Filebeats s3 plugin4/20/2023 So we need to keep track of a couple of files: We are going to look into linux and oracle auditing. There are and could be multiple input products, in this blogpost I use ‘filebeat’, which keeps track of logfiles. The last part of the data pipeline is ‘filebeat’. Logstash uses upstart (meaning a startup script in /etc/init) instead of the legacy startup mechanism using the chkconfig and service utilities. It does not mean it will all work as desired, there could be runtime issues. If you see the ‘Configuration OK’ message, it means logstash could interprent the configuration files. Sending Logstash's logs to /var/log/logstash which is now configured via log4j2.properties # sudo -u logstash /usr/share/logstash/bin/logstash ttings /etc/logstash -t In order to make the installation really easy, I use the yum repository of the elastic company, this is how to set that up (all done as root, ‘#’ indicates root): The below install actions were executed on a Linux 64 bit host running Oracle Linux 6.8. In reality you should have a log gatherer on every host (called ‘filebeat’) and a dedicated host which runs the rest of the stack (logstash, elasticsearch and kibana). In this blogpost I will install everything on the same host, everything being the ELK stack and an Oracle database installation. Installing the ELK stack in a basic way is easy. When looking at Kibana, it quite much looks like the splunk interface. – Kibana is an open source data visualisation plugin for Elasticsearch. – Logstash is a fully configurable open source data processing pipeline that can receive data from a multiple sources simultaneously, transform it and output it based on the output plugin, which is the elastic search plugin in this blogpost but could be anything from STDOUT, an unix pipe, a file, a file in CSV, HTTP, email, IRC, Jira, graphite, kafka, mongodb, nagios, S3, SolR, … really whatever you want. – Elasticsearch is an open source search engine based on Apache Lucene, which provides a distributed, multitenant-capable full-text search engine with a http web interface and schema-free JSON documents. The ELK stack gets it’s name from Elasticsearch, Logstash and Kibana. This blog post is about two things: one how you can monitor who is bringing you database up and down (there is a twist at the end!) and two how you can very conveniently do that with aggregated logs in a browser with a tool called ‘Kibana’, which is the K in ELK.
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