I'm trying to integrate some code into an existing ELK stack, and we're limited to using filebeats + logstash. I'd like to have a way to configure a grok filter that will allow different developers to log messages in a pre-defined format such that they can capture custom metrics, and eventually build kibana dashboards.
For example, one team might log the following messages:
metric_some.metric=2
metric_some.metric=5
metric_some.metric=3
And another team might log the following messages from another app:
metric_another.unrelated.value=17.2
metric_another.unrelated.value=14.2
Is there a way to configure a single grok filter that will capture everything after metric_ as a new field, along with the value? Everything I've read here seem to indicate that you need to know the field name ahead of time, but my goal is to be able to start logging new metrics without having to add/modify grok filters.
Note: I realize Metricsbeat is probably a better solution here, but as we're integrating with an existing ELK cluster which we do not control, that's not an option for me.
As your messages seems to be a series of key-value pairs, you can use the kv filter instead of grok.
When using grok you need to name the destination field, with kv the name of the destination field will be the same as the key.
The following configuration should work for your case.
filter { kv { prefix => "metric_" } }
For the event metric_another.unrelated.value=17.2 your output will be something like { "another.unrelated.value": "17.2" }
Related
If I make any configuration changes to Logstash.
Will I see the chnages applied to Elastic Search
For Example
If I change the grok pattern and added new Fields,
Will I be able to see the chnages effected on already indexed logs in elastic search.
If not what should I do?
Should I re-index whole old logs which are already indexed again to see the new fields??
If you add any new field it will get reflected in the Mapping Type and new field would get stored in that index. Every time a document contains new fields, those will end up in the index’s mappings. This isn’t worrying for a small amount of data, but it can become a problem as the mapping grows. But you should be very careful having too many fields in an index can lead to mapping explosion which can cause a lot of memory error.
Any change you make in your Logstash pipeline will only apply to logs ingested after the change, logs already in elasticsearch are not changed.
If you want to add new fields to documents already in elasticsearch you will need to reindex them through logstash.
I am using Logstash-6.3.0 ,Elastic search-6.3.0 and Kibana-6.3.0 combination. I have some fields in kibana which are scripted.
I need to send an alert based on these values. I can send alert for elastic search fields using watcher plugin for kibana.
How do I configure kibana to send alert based on scripted field values?
I am using elastalert,if there are ways?
Solution using elastalert is fine.
I don't think you can query on scripted fields using ElastAlert as scripted field values are computed at the query time (in kibana only) and aren't indexed into the Elasticsearch hence cannot be queried on as ElastAlert only queries Elasticsearch directly.
Better explain.
What i want is a validation xml in DSL, that apply one or other xsd depending on one of the fields of the xml.
At now look like this:
Read from a MongoDB -> Split in the files the JSON have -> trying to validate.
But what i want to pass as a parameter is the same XML, not the "classpath:validation.xsd".
return IntegrationFlows.from(configurationInbound(factory))
.split(Configuration.class,m->m.getFiles().values())
.filter(new XmlValidatingMessageSelector(commonResources.getResource("classpath:validation.xsd"),
SchemaType.XML_SCHEMA))
Is any way to do it?
Your explanation is a bit not clear, but let me guess:
You want to use an XSD resource from the message passing through the flow, not statically configured on the mentioned XmlValidatingMessageSelector.
If it is that, then unfortunately that is how this XmlValidatingMessageSelector is designed.
As a solution I suggest to implement your own DynaicXmlValidatingMessageSelector with some copied logic from the existing XmlValidatingMessageSelector and create an XmlValidator in the accept() method on the fly based on the incoming message.
I'm looking for some guidance on how to setup my logstash/elastic/kibina config to most effectively query my rabbitmq logs.
What I want to do is query and visualise nested properties within my _source object.
For example my _source might look like this:
{
"ApplicationName": "MyApp",
"JsonPayload":
{
"ExceptionType":"System.InvalidOperationException",
"Message":"Some details about the exception"
}
}
I am able to see ApplicationName and JsonPayload listed in my discover fields in kibana, but I am unable to do anything with the nested fields ExceptionType and Message.
I presume I need to flatten out the JsonPayload object for Kibana to work with it, but I'm unsure where to do this:
Can I write a query in Kibana for this?
Do I do something with elastic search to enable this?
Do I need to adjust some mapping in Logstash?
I'm new to the stack so unsure which of the tools is the most appropriate place to do this.
I'm using logstash and kibana 5.5 if this helps.
Trying to access the analyzed/tokenized text in my ElasticSearch documents.
I know you can use the Analyze API to analyze arbitrary text according your analysis modules. So I could copy and paste data from my documents into the Analyze API to see how it was tokenized.
This seems unnecessarily time consuming, though. Is there any way to instruct ElasticSearch to returned the tokenized text in search results? I've looked through the docs and haven't found anything.
This question is a litte old, but maybe I think an additional answer is necessary.
With ElasticSearch 1.0.0 the Term Vector API was added which gives you direct access to the tokens ElasticSearch stores under the hood on per document basis. The API docs are not very clear on this (only mentioned in the example), but in order to use the API you have to first indicate in your mapping definition that you want to store term vectors with the term_vector property on each field.
Have a look at this other answer: elasticsearch - Return the tokens of a field. Unfortunately it requires to reanalyze on the fly the content of your field using the script provided.
It should be possible to write a plugin to expose this feature. The idea would be to add two endpoints to:
allow to read the lucene TermsEnum like the solr TermsComponent does, useful to make auto-suggestions too. Note that it wouldn't be per document, just every term on the index with term frequency and document frequency (potentially expensive with a lot of unique terms)
allow to read the term vectors if enabled, like the solr TermVectorComponent does. This would be per document but requires to store the term vectors (you can configure it in your mapping) and allows also to retrieve positions and offsets if enabled.
You may want to use scripting, however your server should have the scripting enabled.
curl 'http://localhost:9200/your_index/your_type/_search?pretty=true' -d '{
"query" : {
"match_all" : { }
},
"script_fields": {
"terms" : {
"script": "doc[field].values",
"params": {
"field": "field_x.field_y"
}
}
}
}'
The default setting for allowing the script depends on the elastic search version, so please check that out from the official documentation.