

Installation on Windows

Download zip file on https://www.elastic.co/downloads/kibana.

Unzip the folder, for example in C:\Users\{name}\

In the folder  .\Kibana\config\kibana.yml, configure the address of Elasticsearch.

To launch Kibana, click on kibana.bat.

Add an index

To add an index in Kibana, open the URL {host} :5601. In Settings > Indices tab, shoot “index contains time-based events”. Enter the name of the Elasticsearch index and click on “Create”.

Add-Kibana-index_imagelarge

Add dashboard

In Settings  > Objects tab click on “Import”. Click on the visualizations file (visualisations_rendition.json) and restart with the dashboard file (rendition.json).

Import-visualizations-and-dashbaord_imagelarge

In the “Dashboard”  tab, click on “Load Saved Dashboard” and click on the dashboard name.

Open-dashboard_imagelarge

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