diff --git a/_posts/2016-01-11-log-aggregation.md b/_posts/2016-01-11-log-aggregation.md index aec7368..f16116f 100644 --- a/_posts/2016-01-11-log-aggregation.md +++ b/_posts/2016-01-11-log-aggregation.md @@ -20,8 +20,8 @@ The problems it tackles are: One of the most prolific open source solutions on the market is the [ELK stack](https://www.elastic.co/videos/introduction-to-the-elk-stack) created by Elastic. -<{:.center}> -![Log aggregation Elk]({{ site.url }}/images/logaggregation-elk.png){:style="margin:auto; width:50%"} +{:.center} +![Log aggregation Elk]({{ site.url }}/images/logaggregation-elk.png){:style="margin:auto; width:70%"} ELK stands for Elasticsearch – Logstash – Kibana and they are respectively their Search engine, Log Shipper and Visualization frontend solutions. Elasticsearch becomes the nexus for gathering and storing the log data and it is not exclusive to Logstash. @@ -29,7 +29,7 @@ Elasticsearch becomes the nexus for gathering and storing the log data and it is Another very good data collection solution on the market is Fluentd, and it also supports Elasticsearch (amongst others) as the destination for it’s gathered data. So using the same data repository and frontend solutions, this becomes the EFK stack and if you do a bit of searching you will discover many people have chosen to substitute Elastic's logstash with FluentD and we will talk about why that is in a minute. {:.center} -![Log aggregation Efk]({{ site.url }}/images/logaggregation-efk.png){:style="margin:auto; width:20%"} +![Log aggregation Efk]({{ site.url }}/images/logaggregation-efk.png){:style="margin:auto; width:50%"} # Logstash vs FluentD Both of them are very capable, have [hundreds](https://www.elastic.co/guide/en/logstash/current/input-plugins.html) and [hundreds](http://www.fluentd.org/plugins) of plugins available and are being maintained actively by corporation backed support.