I've got two indexes one with customer data and the other with netflow.
I want to match the data while entering to the netflow index and match it with other index, if there is a match I want to mutate the data and add the customer id.
I tried using logstash but nothing works ok :|
any ideas?
Thanks in advice
Logstash looks to be the best strategy.
You can use a logstash input to read your netflow index (or use logstash to ingest your netflow directly)
Then in an elasticsearch filter you will query your customer index, find the good customer document, and add the data on your netflow event.
In an elasticsearch output, you update (or ingest) your enhanced netflow document.
I use this strategy for data fixes and data enhancement, when a enrich processor is not the good strategy.
Related
I am new to the ELK and i am in the progress of learning it. In my project, they are importing the data from Amazon S3 -> File Beat -> logstash -> Elastic search -> Kibanna.
In the logstash file, they have directly importing the data and sending to the Elastic search something like below and there was no indexes mentioned in the config file,
output elasticsearch
{
hosts => ["http://localhost:9200"]
}
In Amazon s3, we have logs from Salesforce and in future we are going to implement from multiple sources.
In Elastic search, i could see 41 indexes(Used Get Curl script) is present. Assume if we keep the same setup in logstash, then all logs(Multiple sources) will be sent to elastic search in same manner. I would like to know how the data is getting mapped to the particular index in elastic search ??
In many tutorials, they have given indexes in the logstash config file so in kibanna we could see the index name along with timestamp. I have tried to check by placing a sample Mulesoft log file in Amazon S3 but i cant able to find those data in Kibanna. So shall i need to create one more new index with a name Mule along with mappings??
There is no ELK expert in my project so please guide me on how to approach this one or any references will be more helpful.
This page (https://www.elastic.co/guide/en/logstash/current/plugins-outputs-elasticsearch.html) documents Logstash's Elasticsearch output plugin.
As you can see in the Configuration Options section, the option index is not mandatory. If this option is not specified, its default-value is logstash-%{+YYYY.MM.dd}.
With that being said, the documents will get indexed into indices with the prefix 'logstash-' followed by the date of ingestion. For example:
logstash-2020.04.07
logstash-2020.04.08
Since someone in your organization has chosen to go with the default value, this option can be left out. This explains why you can't find a particular index name in the Logstash configuration. If you need to index documents into different indices, then you'd have to set a particular value for the index option.
Elasticsearch will automatically create these indices with a dynamic mapping (https://www.elastic.co/guide/en/elasticsearch/reference/current/dynamic-mapping.html) if you haven't setup an explicit mapping via index templates in advance. In order to see the data in kibana, you first need to create an index pattern matching the index name.
I hope I could help you.
I have a working ELK with input coming from filebeat prospecting several log files and sending them to logstash. Logstash retrieves the stream, filters that in order to match lines with some fields and then sends them into elasticsearch.
Now I would like to check before output to elasticsearch, if for a coming entry into elasticsearch, there is already an existing document. If yes, I want to apply another output plugin instead of elasticsearch.
Consider the following use case:
I want the information from one particular log line to be indexed into Elasticsearch, as a document X.
I want the information from some log line further down the log file to be indexed into the same document X (not overriding the original, just adding more data).
The first part, I can obviously achieve with filebeat.
For the second, does anyone have any idea about how to approach it? Could I still use filebeat + some pipeline on an ingest node for example?
Clearly, I can use the ES API to update the said document, but I was looking for some solution that doesn't require changes to my application - rather, it is all possible to achieve using the log files.
Thanks in advance!
No, this is not something that Beats were intended to accomplish. Enrichment like you describe is one of the things that Logstash can help with.
Logstash has an Elasticsearch input that would allow you to retrieve data from ES and use it in the pipeline for enrichment. And the Elasticsearch output supports upsert operations (update if exists, insert new if not). Using both those features you can enrich and update documents as new data comes in.
You might want to consider ingesting the log lines as is to Elasticearch. Then using Logstash, build a separate index that is entity specific and driven based on data from the logs.
Is there a way to tell logstash to remove/update some log entries from Elasticsearch? It seems that Logstash can index documents but I didn't find evidence that it can make update/delete operations.
If it is possible, we could imagine that we could "log" operations on Elasticsearch and use Logstash to output them in bulk in Elasticsearch. This way the programmer doesn't have to create a mechanism to make bulk operations on Elasticsearch.
Everything is in the docs.
To update an entry with Logstash, you need to provide the document id in document_id and the document will be replaced with the new content.
To delete a document with logstash, provide it's id in document_id and set the action field to "delete".
How are events indexed and stored by Elasticsearch when using ELK (Elastichsearch, Logstash, Kibana)
How does Elasticsearch work in ELK
Looks like you got downvoted for not just reading up at elastic.co, but...
logstash picks up unstructured data from log files and other sources, transforms it into structured data, and inserts it into elasticsearch.
elasticsearch is the document repository. While it's not useful for log information, it's a text engine at heart and can analyze the data (tokenization, stop words, stemming, etc).
kibana reads from elasticsearch and allows you to explore the data and make dashboards.
That's the 30,000-ft overview.
Elasticsearch have the function of database on ELK Stack.
You can read more information about Elasticsearch and ELK Stack here: https://www.elastic.co/guide/en/elasticsearch/guide/current/index.html.
first of all you will have logs file that you used to write system logs on it
for example when you add new record to database you will write the record in any form you need to log file like
date,"name":"system","serial":"1234" .....
after that you will add your configuration in logstash to parse the data from the logs
and it will be like
name : system
.....
and the data will saved in elastic search
kibana is used to preview the elastic search data
and you can use send a request to elasticsearch with the required query and get your data from it