Mercurial > logstash
view Kibana-external-config-patch @ 32:082f7a76fa48
update to logstash 1.1.13
author | Carl Byington <carl@five-ten-sg.com> |
---|---|
date | Wed, 29 May 2013 11:37:41 -0700 |
parents | 610835fb4209 |
children |
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--- KibanaConfig.rb 2013-05-02 15:22:03.011877891 -0700 +++ KibanaConfig.new.rb 2013-05-02 15:26:57.419447970 -0700 @@ -3,26 +3,14 @@ # Your elastic search server(s). This may be set as an array for round robin # load balancing # Elasticsearch = ["elasticsearch1:9200","elasticsearch2:9200"] - Elasticsearch = "localhost:9200" + Elasticsearch = ENV['KIBANA_ES'] ? ENV['KIBANA_ES'] : "localhost:9200" #Set the Net::HTTP read/open timeouts for the connection to the ES backend ElasticsearchTimeout = 500 - # The port Kibana should listen on - KibanaPort = 5601 - - # The adress ip Kibana should listen on. Comment out or set to - # 0.0.0.0 to listen on all interfaces. - KibanaHost = '127.0.0.1' - - # Below is an example showing how to configure the same variables - # using environment variables, which can be set in an init script - # es_ip = ENV['ES_IP'] ? ENV['ES_IP'] : '127.0.0.1' - # es_port = ENV['ES_PORT'] ? ENV['ES_PORT'] : 9200 - # Elasticsearch = "#{es_ip}:#{es_port}" - # KibanaPort = ENV['KIBANA_PORT'] ? ENV['KIBANA_PORT'] : 5601 - # KibanaHost = ENV['KIBANA_HOST'] ? ENV['KIBANA_HOST'] : 'localhost' - + # The port and adress ip Kibana should listen on. + KibanaPort = ENV['KIBANA_PORT'] ? ENV['KIBANA_PORT'] : 5601 + KibanaHost = ENV['KIBANA_HOST'] ? ENV['KIBANA_HOST'] : 'localhost' # The record type as defined in your logstash configuration. # Seperate multiple types with a comma, no spaces. Leave blank @@ -44,19 +32,19 @@ # Do not use isoUtcDatetime or the "UTC:" prefix described in the above # article, as timezone correction is already performed by the "Timezone" # config variable. - # Time_format = 'isoDateTime' + # Time_format = 'isoDateTime' Time_format = 'mm/dd HH:MM:ss' # Change which fields are shown by default. Must be set as an array # Default_fields = ['@fields.vhost','@fields.response','@fields.request'] Default_fields = ['@message'] - # If set to true, Kibana will use the Highlight feature of Elasticsearch to + # If set to true, Kibana will use the Highlight feature of Elasticsearch to # display highlighted search results - Highlight_results = true + Highlight_results = false - # A field needs to be specified for the highlight feature. By default, - # Elasticsearch doesn't allow highlighting on _all because the field has to + # A field needs to be specified for the highlight feature. By default, + # Elasticsearch doesn't allow highlighting on _all because the field has to # be either stored or part of the _source field. Highlighted_field = "@message" @@ -99,18 +87,18 @@ # indexing Smart_index = true - # You can define your custom pattern here for index names if you - # use something other than daily indexing. Pattern needs to have - # date formatting like '%Y.%m.%d'. Will accept an array of smart - # indexes. - # Smart_index_pattern = ['logstash-web-%Y.%m.%d', 'logstash-mail-%Y.%m.%d'] + # You can define your custom pattern here for index names if you + # use something other than daily indexing. Pattern needs to have + # date formatting like '%Y.%m.%d'. Will accept an array of smart + # indexes. + # Smart_index_pattern = ['logstash-web-%Y.%m.%d', 'logstash-mail-%Y.%m.%d'] # Smart_index_pattern = 'logstash-%Y.%m.%d' # here is an example of how to set the pattern using an environment variable # Smart_index_pattern = ENV['SMART_INDEX'] ? ENV['SMART_INDEX'] : 'logstash-%Y.%m.%d' Smart_index_pattern = 'logstash-%Y.%m.%d' - + # Number of seconds between each index. 86400 = 1 day. - Smart_index_step = 86400 + Smart_index_step = 86400 # ElasticSearch has a default limit on URL size for REST calls, # so Kibana will fall back to _all if a search spans too many @@ -120,7 +108,7 @@ # Elasticsearch has an internal mechanism called "faceting" for performing # analysis that we use for the "Stats" and "Terms" modes. However, on large - # data sets/queries facetting can cause ES to crash if there isn't enough + # data sets/queries facetting can cause ES to crash if there isn't enough # memory available. It is suggested that you limit the number of indices that # Kibana will use for the "Stats" and "Terms" to prevent ES crashes. For very # large data sets and undersized ES clusers, a limit of 1 is not unreasonable.