ELG Stack Setup and Installation Guide | Generated by AI

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Overview of ELG Stack (Elasticsearch, Logstash, Grafana)

The ELG stack (often a variant of the ELK stack where Kibana is replaced by Grafana for visualization) is a powerful open-source suite for collecting, processing, storing, and visualizing large volumes of data, particularly logs from applications, servers, and infrastructure. It enables real-time monitoring, analytics, and alerting. Key components:

• Elasticsearch: A distributed search and analytics engine for storing, searching, and analyzing data at scale.
• Logstash: A data processing pipeline that ingests data from multiple sources, transforms it, and sends it to Elasticsearch.
• Grafana: A visualization and monitoring dashboard tool that connects to data sources like Elasticsearch for creating charts, graphs, and alerts.

This guide assumes basic Linux knowledge (e.g., Ubuntu/Debian; adapt for other OSes). Use official docs for full details. Installation via downloads from elastic.co and grafana.com.

1. Install Elasticsearch

Elasticsearch handles data storage and indexing.

• Prerequisites: Java 11+ (install via sudo apt update && sudo apt install openjdk-11-jdk).
• Download and install:

  wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo apt-key add -
  echo "deb https://artifacts.elastic.co/packages/7.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-7.x.list
  sudo apt update && sudo apt install elasticsearch
  

• Start and enable: sudo systemctl start elasticsearch && sudo systemctl enable elasticsearch.
• Verify: Visit http://localhost:9200 – should return JSON with cluster info.
• Basic config (edit /etc/elasticsearch/elasticsearch.yml): Set network.host: 0.0.0. for remote access (secure with TLS/firewall in production).

2. Install Logstash

Logstash pulls data from sources (e.g., files, syslogs) and ships it to Elasticsearch.

• Install alongside Elasticsearch:

  sudo apt install logstash
  

• Start and enable: sudo systemctl start logstash && sudo systemctl enable logstash.
• Example config for ingesting logs (/etc/logstash/conf.d/simple.conf):

  input {
    file {
      path => "/var/log/syslog"
      start_position => "beginning"
    }
  }
  filter {
    grok {
      match => { "message" => "%{SYSLOGTIMESTAMP:timestamp} %{SYSLOGHOST:host} %{WORD:program}: %{GREEDYDATA:message}" }
    }
  }
  output {
    elasticsearch {
      hosts => ["localhost:9200"]
    }
    stdout { codec => rubydebug }
  }
  

• Test pipeline: sudo /usr/share/logstash/bin/logstash -f /etc/logstash/conf.d/simple.conf (run in background for persistent use).
• Reload config: sudo systemctl restart logstash.

3. Install Grafana

Grafana provides dashboards for visualizing Elasticsearch data.

• Install:

  wget -q -O - https://packages.grafana.com/gpg.key | sudo apt-key add -
  echo "deb https://packages.grafana.com/oss/deb stable main" | sudo tee /etc/apt/sources.list.d/grafana.list
  sudo apt update && sudo apt install grafana
  

• Start and enable: sudo systemctl start grafana-server && sudo systemctl enable grafana-server.
• Access: Visit http://localhost:3000 (default login: admin/admin; change password).
• Connect to Elasticsearch:
  1. Go to Configuration > Data Sources > Add data source.
  2. Select “Elasticsearch”, set URL to http://localhost:9200, index name (e.g., logstash-*), and time field (e.g., @timestamp).
  3. Save and test connection.

Setting Up the Full ELG Pipeline

1. Data Flow: Logstash collects/parses logs → sends to Elasticsearch → Grafana queries and visualizes.
2. Example Workflow:
   • Send sample data: Use Logstash input plugins or tools like stdout for testing.
   • Index in Elasticsearch: Logs appear as documents (e.g., via Kibana API or direct curl: curl -X GET "localhost:9200/_search?pretty").
   • Dashboard in Grafana: Create panels (e.g., line chart for log errors over time using Lucene queries like program:kern*).
3. Security Basics: Use HTTPS/TLS, authentication (e.g., X-Pack for Elasticsearch), and firewalls. For production, scale with multiple nodes/cluster.
4. Monitoring: Enable JVM monitoring in Elasticsearch; Grafana has built-in alerts for thresholds.

Common Issues and Tips

• Out of Memory: Increase JVM heap in /etc/elasticsearch/jvm.options (e.g., -Xms1g -Xmx1g).
• Port Conflicts: Default ports: Elasticsearch 9200/9300, Logstash 5044, Grafana 3000 – check netstat -tulpn.
• Performance: Use beats (e.g., Filebeat) instead of Logstash for lightweight shipping.
• Learning Resources: Elastic’s official guides (elastic.co/guide), Grafana docs (grafana.com/docs). Practice with Docker: Search for “ELG stack Docker Compose” on GitHub.

For custom setups or troubleshooting specific errors, provide more details. This is a starting point; ELG excels in log analysis, IoT data, and app monitoring.

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