We are using ELK and shoving all syslogs into Elasticsearch.
I have a log type like whose message field looks like:
"message":"11/04/2016 12:04:09 PM|There are now 8 active connections#015"
I would like to use Kibana to parse the message to get the number of active connections over time and then graph that in Kibana.
Am I thinking of how to do this correctly?
The reading I've done seems to be telling me to set up a filter in Logstash...but that seems like the wrong place to parse the message field for this single log line type, given the amount of messages/logs and message/log types getting sent through Logstash.
Is there a way to parse the message field for this number and then graph that count over time in Kibana?
Kibana is not meant to do this kind of parsing. There are a few options you can use:
You could write an analyser that analyses this string. It can be
done, but I would not do it like this.
Use logstash, but you already suggested that yourself. If you feel
log stash is to heavy and you have a choice for the version to use,
go for option three.
Use ingest, this is a new feature of elasticsearch. This is kind of
a lightweight logstash that comes pre-packaged with elastic, it
support patterns with grok that can do this.
Related
I have configured Fluent-bit on my ECS cluster . I can see the logs in Kibana. But all the log data are sent to a single field "log". How can I extract each field into a separate field. There is a solution for fluentd already in this question.
But how can I achieve the same with fluent-bit?
There is a solution in Kuberntetes with fluent-bit: https://docs.fluentbit.io/manual/filter/kubernetes
How do I achieve the same thing in ECS?
Generally fluent-bit send exactly docker log file that taking from /var/lib/docker/containers/*/*.log
You can browse this path on your machine and see that it contains JSON strings with exactly two fields you mentioned.
From here you have number ways, I'll discover two that I know well:
Use logstash:
You should know well the log structure. This helps you to create the right filters pipeline for the parse log field. Usually, people use filter plugins for this. If you add log examples I will be able to make an example of a filter like this
Use the elasticsearch ingest node.
You should know well the log structure. For be able easy to create processors pipeline for parse log field. More one time, specific log examples help's us to help you.
The most used filter/processor is grok filter/processor. This tool have a lot of options for parse structured text from any log.
I have a large ingestion pipeline, and sometimes it takes awhile for things to progress from source to the Elasticsearch index. Currently, when we parse our messages with Logstash, we parse the #timestamp field based on when the message was written by the source. However, due to large volumes of messages, it takes a currently unknown and possibly very inconsistent length of time to travel from the source producer before it's ingested by Logstash and sent to the Elasticsearch index.
Is there a way to add a field to the Elasticsearch output plugin for Logstash that will mark when a message is sent to Elasticsearch?
You can try to add a ruby filter as your last filter to create a field with the current time.
ruby {
code => "event.set('fieldName', Time.now())"
}
You can do it in an ingest pipeline. That means the script is executed in elasticsearch, so it has the advantage of including any delays caused by back-pressure from the output.
i have an issue which i suspect is quite basic but i have been stuck on this for too long and i fear i am missing something so basic that i can't see it by now.
we are using the ELK stack today for log analysis of our application logs.
logs are created by the JAVA application into JSON format, shipped using filebeat into logstash which in turn processes the input and queues it into ES.
some of the messages contain unstructured data in the message field which i currently cannot parse into separate fields so i need to catch them in the message field. problem is this:
the string i need to catch is: "57=1" this is an indication of something which i need to filter documents upon. i need to get documents which contain this exact string.
no matter what i try i can't get kibana to match this. it seems to always ignore the equal char and match either 57 or 1.
please advise.
thanks
You may check the Elasticsearch mapping on the field type of the referring field. If it is analyzed, the '=' may not have been indexed due to the default-analyzer. (source 1, source 2)
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.
Basic usecase that we are trying to solve is for users to be able to search from the contents of the log file .
Lets say a simple situation where user searches for a keyword and this is present in a log file which i want to render it back to the user.
We plan to use ElasticSearch for handling this. The idea that i have in mind is to use elastic search as a mechanism to store the indexed log files.
Having this concept in mind, i went through https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html
Couple of questions i have,
1) I understand the input provided to elastic search is a JSON doc. It is going to scan this JSON provided and create/update indexes. So i need a mechanism to convert my input log files to JSON??
2) Elastic search would scan this input document and create/update inverted indexes. These inverted indexes actually point to the exact document. So does that mean, ES would store these documents somewhere?? Would it store them as JSON docs? Is it purely in memory or on file sytem/database?
3) No when user searches for a keyword , ES returns back the document which contains the searched keyword. Now do i need to have the ability to convert back this JSON doc to the original log document that user expects??
Clearly im missing something.. Sorry for asking questions this silly , but im trying to improve my skills and its WIP.
Also , i understand that there is ELK stack out there. For some reasons we just want to use ES and not the LogStash and Kibana part of the stack..
Thanks
Logs needs to be parsed to JSON before they can be inserted into Elasticsearch
All documents are stored on the filesystem and some data is kept in memory but all data is persistent.
When you search Elasticsearch you get back matching JSON documents. If you want to display the original error message, you can store that original message in one of the JSON fields and display just that.
So if you just want to store log messages and not break them into fields or anything, you can simply take each row and send it to Elasticsearch like so:
{ "message": "This is my log message" }
To parse logs, break them into fields and add some logic, you will need to use some sort of app, like Logstash for example.