Build a Central Linux Logging Server to Collect, Store, and Visualize All Infrastructure node Logs

Friday, 20th March 2026

build-a-central-linux-logging-server-to-collect-store-and-visualize-all-infrastructure-node-logs
If you manage multiple servers or collection of multiple services on many nodes within a company server infrastructure, you know the pain of dealing with logs scattered to multiple locations across systems. It is really crazy and takes up a lot of time and drains energy.
One server shows nothing, another rotated logs yesterday, and your app logs are buried somewhere in /var/log/app.

A central logging server solves this problem, as all logs collected, stored, and accessible in one single place.

In this article will present shortly how to build one using ELK Stack + Beats (lightweight agents) on a Linux server.

1. Architecture Overview

Here’s the typical flow looks like this:

[ Servers / Apps ] –> [ Filebeat / Metricbeat ] –> [ Logstash ] –> [ Elasticsearch ] –> [ Kibana / Grafana (Visualization) ]

  • Beats → Lightweight log shippers installed on all machines.
  • Logstash → Optional pipeline for parsing, filtering, and enriching logs.
  • Elasticsearch → Storage and search engine.
  • Kibana / Grafana → Visualization dashboards.

2. Prepare Your Central Logging Server

Requirements:

  • Debian Linux 12 recommended / Ubuntu or Fedora RHEL
  • At least 4 GB RAM (8+ GB for production ELK)
  • Plan enough SSD storage (logs grow fast)
  • Open ports: 5044 for Beats, 9200 for Elasticsearch, 5601 for Kibana

Install Prerequisites

# apt update && sudo apt install openjdk-17-jdk wget curl apt-transport-https -y

ELK requires Java, OpenJDK 17 should work fine.

3. Install Elasticsearch

# wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-8.11.1-amd64.deb
# dpkg -i elasticsearch-8.11.1-amd64.deb
# systemctl enable elasticsearch
# systemctl start elasticsearch


Check ElasticSearch server is running:

# curl -X GET "localhost:9200/"

That should see the Cluster info in JSON format.

4. Install Kibana

# wget https://artifacts.elastic.co/downloads/kibana/kibana-8.11.1-amd64.deb
# dpkg -i kibana-8.11.1-amd64.deb
# systemctl enable kibana
# systemctl start kibana


Access Kibana URL in browser:

http://<server-ip>:5601

5. Install Logstash to Process logs before sending to Elasticserch

# wget https://artifacts.elastic.co/downloads/logstash/logstash-8.11.1.deb
# dpkg -i logstash-8.11.1.deb
# systemctl enable logstash
# systemctl start logstash

Logstash allows filtering and structuring logs before sending them to Elasticsearch. Example simple pipeline:

# vim /etc/logstash/conf.d/syslog.conf

input {
  beats {
    port => 5044
  }
}
filter {
  grok { match => { "message" => "%{SYSLOGTIMESTAMP:timestamp} %{SYSLOGHOST:host} %{DATA:program}: %{GREEDYDATA:message}" } }
}
output {
  elasticsearch {
    hosts => [“localhost:9200”]
    index => "central-logs-%{+YYYY.MM.dd}"
  }
}

Start Logstash

# systemctl restart logstash

6. Install Beats on Client Machines

On each server you want to monitor:

# apt install filebeat metricbeat -y


Configure Filebeat

Edit config

# vim  /etc/filebeat/filebeat.yml

Set the output to your central server:

output.logstash:

hosts: [":5044"]

Start the agent:

systemctl enable filebeat
systemctl start filebeat

Do the same for Metricbeat if you want metrics like CPU, memory, disk.

7. Create Dashboards in Kibana or Grafana

  • In Kibana, use Discover to view logs.
  • Create visualizations for errors, warnings, top endpoints, etc.
  • Use Grafana if you want multi-source dashboards, combining logs and metrics.

8. Optional: Secure Your Logging Server

  • Enable TLS/SSL in Beats and Elasticsearch.
  • Use firewall rules to restrict access.
  • Create dedicated users in Elasticsearch for log access.

9. Maintenance Tips

  • Index Lifecycle Management → Rotate daily and delete old logs automatically.
  • Monitor disk usage → Logs grow fast. SSDs are better.
  • Filter noise → Don’t ship debug logs unless needed.
  • Backup Elasticsearch → Especially if logs are critical.

Sum Up, how it Works

  • All logs are centralized → easier troubleshooting.
  • Scalable → add new servers, Beats handle shipping automatically.
  • Searchable → find errors instantly using Elasticsearch.
  • Visual → dashboards in Kibana/Grafana give real-time insight.

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